| |
Biostatistics |
| |
-
BIOST 2011 - PRINCIPLES OF STATISTICAL REASONING
Minimum Credits: 3
Maximum Credits: 3
Acquaints students with the concepts of statistical reasoning as applied to the study of public health problems. Students learn the general principles of statistical analysis and acquire the ability to utilize a statistical software package (Minitab) as a tool to facilitate the processing, editing, storing, displaying, analysis and interpretation of health research related data.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PROG: Graduate School of Public Health; PLAN: Excluded Plans = Biostatistics(DPH, PHD, MPH, MS, MSH)
Course Attributes: Global Studies
|
| |
-
BIOST 2016 - SAMPLING DESIGN AND ANALYSIS
Minimum Credits: 2
Maximum Credits: 2
This is an applied statistical methods course designed to provide students with a working knowledge of introductory and intermediate-level sample designs and associated methods of statistical analysis along with a basic understanding of the theoretical underpinnings. Emphasis is placed on sampling human populations in large communities. Students will also learn statistical software used in survey data analysis, including sample selection and survey procedures in the STATA software package. Lecture topics include: simple probability samples, stratified sampling, ratio and regression estimation, cluster sampling, sampling with unequal probabilities, variance estimation and weighting in complex surveys, two-phase sampling, estimating population size and estimation of rare populations and small areas. The course will consist of one weekly 2-hour lecture and one class devoted to student presentations related to a term project assigned at midterm.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2011 or 2039 or 2041; PROG: Graduate Sch of Public Health (PPBHL)
|
| |
-
BIOST 2021 - SPECIAL STUDIES
Minimum Credits: 1
Maximum Credits: 15
Qualified students may undertake advanced work or research with the approval and under the guidance of a member of the staff.
Academic Career: Graduate
Course Component: Independent Study
Grade Component: Grad SN Basis
|
| |
-
BIOST 2025 - BIOSTATISTICS SEMINAR
Minimum Credits: 1
Maximum Credits: 1
Biometry seminars introduce the students to current health problems involving the application and development of biostatistics methods and theory.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad SN Basis
|
| |
-
BIOST 2036 - INTRODUCTION TO HEALTH DATA SCIENCE
Minimum Credits: 2
Maximum Credits: 2
This course will teach students methods and concepts in data science that are motivated by real life problems in public health. Students will become familiar with data science terms such as data wrangling. Students will learn the concepts of exploratory data analysis, data cleaning, data wrangling, and visualization. Students will learn the necessary skills to tidy, manage, and visualize data and communicate results. This course will mainly use the R programming language but will also teach certain concepts in SQL and Python. The course lectures will cover the following general themes: data structures and representation, data wrangling and processing, computational tools and techniques, and case studies illustrating steps of analysis of real data, including examples from public health.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PLAN: Biostatistics (MS or PHD)
|
| |
-
BIOST 2038 - FOUNDATIONS OF STATISTICAL THEORY
Minimum Credits: 3
Maximum Credits: 3
The course covers basic theory of probability and statistical inference with a focus on appropriate use of standard methods and construction of new statistical inference tools. Topics covered in the first half include joint, marginal, and conditional probabilities; random variables and functions thereof; distribution characteristics of random variables; basic asymptotic theory and univariate theorems including Chebyshev’s inequality, law of large numbers, and central limit theorem. Topics covered in the second half include principles and methods of constructing estimators (e.g., MLE, MME,CRLB), confidence intervals, and hypothesis testing (including Neyman-Person and Generalized Likelihood Ratio tests); data reduction principles and techniques, and their relationship to optimal statistical inference (e.g., sufficiency, Rao-Blackwell principle); basic likelihood-based, exact, conditional, and asymptotic statistical inference.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PLAN: Biostatistics (MS)
|
| |
-
BIOST 2039 - BIOSTATISTICAL METHODS
Minimum Credits: 3
Maximum Credits: 3
This course is an introductory biostatistics methods course for biostatistics graduate students, other quantitative public health students, and health career professionals who will make use of statistical methods in research projects, interpreting literature and possibly develop new biostatistical methods in the future. This class is intended for students needing a more research-oriented approach than that provided in BIOST 2011 and an approach with a greater emphasis on mathematical foundation than provided in BIOST 2041. Students in BIOST 2039 are expected to have a working knowledge of calculus, including multivariable differentiation and integration. Topics covered in this course include exploratory and descriptive analyses, probability, estimation and hypothesis testing. One and two sample problems will be considered for both continuous and discrete variables. ANOVA, regression, correlation and nonparametric methods will be discussed. R will be used extensively for data analysis.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PLAN: BIOST-MS, PHD
|
| |
-
BIOST 2040 - ELEMENTS OF STOCHASTIC PROCESSES
Minimum Credits: 3
Maximum Credits: 3
Covers generating functions and convolutions of random variables, the poison and compound poison distributions, branching processes, random walk, and the gambler’s ruin problem, Markov chains, and simple birth and death processes.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2043
|
| |
-
BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS
Minimum Credits: 3
Maximum Credits: 3
Discusses techniques for the application of statistical theory to actual data. Topics include probability theory, estimation of parameters, and tests of hypothesis for both the discrete and continuous case.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
|
| |
-
BIOST 2042 - INTRODUCTION TO STATISTICAL METHODS 2
Minimum Credits: 3
Maximum Credits: 3
More techniques are given for the application of statistics to actual data with emphasis on distribution-free and multivariate methods. Interpretation of results and concepts will be stressed.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2041
|
| |
-
BIOST 2043 - INTRODUCTION TO STATISTICAL THEORY 1
Minimum Credits: 3
Maximum Credits: 3
Covers joint, marginal, and conditional probabilities; distributions of random variables and functions of random variables; expectations of random variables and moment generating functions; law of large numbers; central limit theorem.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
|
| |
-
BIOST 2044 - INTRODUCTION TO STATISTICAL THEORY 2
Minimum Credits: 3
Maximum Credits: 3
Covers elements of statistical inference; sampling distributions of estimators; Rao-Cramer’s Inequality; problems of testing statistical hypotheses; Neyman-Pearson lemma; likelihood ratio tests.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2043
|
| |
-
BIOST 2046 - ANALYSIS OF COHORT STUDIES
Minimum Credits: 3
Maximum Credits: 3
This introductory applied course in statistical modeling focuses on maximum likelihood and related regression methods for the analysis of cohort data. Topics include generalized linear models, generalized estimating equations, and generalized linear mixed models. The course emphasizes logistic and poisson regression, and discrete survival models with time-dependent covariates. Students analyze several cohort data sets, assess the adequacy of their models, and interpret their results.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2042 and 2049
|
| |
-
BIOST 2049 - APPLIED REGRESSION ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
This is an introductory course in statistical modelling intended for Masters or PhD students in biostatistics or other disciplines who have already had basic training in statistical methods. The course focuses on all types of regression methods with the following learning objectives: To fit and interpret linear regression models with multiple continuous and/or categorical predictors. To fit and interpret generalized linear models (GLMs) with emphasis on logistic and Poisson regression. To justify and apply standard modelling procedures using data, including model interpretation and assessment of model adequacy. To analyze data sets taken from the fields of medicine and public health. To develop oral and written communication skills through the description of analytic strategies and the summarization and interpretation of results.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2039 or BIOST 2041
|
| |
-
BIOST 2050 - LONGITUDINAL AND CLUSTERED DATA ANALYSIS
Minimum Credits: 2
Maximum Credits: 2
This introductory course in statistical modeling is intended for MS students in biostatistics and PhD students in biostatistics or epidemiology in their second year of graduate work. This course may be thought of as the third methods course in Biostatistics following BIOST 2041/2039 and BIOST 2049. The course focuses on regression methods for the analysis of longitudinal or more generally clustered data with emphasis on generalized estimating equation. The course objectives are to introduce generalized estimating equations (GEEs), mixed models, and generalized linear mixed models from an applied perspective to analyze longitudinal and clustered data, to understand the justification and applicability of standard procedures to standard problems, including model interpretation and assessment of model adequacy.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2049; PROG: Graduate Sch of Public Health
|
| |
-
BIOST 2051 - STATISTICAL ESTIMATION THEORY
Minimum Credits: 3
Maximum Credits: 3
Fisher’s information; Rao-Cramer Inequality and Sufficient Statistics; Bhattacharyya Bounds; Rao-Blackwell Theorem; Methods of Moments; the Method of Maximum Likelihood; Newton-Raphson Method and Rao’s Scoring for Parameters; estimation of several parameters; order statistics and life testing problems; estimation with censored data and survival analysis.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2039 and 2044; PLAN: Biostatistics (PHD)
|
| |
-
BIOST 2052 - MULTIVARIATE ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
Multivariate normal distribution, estimation of the mean vector and covariance matrix, distributions and uses of simple, partial and multiple conclation correlation coefficients, generalized T2 statistic, distribution of the sample generalized variance, Multivariate Analysis of Variance and the Multivariate Behrens-Fisher problem. Multivariate methods applied to repeated measures analysis, factor analysis, and discriminant analysis. Beginning of the course emphasizes theory; later, applications and computational methods emphasized. Lectures are of current and classical literature.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2044
|
| |
-
BIOST 2054 - SURVIVAL ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
Introduces the student to the design considerations and statistical analysis of clinical trials. Covers the theoretical aspects of various models in reliability theory and the proportional hazards model, as well as the more applied problems of interpreting specific data sets and designing large-scale trials.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BIOST 2039 and 2044
|
| |
-
BIOST 2055 - INTRODUCTORY HIGH-THROUGHPUT GENOMIC DATA ANALYSIS 1: DATA MINING AND APPLICATIONS
Minimum Credits: 3
Maximum Credits: 3
This course is a graduate level introduction and overview of modern high-throughput genomic data analysis. It is designed for graduate students in biostatistics and human genetics who are interested in the technology and elementary data mining of high-throughput genomic data (including but not limited to classical expression arrays, various array-based applications, next-generation sequencing and proteomics). The course is also helpful for biology students with basic quantitative training (e.g. two elementary statistics courses and R programming) who have interests in understanding the intuition and logic underlying the data analysis methods. R is the major language used in the course.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2039; PLAN: Biostatistics (MS or PHD)
|
| |
-
BIOST 2056 - INTRODUCTION TO DIAGNOSTIC TEST EVALUATION AND ROC ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
The course offers an introduction to concepts and approaches for statistical assessment of diagnostic systems and ROC analysis. The covered material includes different measures of diagnostic accuracy, aspects of the design of accuracy studies, statistical estimation and hypothesis testing, sample size calculation and some advanced topics. General prerequisites include knowledge of basic statistical concepts and approaches related to estimation and hypothesis testing; some knowledge of regression modeling and SAS is desirable.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2038 and 2039; PLAN: Biostatistics (PHD,MS)
|
| |
-
BIOST 2058 - SCIENTIFIC COMMUNICATION SKILLS
Minimum Credits: 2
Maximum Credits: 2
This course is meant to help students develop oral, visual and written scientific communication skills and to familiarize students with research resources. Students may use their own research topic, including work on a thesis or dissertation, or help will be provided in selecting one.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
|
| |
-
BIOST 2059 - CONSTRAINED STATISTICAL INFERENCE WITH APPLICATIONS
Minimum Credits: 2
Maximum Credits: 2
This is an applied biostatistics course for biostatistics graduate students, other quantitative public health students, and health career professionals who will make use of statistical methods in research projects and possibly develop new biostatistical methods in the future. While this course is intended to be an application oriented course motivated by real scientific problems, it will rely on some statistical theory. Students are expected to have basic understanding of statistical theory at the level of BIOST 2044 (Introduction to Statistical Theory 2) and have applied analysis skills at the level of BIOST 2049 (Applied Regression Analysis). Additionally, students are expected to have working knowledge of the programming language R.
Topics covered in this course include: (a) Brief review of some important concepts from BIOST 2043, BIOST 2044 and BIOST 2049, such as parametric and nonparametric estimation and testing of hypotheses, linear fixed and mixed effects models, best linear unbiased predictor (BLUP) and generalized linear models. (b) Some real world motivating examples of various types of constraints on parameter spaces. Reasons for constrained inference. (c) Estimation of parameters and testing of hypotheses under inequality constraints in a variety of settings - challenges and solutions. Various estimation and testing procedures such as Pool Adjacent Violators Algorithm (PAVA), Restricted Maximum Likelihood Estimation (RMLE), Isotonic Regression, Likelihood Ratio Test (LRT), Williams’ test, Dunnett’s test, Jonckheere-Terpstra test. Substantial reduction in samples sizes and gain in power when using constrained inference based methods in comparison to standard methods. (e) Resampling methods for constrained inference, why they fail for confidence intervals but are suitable for some testing problems. (f) Nonparametric problems - various notions of orderings of random variables, univariate and multivariate analysis. (g) Applications in clinical trials, toxicology, high dimensional gene expression studies, microbiome, cell-cycle and circadian clock.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2044 and BIOST 2049
|
| |
-
BIOST 2061 - LIKELIHOOD THEORY AND APPLICATION
Minimum Credits: 2
Maximum Credits: 2
The purpose of this course is to introduce the student to modern likelihood theory and its applications. The course will cover maximum likelihood theory, profile likelihood theory, pseudo likelihood theory and generalized estimating equations. The course is taught at a doctoral level and much of the theory is illustrated through applications.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2044
|
| |
-
BIOST 2062 - CLINICAL TRIALS: METHODS AND PRACTICE
Minimum Credits: 3
Maximum Credits: 3
The course lectures integrate web-based material covering fundamental concepts in the design and conduct of modern clinical trials. Topics include: experimental designs, interim monitoring, analysis methods for comparative clinical trials, ethical, organizational, and practical considerations of design, case studies, and international guidelines for publication of trials in major journals, and meta-analyses.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2039 and 2093; PLAN: Biostatistics (MS,MPH, or PHD)
|
| |
-
BIOST 2063 - BAYESIAN DATA SCIENCE
Minimum Credits: 3
Maximum Credits: 3
This is a course in Bayesian methods for applied statistics and data science whose broad goal is to provide students with the skills needed to be able to select, conduct, report and interpret appropriate Bayesian analyses for a wide variety of applied problems. General topics covered include Bayesian concepts of statistical inference, Markov chain Monte Carlo and other computational methods, linear, hierarchical and generalized linear models, model selection and diagnostics, and Bayesian learning. The course explores the use of the popular and free software packages R, JAGS and Stan for conducting Bayesian analyses.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: (BIOST 2039 or 2041) and BIOST 2049
|
| |
-
BIOST 2065 - ANALYSIS OF INCOMPLETE DATA
Minimum Credits: 3
Maximum Credits: 3
This course will present missing-data problems in statistics and discuss nave methods such as complete-case analysis, available-case analysis and imputation; standard likelihood- based methods, theory and application of multiple imputation, data augmentation, Gibbs sampler, and some recently developed methodologies in the missing-data literature and related fields.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2049 and 2051 and 2061
|
| |
-
BIOST 2066 - APPLIED SURVIVAL ANALYSIS: METHODS AND PRACTICE
Minimum Credits: 2
Maximum Credits: 2
This course covers fundamental concepts and methods important for analysis of datasets where the outcome is the time to an event of interest, such as death, disease occurrence or disease progression. Topics include: basic methods for summarizing and presenting time-to-event data in tabular form and graphically as life tables, non-parametric statistical techniques for testing hypotheses comparing life tables for two or more groups; approaches to fitting the semi-parametric Cox proportional hazard model and other commonly used parametric models that incorporate study co-variables, methods for assessing goodness-of-fit of the models, and sample size considerations. In addition to didactic lectures, there are group projects that involve analysis of datasets and presentation of analytic reports in the classroom.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2049; PLAN: Biostatistics (PHD,MS)
|
| |
-
BIOST 2069 - STATISTICAL METHODS FOR OMICS DATA
Minimum Credits: 2
Maximum Credits: 2
This 2-credit course is a graduate level course to cover popular statistical and computational methods for high-throughput omics data analysis. With the rapid advances of many omics technologies, the course will focus on the fundamental concepts of various topics (e.g. data preprocessing, association analysis, causal mediation analysis, differential analysis, statistical learning, pathway analysis, etc.) and their specific applications to different omics data types (e.g. microarray, next-generation sequencing, single cell sequencing, mass spectrometry, microbiome, etc.). The major target audience is graduate students (master or PhD students) interested in omics data analysis and related research. Through homework problem sets, computer labs and a final project, students train with hands-on materials to understand the methods, implement the algorithms and interpret results in real omics applications.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: Pre-reqs: BIOST 2049; AND BIOST 2038 OR BIOST 2043. PLAN: BIOST-MS or BIOST-PHD
Students are required to have basic R programming ability, which is provided through the three prerequisite courses.
|
| |
-
BIOST 2078 - STATISTICAL LEARNING IN HIGH-DIMENSIONAL DATA WITH OMICS APPLICATIONS
Minimum Credits: 2
Maximum Credits: 2
This 2-credit course is a graduate level course to introduce theories and algorithms for statistical analysis of high-throughput genomic data. Emphases will be given to high-dimensional data analysis and theories behind the commonly used methods. This course is designed for graduate students who already have sufficient statistical background, have basic knowledge of various high-throughput genomic experiments (e.g. already finished BIOST 2055 or MSCBIO 2070) and wish to learn advanced statistical theories for bioinformatics and genomics research. Students are expected to have programming experiences in R (e.g. BIOST 2094) or in other low-level languages such as C, C++, Java and Fortran. The course will meet four hours per week for half a semester.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2039 and 2043; PLAN: Biostatistics (MS, PHD )
|
| |
-
BIOST 2079 - INTRODUCTORY STATISTICAL LEARNING FOR HEALTH SCIENCES
Minimum Credits: 2
Maximum Credits: 2
This 2-credit course is a graduate level course to introduce basic concept and methods for statistical learning with emphasis on modern health science applications. The syllabus includes linear regression with regularization, supervised machine learning, unsupervised clustering, dimension reduction and other special topics (e.g. Bayesian network and hidden Markov model). Target audience will be second year Biostatistics master students or early PhD students with interests in statistical learning techniques for health science data. Through homework problem sets, computer labs and a final project, students train with hands-on materials to implement methods and interpret results in real applications.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2039 and 2043 and 2049; PLAN: Biostatistics(MS or PHD); Students are expected to have programming experiences in R or in some low-level languages such as C, C++, Java and Fortran.
|
| |
-
BIOST 2080 - ADVANCED STATISTICAL LEARNING
Minimum Credits: 2
Maximum Credits: 2
This is a 2-credit course in advanced statistical learning, covering topics related to the statistical interpretation and theory behind machine learning models/methods. Emphases will be given to in-depth derivation of models/algorithms from topics covered in BIOST 2079 (Introductory Statistical Learning for Health Sciences) as well as additional topics on modern statistical learning methodologies, with special focus on methods for health science applications. This course is designed for graduate students in the Department of Biostatistics and other interested graduate students who already have sufficient statistical and programming background. Students are expected to be familiar with R. Experience in C/C++, Python or Matlab may be helpful, but is not required. Programming skills/training shall be demonstrated by previous programming (or programming heavy) courses in R, Python, Matlab, C/C++, etc.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2049 and BIOST 2079; Special Instructions: Programming skills/training shall be demonstrated by previous programming (or programming heavy) courses in R, Python, Matlab, C/C++, etc.
|
| |
-
BIOST 2081 - MATHEMATICAL METHODS FOR STATISTICS
Minimum Credits: 3
Maximum Credits: 3
Differentiation and integration of functions of several variables. Infinite sequences and series. Fundamentals of matrix algebra. Class examples and homework problems will emphasize applications to probability and statistics.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PLAN: Biostatistics (PHD, MS, MPH)
|
| |
-
BIOST 2083 - LINEAR MODELS
Minimum Credits: 3
Maximum Credits: 3
Acquaints students with linear model techniques for analyzing both balanced and unbalanced data. The topics covered include generalized inverses, orthogonal contrasts with unbalanced data, and analysis of covariance. Analysis with computer packaged programs is discussed.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BIOST 2044
|
| |
-
BIOST 2086 - APPLIED MIXED MODELS ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
Mixed model analysis provides a new approach to modeling which allows one to relax the usual independence assumptions and take into account complicated data structures. This course will consider all types of mixed models into a general framework and consider the practical implications of their use. Topics will include; normal mixed models, generalized mixed models, and mixed models for categorical data, repeated measures data analysis and cross-over trials with mixed models. Software for fitting mixed models will be discussed.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2083
|
| |
-
BIOST 2087 - BIOSTATISTICS CONSULTING PRACTICUM
Minimum Credits: 1
Maximum Credits: 1
Provides advanced students (second-year masters and doctoral) with exposure and practical experience in consulting on the bio statistical aspects of research problems arising in the biomedical or other allied fields. Students initially under the supervision of a faculty member participate in discussions with investigators leading to the design and/or analysis of a current research problem.
Academic Career: Graduate
Course Component: Practicum
Grade Component: Grad Letter Grade
|
| |
-
BIOST 2093 - SAS FOR DATA MANAGEMENT AND ANALYSIS
Minimum Credits: 2
Maximum Credits: 2
The goal of this course is to provide students with an understanding of the SAS program environment as well as the skills needed to use SAS as a tool to conduct research, prepare data, and perform analyses. Upon completion of the course the student will have an understanding of SAS at the intermediate level. The course covers the utility of SAS as a data management, data manipulation, and data analysis tool. The focus will not be statistical analysis, but rather how to use SAS as a programming tool. Emphasis will be placed on program code writing. Concepts will be illustrated with numerous examples from basic descriptive analysis.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad HSU Basis
Course Requirements: PREQ: BIOST 2039; PROG: Graduate Sch of Public Health
|
| |
-
BIOST 2094 - ADVANCED R COMPUTING
Minimum Credits: 2
Maximum Credits: 2
An advanced statistical computing course using R designed for graduate level biostatistics students with programming experience in R or other low-level languages such as C, C++, Java, and/or Fortran. Experience in SAS and/or Stata does not qualify. The course will cover topics, including but not limited to, R in modeling and optimization, advanced R graphics, functional programming, object-oriented field guide, efficient computing in R, GUI for R-shiny, embedding C/C++, R package/documentation, Julia, Github etc. The course will also include real life application for students to practice the programming techniques learned in class.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2039 and 2043; PLAN: Biostatistics
|
| |
-
BIOST 2096 - NUMERICAL METHODS BIOSTATISTICS
Minimum Credits: 3
Maximum Credits: 3
The purpose is to familiarize students with a broader range of numerical methods which are useful in bio statistical research. Selected computational techniques used in statistical research will be covered. Background will be provided to facilitate understanding of a few numerical algorithms widely used in statistics. The following are covered: recurrence relations, power series and asymptotic expansions, generating pseudo-random deviates, basic simultaneously methodology, solutions of nonlinear equations, newton’s method, vector and matrix norms, linear regression and matrix inversion.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PREQ: BIOST 2044 and 2049
|
| |
-
BIOST 2099 - CAPSTONE
Minimum Credits: 2
Maximum Credits: 2
The capstone course is a heavily directed and mentored statistical data analysis project course leading to an ETD formatted thesis and formal oral presentation of the work. This course will be an intense data analysis and writing course with the goal of producing an ETD formatted thesis document containing rigorous analytic methods, appropriately summarized analysis results with logical, statistically and scientifically valid conclusions. The Capstone course will ensure that the written thesis milestone demonstrates the student’s competency in biostatistics (and area of concentration if applicable) as well as oral and written communication skills in general.
Academic Career: Graduate
Course Component: Thesis Research
Grade Component: Grad HSU Basis
Course Requirements: PLAN: Biostatistics (MS); Required to have passed MS comprehensive exam.
|
| |
-
BIOST 3010 - RESEARCH AND DISSERTATION PHD
Minimum Credits: 1
Maximum Credits: 15
Academic Career: Graduate
Course Component: Thesis Research
Grade Component: Grad SN Basis
|
Business Accounting |
| |
-
BACC 2060 - INDEPENDENT STUDY IN ACCOUNTING
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Independent Study
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2100 - MACC INTERNSHIP
Minimum Credits: 1
Maximum Credits: 3
To enroll for an IFC through the MACC program, you must be a MACC student and work for a minimum of 10 hours a week for 10 weeks during the semester you intend to take the internship for credit. You may receive up to six internship credits, but only three per semester, and no more than three credits for an experience. The grade for these credits will be pass/fail (satisfactory/unsatisfactory). The deadline to apply for an internship for credit is the date the add/drop period ends for that given semester. All internship offers must be approved by the MACC office prior to enrollment for that experience. Performance appraisals must be submitted to your faculty advisor and to career services and your employer must complete a midpoint and final performance appraisal.
Academic Career: Graduate
Course Component: Internship
Grade Component: Grad HSU Basis
|
| |
-
BACC 2251 - FORENSIC ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
“Fraud is extremely costly to our society, and the costs seem to be growing. The AICPA recently called forensic accounting one of the seven hot, new, “sizzling” career areas in accounting. It is estimated that there will be a shortage of between 25,000 and 50,000 professionals working in this area in the next few years in the U.S., So there are many opportunities for students knowledgeable in fraud to work in various federal agencies (e.g. FBI), major corporations, and professional service firms. The objectives of the forensics course are to familiarize students with several forms of fraud and the methods that fraud examiners use to prevent and detect it. Students will develop expertise in detecting financial statement fraud from the external auditor perspective, and learn how to use technology to detect fraud. They will acquire a basic understanding of how interviews are conducted in order to detect deception. The class will also provide a historical view of financial statement fraud. The tools used in the class will include interviewing, document examination, and public records searches, which will be helpful to students wanting to become consultants, auditors, tax professionals, managers, etc. The class, of course, includes an ethics component. It will help students to understand the common ethical dilemmas that they might encounter in the business world, and will help prepare them to resist pressure to commit fraud.”
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2252 - CORPORATE TAX ACCOUNTING AND PLANNING
Minimum Credits: 3
Maximum Credits: 3
The objective of this course is to help students understand how important features of the internal revenue code influence decisions regarding how to organize and structure business operations and select the most appropriate form of doing business. The course begins with a comparison of the issues surrounding the choice of taxable business entity, comparing the regular corporation (c corporation), the small business corporation (s corporation), the partnership, and the sole proprietorship. After this, the course focuses primarily on the c corporation and the s corporation and the underlying principles that determine their respective tax bases and resulting tax obligations. Tax planning is an integral part of the course. Income shifting, tax deductions, tax credits, and income exclusions are discussed in detail. The course uses case studies (including some reflecting an international tax perspective) and tax return preparation to help students to apply the theory and detail of the tax code. Course materials are updated as tax laws change.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2253 - INTERNATIONAL ACCOUNTING
Minimum Credits: 2
Maximum Credits: 2
This course will explore the rapid movement toward a set of internationally consistent financial reporting methods in the global marketplace. The financial accounting standards board (FSAB) and the international accounting standards board (IASB) have formally agreed to harmonize reporting standards over time. In addition, the securities and exchange commission (sec) is currently considering a proposed time-line for the adoption of international financial reporting standards (IFRS) in the US. The course will examine the substantive differences between us generally accepted accounting principles (us GAAP) and IFRS, which have already been adopted by many other countries. The course will also provide a framework for understanding the theory and application of IFRS versus us GAAP and explore some of the ethical issues inherent in international business reporting.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2254 - ADVANCED FINANCIAL ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
This course covers topics that are of particular interest to financial report preparers and auditors. Special emphasis is placed on accounting for business combinations and consolidated financial reporting. Other topics include international accounting, accounting for partnerships, and accounting by fiduciaries.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PLAN: Accounting (MS)
|
| |
-
BACC 2255 - INTERNAL CONTROLS AND ACCOUNTING DISCLOSURES FOR DERIVATIVES
Minimum Credits: 1.5
Maximum Credits: 1.5
This accounting elective will focus on derivative instruments and their impact on accounting and internal controls. The course will cover various topics tied to derivative instruments including the benefits, hedging, the risks, cash flow implications, internal controls, accounting & reporting requirements, taxation, and regulations. The course will analyze various incidents where internal controls were compromised and the implications. Upon successful completion of this course, the student will have the knowledge and background required to account for, audit, and monitor the use of derivative products. This course will also help those students who plan on sitting for the CPA examination.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BUSACC 1238
|
| |
-
BACC 2256 - STRATEGIC COST MANAGEMENT
Minimum Credits: 3
Maximum Credits: 3
This course deals with strategic implications of alternative methods of product cost measurement. The discussions will primarily be case-based and will include cost measurement issues in both conventional and modern manufacturing environments.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PLAN: Accounting (MS)
|
| |
-
BACC 2258 - STRATEGIC COST MANAGEMENT
Minimum Credits: 3
Maximum Credits: 3
The quality, timeliness and credibility of the cost information used in corporate decision-making can have a significant impact on value creation. This is because cost information is important not only in strategy formulation and in the development and implementation of action plans that link strategies to value creation, but also because such data serve as measures of financial performance for products, processes, organizational sub-units and managers. In particular, product and service cost estimates have a major influence on corporate strategic decisions such as pricing, resource allocation, product development, supply chain design and customer focused management. In addition, product costs are informative signals of operational efficiency. Therefore, they constitute financial measures of the success of management actions such as continuous improvement and business process reengineering. Over-aggregate or obsolete cost systems can have a significant adverse impact on cost reduction in particular and overall corporate strategy and competitiveness in general. The objective of this course is to develop an integrated approach to analyzing these issues. In particular, we will study (a) how product cost measurement affects strategy and resource allocation decisions; (b) how to be sophisticated users of cost feedback and how to understand the strategic distortions that are induced by flaws in cost system design; (c) the strategic role of value-driver information and the relationship between process improvement and cost reduction; (d) the use of budgetary control systems and financial measures in performance evaluation and management and (e) incentive conflicts in organizations and their mitigation through appropriate mechanisms.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2401 - FINANCIAL ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
The major objective of this course is to help students understand the basic structure and substance of a firm’s reports from a user’s point of view. This includes what is (and what is not) included in the reports, how and when events affect the statements, and what can be inferred from these reports about the firm’s past activities, present position and the future prospects.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2402 - FINANCIAL ACCOUNTING IN HEALTHCARE ORGANIZATIONS
Minimum Credits: 3
Maximum Credits: 3
The major objective of this course is to help students understand the basic structure and substance of a firm’s reports from a user’s point of view.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2466 - RISK MANAGEMENT AND COMPLIANCE ISSUES FACING INTERNATIONAL ORGANIZATIONS
Minimum Credits: 2
Maximum Credits: 2
This course will be valuable to MBA and mac students interested in working for global businesses, regardless of their desired career paths. As business organizations continue to seek growth in markets outside the United States and Western Europe, they will face increasingly complex and difficult challenges, including compliance with U.S. And foreign criminal and civil laws in places that are corrupt. Compliance with the U.S. Foreign corrupt practices act, which forbids businesses from providing certain benefits to government officials, is essential for global organizations, as penalties are severe. And to succeed in their careers, auditors will need to understand that businesses in certain geographic areas maintain multiple sets of books and hide bribery and tax fraud schemes. Strategic planners and supply-chain professionals will face cross-border risks, including demands by government customs and tax inspectors for bribe payments. Energy executives will confront violence, corruption and supply-chain problems in many oil and gas-producing areas. Sales professionals will confront demands for kickbacks. The course will cover these issues, and will provide students with the knowledge and compliance tools necessary to advance their professional careers in a global economy.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2510 - INTERMEDIATE FINANCIAL REPORTING AND ANALYSIS 1
Minimum Credits: 2
Maximum Credits: 2
This financial accounting elective is designed for accounting and finance majors who plan to be financial analysts or heavy users of financial reports. Topics covered include accounting procedures for recording and presenting financial information, asset valuations, revenue recognition and financial statement footnote disclosures.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BACC 2401; PROG: Joseph M. Katz Grad Sch Bus
|
| |
-
BACC 2523 - ACCOUNTING DATA ANALYTICS
Minimum Credits: 3
Maximum Credits: 3
Accounting data analytics exposes macc students to the role of big data in accounting and the information technology tools and techniques used by accountants and auditors to produce more timely and accurate reports. Topics include advanced excel, data modeling, statistical sampling and cluster analysis, business intelligence, and xbrl generation and analysis.The course will cover data analytics covering four major themes: financial reporting, performance evaluation, audit analytics, and tax. Each theme will include hands-on instruction using commercial and open source software and requires students to complete a related data analysis project. Accounting data analytics is different from other database and information systems courses in that it will show students how to use specific tools to complete projects and develop an analytical mindset with a specific focus on accounting and auditing processes. This is primarily a project-based course. The students will complete three projects, showing their mastery of the tools, decisions, and the steps they followed to reach their conclusions. The final exam would be used to evaluate general understanding of the concepts discussed throughout the semester. There is potential for additional ebl components including field trips if we can work out logistics. I’m currently developing relationships with the accounting firms to bring in local experts and to work on real-world cases.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2524 - INTERNAL AUDIT: RISK & ADVISORY
Minimum Credits: 2
Maximum Credits: 2
Students are introduced to generally accepted auditing standards (GAAS). Internal control is studied in detail with emphasis on how to test for its effectiveness. Audit objectives, planning and sampling techniques are developed as a basis for the audit opinion.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2525 - FINANCIAL STATEMENT ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
Financial statement analysis focuses on the evaluation of publicly traded company financial statements and related note disclosures as well as the correlation of this historic financial performance to the company’s stock prices. This course will assist students’ development of a systematic approach to analyzing reported financial data and understanding the underlying risks and possible inconsistencies among comparative companies. Requirements of the course include interim exams and written and oral presentations of analysis.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PLAN: Accounting (MS)
|
| |
-
BACC 2528 - MANAGERIAL ACCOUNTING
Minimum Credits: 2
Maximum Credits: 2
Students learn how the costs of products and services are determined in cost accounting systems and how this data is used in managerial decisions and in planning and control of business operations.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BACC 2401; PROG: Katz Graduate School of Business
|
| |
-
BACC 2533 - ACCELERATED INTERMEDIATE FINANCIAL REPORTING
Minimum Credits: 3
Maximum Credits: 3
Accelerated intermediate financial reporting fulfills the prerequisites of intermediate financial reporting 1 and intermediate financial reporting 2 for students who are entering the MACC program. This course studies the preparation, communication, interpretation and analysis of financial data with emphasis on the information needs of users of financial information prepared under us GAAP. General topics covered in this course include revenue recognition, inventory accounting, long term assets and impairment, investments, current liabilities and contingencies, long term liabilities, capital and retained earnings, leases, pensions and postretirement benefits, income taxes, and preparation of the statement of cash flows. Students are expected to have an accounting background. This course is designed to sit on top of an existing foundation in accounting and will assume students already have taken several financial accounting courses or knowledge obtained through work experience. It is expected that students are fluent with accrual accounting and the accounting cycle and that they have already studied some of the topics in the course in depth. The course will move quickly.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2534 - CONTROLLERSHIP
Minimum Credits: 2
Maximum Credits: 2
This accounting elective is designed for MAcc students seeking a role in corporate accounting and controls. The course will cover the changing role of the controller and the major functions managed by the controller of a typical company. Topics covered include: role of the controller, general accounting, cash management, accounts receivable, accounts payable, payroll, financial planning and budgeting, management reporting and designing well-controlled financial processes and systems.
The content will focus not only on the processes managed by the controller, but also the optimization of these processes, policies and procedures and leadership issues. The use of experts from the accounting community will be used as a complement to the theoretical materials presented to illustrate the practical applications and challenges of controllership.
Because the course is practical in nature, an experience-based learning group project will be a large part of the curriculum and learning experience offered to students.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2537 - TAXES AND MANAGEMENT DECISIONS
Minimum Credits: 2
Maximum Credits: 2
Designed as an introduction to business taxation for majors in areas such as finance or financial planning. Focuses on how managers and analysts can recognize tax problems, consequences and opportunities associated with common business events.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BACC 2401; PROG: Katz Graduate School of Business
|
| |
-
BACC 2540 - INTERNATIONAL TAXATION
Minimum Credits: 3
Maximum Credits: 3
This course is an introduction to the U.S. law of international taxation. It is designed to provide those entering the global marketplace with a basic understanding of how international transactions are taxed. The course will focus on: (1) fundamentals of international taxation, (2) U.S. activities of foreign taxpayers, and (3) foreign activities of U.S. taxpayers.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BACC 2559; PROG: Katz Graduate School of Business
|
| |
-
BACC 2541 - SEC REPORTING AND DISCLOSURE
Minimum Credits: 3
Maximum Credits: 3
This accounting elective is designed for MACC students as a capstone course in financial accounting. The course covers the rules for financial disclosures under the u. S. Securities and exchange commission and is meant to expose students to the financial reporting processes followed by public companies. The fundamentals of the following processes will be covered: earnings releases; quarterly reporting; annual reporting; proxy statements; comment letters and company responses; benefit plan reporting; working with the division of corporation finance and working the division of enforcement. Hot topics in sec reporting and advanced disclosure topics, such as special areas of revenue recognition, management’s discussion and analysis, asset retirement obligations, leasing, corporate restructurings, business acquisitions/spin offs, forward looking statements and disclosures about market risk will be covered.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BACC 2254 and BUSACC 1238; PROG: Katz Graduate School of Business
|
| |
-
BACC 2542 - ACCOUNTING AND FINANCE LAW
Minimum Credits: 3
Maximum Credits: 3
This course is designed to provide macc and mba candidates with advanced legal information that is necessary for effectuating management level responsibilities in the contemporary business environment. This course will enhance a business student’s knowledge of the law (past that of the three credit business law elective course that is offered) in a manner that strategically is consistent with the content of the CPA exam.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BSEO 2315 or 2528; PROG: Joseph M. Katz Grad Sch Bus
|
| |
-
BACC 2543 - TAX POLICY 1
Minimum Credits: 2
Maximum Credits: 2
Our nation was born from a revolution over taxation without representation. Nearly 250 years later, the debate over tax policy continues to dominate political debates and presidential campaigns. Why the tax system attracts all this attention is no mystery. It is the aspect of government that directly affects more people than any other. This course will explore the history of tax policy in the united states, the tax legislative process in congress, how our tax policies influence people’s decisions and behavior, international tax considerations, and ideas for future tax reform. Students will discuss what factors are important in designing a good tax system and survey the social justices and injustices that arise from how the government raises its revenue. Upon completion of this course, students should be able to think critically about our tax system and form opinions grounded in facts and policy. This course is for any student that wants to become a more educated citizen (and voter!) With respect to our nation’s ongoing debate over tax reform.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BACC 2559; PROG: Joseph M. Katz Grad Sch Bus
|
| |
-
BACC 2544 - TAX POLICY 2
Minimum Credits: 2
Maximum Credits: 2
This course will build upon tax policy I by taking a more in-depth look at our federal tax system. Students will also be introduced to international tax policies and provisions. Students will continue to discuss what factors are important in designing a good tax system and survey the social justices and injustices that arise from how the government raises its revenue. Upon completion of this course, students should be able to think critically about our tax system and form opinions grounded in facts and policy.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2549 - STRATEGIC COST ANALYSIS
Minimum Credits: 2
Maximum Credits: 2
This course deals with strategic implications of alternative methods of product cost measurement. The discussions will primarily be case-based and will cover cost measurement issues in both conventional and modern manufacturing environments.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BACC 2401 and 2528; PROG: Katz Graduate School of Business
|
| |
-
BACC 2557 - ACCOUNTING RESEARCH AND WRITING
Minimum Credits: 2
Maximum Credits: 2
This course focuses on improving students’ writing, deductive reasoning, and problem-solving skills as they conduct research to make a recommendation on the accounting treatment for transactions for which no direct or clear guidance currently exists. Weekly writing assignments are evaluated on both content and the quality of the writing.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: BACC 2401; PROG: Joseph M. Katz Grad Sch Bus
|
| |
-
BACC 2558 - NON-PROFIT AND GOVERNMENTAL ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
This course focuses on financial reporting and disclosure for not-for-profit and governmental entities based on the standards and principles promulgated by the financial accounting standards board (FASB) and the governmental accounting standards board (GSAB). Students will learn how such entities prepare their financial reports and how to interpret and use such information. The course covers financial reporting for not-for-profit entities, balancing the focus on internal operations with fiduciary responsibility. In addition, the course examines the objectives of financial reporting for governmental units and the preparation and use of the financial statements for such entities. A sample of specific entities will be reviewed to illustrate the preparation and use of their financial statements. In addition, accounting software for governmental transactions will be introduced.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2559 - INDIVIDUAL TAX ACCOUNTING AND PLANNING
Minimum Credits: 3
Maximum Credits: 3
This course focuses on individual tax return preparation and planning. Students will learn how to calculate the taxes associated with a variety of personal, investment, property, and sole-proprietorship transactions. Concepts will be reinforced through the preparation of actual tax returns that reflect different combinations of such transactions. Students will develop tax planning skills by considering how various transactions can be restructured to minimize the current or future tax liability.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2801 - FINANCIAL ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
The major objective of this course is to help students understand the basic structure and substance of a firm’s reports from a user’s point of view. This includes what is (and what is not) included in the reports, how and when events affect the statements and what can be inferred from these reports about the firm’s past activities, present position and the future prospects.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 2802 - FINANCIAL ACCOUNTING IN HEALTHCARE ORGANIZATIONS
Minimum Credits: 3
Maximum Credits: 3
The major objective of this course is to help students understand the basic structure and substance of a firm’s reports from a user’s point of view.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 2901 - ACCOUNTING AND CONTROL FOR HEALTH CARE ORGANIZATIONS
Minimum Credits: 3
Maximum Credits: 3
In this course you will develop an understanding of the various roles that accounting information plays in healthcare organizations. We will begin by analyzing the needs of managers, healthcare professionals, healthcare consumers and other parties for financial information concerning a healthcare organization’s financial position, current financial performance and cash generating ability. You will learn how standard financial statements (balance sheet, income statement, and statement of cash flows) address these needs, and the strengths and weaknesses of the statements in supplying this information. Financial statement analysis concepts and techniques will be introduced as cost-effective tools that enable healthcare decision makers to draw appropriate inferences from published financial statements. We will also study key issues that arise in accounting for a healthcare organization’s operations, investing and financing decisions. The final part of the course will analyze specific uses of accounting information in support of organizational decisions. We will study how accounting systems measure the cost and profitability of healthcare services, the effect of volume on profitability, and the proper use of accounting cost information in supporting decisions such as whether to invest in new equipment and whether or not to expand existing services.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 3001 - INTRODUCTION TO ACCOUNTING RESEARCH
Minimum Credits: 3
Maximum Credits: 3
This seminar is designed to provide new accounting doctoral students with an overview of accounting research. The course will discuss the variety of topics and methods addressed by accounting scholars, and will seek to provide insight into the characteristics that distinguish the highest quality research. Analytical research methods and topics, as well as applications in managerial accounting, will receive particular emphasis in the first half of the course. In the second half, we will read and analyze representative accounting research employing capital markets, archival managerial and experimental methods.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 3005 - ACCOUNTING THEORY
Minimum Credits: 2
Maximum Credits: 2
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SU3 Basis
|
| |
-
BACC 3010 - INDEPENDENT STUDY IN ACCOUNTING
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Independent Study
Grade Component: Grad HSU Basis
|
| |
-
BACC 3014 - EXPERIMENTAL RESEARCH IN ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
The course covers recent experimental studies that apply behavioral decision theory, psychology, and economics to address a variety of accounting research questions. The course focuses most heavily on recent work. The goals of this course are to (1)familiarize students with recent experimental research in accounting, (2) help students develop the skills necessary to critically evaluate such research, and (3) generate ideas for future experimental research topics.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 3017 - ACCOUNTING WORKSHOP
Minimum Credits: 3
Maximum Credits: 3
Presentation of research papers in various aspects of accounting and related areas by faculty and distinguished visitors. The student is expected to attend the workshop, participate in discussions, and present a workshop paper.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 3021 - ARCHIVAL RESEARCH IN MANAGERIAL ACCOUNTING
Minimum Credits: 2
Maximum Credits: 2
This seminar will focus on studying management control and performance measurement issues largely from an economics perspective using archival methods. Topics discussed will include, but not be limited to, analysis and economic impact of cost systems, use of financial measures for performance evaluation and compensation, impact of incentive systems on organizational performance, non-financial measures and balanced scorecard. The course materials will consist of papers in accounting. Course requirements include active class participation, presentations/discussions/summary reports of papers, replication of earlier studies (where data are available), and a final examination.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SU3 Basis
|
| |
-
BACC 3024 - ECONOMIC MODELS OF INCENTIVES AND CONTROLS
Minimum Credits: 2
Maximum Credits: 2
This seminar provides students with an introduction to incentive problems in firms and markets and how contractual arrangements serve to mitigate these problems. Students are introduced to the classic papers in agency research and current working papers spanning economics, accounting and corporate finance.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SU3 Basis
|
| |
-
BACC 3025 - CAPITAL MARKETS RESEARCH IN ACCOUNTING
Minimum Credits: 3
Maximum Credits: 3
This course provides students with a solid understanding of capital market research in accounting and empirical research training. The class will cover topics such as the relation between stock prices and earnings, stock market anomalies, and analyst and management forecasts. Students will also replicate some classic finance and accounting papers in order to provide them with some hands-on experience working with compustat, crsp, ibes, and sdc data using sas statistical programming. The class will help students to better evaluate research in workshops, develop new ideas and do empirical tests.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BACC 3028 - ARCHIVAL RESEARCH IN AUDITING
Minimum Credits: 2
Maximum Credits: 2
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 3050 - CRITICAL THINKING IN ACCOUNTING
Minimum Credits: 2
Maximum Credits: 2
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 3052 - CRITICAL THINKING IN ACCOUNTING II
Minimum Credits: 2
Maximum Credits: 2
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 3053 - CRITICAL THINKING IN ACCOUNTING 3
Minimum Credits: 1.5
Maximum Credits: 1.5
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BACC 3099 - READINGS IN ACCOUNTING
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Directed Studies
Grade Component: Grad Letter Grade
|
Business Administration |
| |
-
BUSADM 3001 - BEHAVIORAL RESEARCH METHODS
Minimum Credits: 3
Maximum Credits: 3
The primary objective of this course is to familiarize you with and develop an appreciation for business research methodology. Research skills will be an important determinant of your success as an academic. The course will introduce you to a variety of research approaches, allow you to develop an understanding to effectively use these approaches in your own research, and prepare you to evaluate research done by others. The course will also provide you with an introduction to causal modeling techniques (lisrel, pls). By the end of the course you should develop a sound appreciation of the research process and a range of research approaches that can be applied to management problems. In addition, you should have an appreciation for what constitutes “good” research so that you can constructively critique and make use of research done by others.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BUSADM 3006 - MULTIVARIATE ANALYSIS
Minimum Credits: 3
Maximum Credits: 3
Examines the theory of and applications for multivariate statistical methods of analysis including, but not limited to, multiple regression, multiple discriminant analysis, and factor analysis. Emphasis on the use and limitations of these tools and upon the meaning and interpretation of results. Students are expected to gain first-hand experience with several techniques by applying canned computer programs to appropriate data sets and by discussing appropriateness of applications in published literature.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad Letter Grade
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BUSADM 3013 - WORK AND ORGANIZATIONS
Minimum Credits: 3
Maximum Credits: 3
This seminar is intended for Ph.D. students who wish to develop an understanding of the theoretical underpinnings of research on the management of knowledge and work in organizations. It reviews the major theoretical perspectives, but places a particular emphasis on the current empirical literature related to human resource management. Because of the multi-disciplinary nature of this research space, readings draw on a broad range of material including studies from sociology, organization theory, strategy, economics, and policy. These are used to develop an integrative understanding of the underpinnings of work and employment-related research published in top tier management journals.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BUSADM 3021 - BEHAVIORAL SCIENCE RESEARCH PRACTICUM
Minimum Credits: 3
Maximum Credits: 3
The primary objective of this course is to provide a hands-on experience in the development, design and execution of rigorous behavioral science research. Students will be asked to design and execute a theory-based research project. We will explore a variety of different methodological approaches and discuss the fit between students’ specific research questions and different techniques. Our goal is two-fold: (1) to help students develop a sophisticated understanding for what constitutes rigorous research within the field; and (2) to coach students through the research process in order to create a high-quality empirical paper for publication.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BUSADM 3030 - MANAGING THE TRIPLE BOTTOM LINE
Minimum Credits: 3
Maximum Credits: 3
Issues such as climate change and global warming, human rights, and health and sanitation for all have garnered significant attention in recent years. Leading businesses realize that it is no longer enough to maximize profits and cater to shareholders but as well critical to integrate the wellbeing of the planet and its people into their business models. Such a transformation to managing the triple bottom line of people, planet and profit requires us to look at business and its operations through a new lens. This doctoral seminar will focus on theories, concepts and methodologies that we can use to understand the role of the firm in 21st century society and develop strategies for long run sustainability. The course will be interdisciplinary, drawing on literatures in strategy, marketing, organizational behavior, operations, and finance as well as methods spanning lab experiments to structural equation models to understand the conditions under which creating social and environmental value can drive business value. The course will feature academic guest speakers from the aforementioned disciplines of business to highlight the interdisciplinary nature of sustainability research.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SU3 Basis
|
| |
-
BUSADM 3050 - METHODS FOR BEHAVIORAL BUSINESS RESEARCH
Minimum Credits: 2
Maximum Credits: 2
Experienced behavioral business researchers usually fall into a pattern that emphasizes a subset of diverse methods and approaches. But both new and experienced researchers must depend on a vast literature that makes use of a diverse set of methods, many of which are outside of their expertise. Therefore, drawing from a limited set of approaches would disadvantage any researcher who desires to understand, the literature of his or her chosen field. Another by-product of following only a limited set of approaches is a likely narrowed understanding of trade-offs necessary in any choice of research method. Because no single method can answer all questions, it is important to make good decisions about those trade-offs. This course provides a “hands on” survey of research methods, covering phases from developing research ideas, theorizing, collecting data, identifying what to measure, and determining how it should be measured. A rolling writing assignment throughout the course will provide opportunities for feedback at each step of the way. As a result of this course, you should be a better consumer, critic, and provider of research results in your field.
Academic Career: Graduate
Course Component: Seminar
Grade Component: Grad LG/SNC Basis
|
| |
-
BUSADM 3199 - RESEARCH AND DISSERTATION PHD
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Thesis Research
Grade Component: Grad SN Basis
|
Business Economics |
| |
-
BECN 2019 - ECONOMICS FOR INTERNATIONAL BUSINESS
Minimum Credits: 3
Maximum Credits: 3
Investigates key aspects of the international economics environment. The first half introduces the international monetary system. Reviews the balance of payments, foreign exchange rate systems, adjustment mechanism, the foreign exchange market, and international money and capital markets. In the second half, topics include theories of international trade and investment restrictions on trade, commercial policies of the United States.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BECN 2401; PROG: Katz Graduate School of Business
Course Attributes: Russian & East European Studies
|
| |
-
BECN 2060 - INDEPENT STUDY IN MANAGERIAL ECONOMICS
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Independent Study
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BECN 2401 - ECONOMIC ANALYSIS FOR MANAGERIAL DECISION: FIRMS AND MARKETS
Minimum Credits: 3
Maximum Credits: 3
This course develops an understanding of how market-based economic systems reconciles the separate needs of consumers and producers, and provides an economic framework for managerial decisions. Topics include: pricing, output, and quality decisions; the impact of productivity improvements on costs; quality-cost tradeoffs; transactions costs as a determinant of the boundaries of the firm; market imperfection and the role of regulation.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BECN 2509 - GLOBAL MACROECONOMICS: INSTITUTIONS AND POLICY
Minimum Credits: 1.5
Maximum Credits: 1.5
This elective course focuses on the forces which drive or determine overall national/global economic activity. The course is organized around the progressive development of an “open economy” macroeconomic model which is capable of handling a number of key policy and other variables.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: Katz Grad School of Business students only.
|
| |
-
BECN 2510 - MACROECONOMICS AND GROWTH IN EMERGING ECONOMIES
Minimum Credits: 1.5
Maximum Credits: 1.5
This follow-up course continues the focus on the forces which drive or determine overall national/global economic activity. This course expands the “open economy” macroeconomics framework developed in BECN 2509.”
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: CREQ: BECN 2509; PROG: Katz Graduate School of Business
Course Attributes: Global Studies
|
| |
-
BECN 3010 - INDEPENDENT STUDY IN ECONOMICS
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Independent Study
Grade Component: Grad HSU Basis
|
| |
-
BECN 3099 - READINGS IN MANAGERIAL ECONOMICS
Minimum Credits: 1
Maximum Credits: 9
Academic Career: Graduate
Course Component: Directed Studies
Grade Component: Grad Letter Grade
|
Business Finance |
| |
-
BFIN 2015 - SHORT-TERM FINANCING
Minimum Credits: 2
Maximum Credits: 2
Focuses on short-term financial management. Major topics include cash management, investment in money market instruments, banking regulations, liquidity policy, financial statement forecasting and simulation credit policy and credit management, and working capital management.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BFIN 2006 or BFIN 2410; PROG: Katz Graduate School of Business
|
| |
Page: 1
| 2
| 3
| 4
| 5
| 6
| 7
| 8
| 9
| 10
| 11
… Forward 10 -> 69 |
