Department of Statistics

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The field of statistics is concerned with ways of understanding variability in measurements. It is the science and art of making informed decisions in the face of uncertainty. Statistical reasoning is fundamental to research in many scientific fields. For example, probabilistic models of learning are used in education and psychology, and time series and regression models guide research in engineering, chemistry, economics, biology, and medicine. Recent high-profile court cases have shown the importance of the use of probability and statistics in law, especially in the fields of forensic medicine and DNA fingerprinting. Statisticians have also been instrumental in developing methods by which observations are obtained in many disciplines. Examples include randomized clinical trials in medicine and complex sampling surveys in social and political science. Probability and statistics are basic to the actuarial sciences. When lists are compiled of the most important scientific theories and discoveries of the last century, a substantial number of these developments are seen to be inherently statistical in nature.

The Department of Statistics offers course work leading to a Bachelor of Science degree in statistics, a minor in applied statistics, and a combined five-year bachelor and master’s degree in statistics. The department also offers a wide array of introductory service courses for general undergraduate audiences that deal with statistical methods in applications (and which require only high school mathematics). A joint major in economics and statistics is also available. Interested students should consult the requirements listed under Economics . Students considering majoring in statistics should consult with a department advisor early in their studies, preferably during their freshman year. For more information on the major, other programs, and the Department of Statistics, visit www.stat.pitt.edu.

Programs

• Statistics, BS/MA

• Data Science, BS
• Statistics, BS

• Applied Statistics Minor

Courses

• BIOST 2011 - PRINCIPLES OF STATISTICAL REASONING
• BIOST 2012 - BAYESIAN & EMPIRICAL BAYES STAT
• BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS 1

• STAT 0200 - BASIC APPLIED STATISTICS
• STAT 0800 - STATISTICS IN THE MODERN WORLD
• STAT 1000 - APPLIED STATISTICAL METHODS
• STAT 1050 - DATA JAM: USING BIG DATA FOR COMMUNITY GOOD
• STAT 1053 - DATA JAM LAB
• STAT 1060 - DATA SCIENCE FOUNDATIONS
• STAT 1100 - STATISTICS AND PROBABILITY FOR BUSINESS MANAGEMENT
• STAT 1151 - INTRODUCTION TO PROBABILITY
• STAT 1152 - INTRODUCTION TO MATHEMATICAL STATISTICS
• STAT 1201 - APPLIED NONPARAMETRIC STATISTICS
• STAT 1211 - APPLIED CATEGORICAL DATA ANLYSIS
• STAT 1221 - APPLIED REGRESSION
• STAT 1223 - APPLIED REGRESSION WRITING COMPONENT
• STAT 1241 - APPLIED SAMPLING
• STAT 1251 - STATISTICAL QUALITY CONTROL
• STAT 1251 - STATISTICAL QUALITY CONTROL
• STAT 1261 - PRINCIPLES OF DATA SCIENCE
• STAT 1281 - DATA SCIENCE WITH PYTHON
• STAT 1291 - TOPICS APPLIED STATISTICS 1
• STAT 1292 - TOPICS IN APPLIED STATISTICS 2
• STAT 1293 - TOPICS IN APPLIED STATISTICS 3
• STAT 1294 - TOPICS IN APPLIED STATISTICS 4
• STAT 1301 - STATISTICAL PACKAGES
• STAT 1311 - APPLIED MULTIVARIATE ANALYSIS
• STAT 1321 - APPLIED TIME SERIES
• STAT 1331 - FINANCIAL ECONOMETRICS
• STAT 1341 - SPORTS ANALYTICS
• STAT 1361 - STATISTICAL LEARNING AND DATA SCIENCE
• STAT 1631 - INTERMEDIATE PROBABILITY
• STAT 1632 - INTERMEDIATE MATHEMATICAL STATISTICAL
• STAT 1651 - INTRODUCTION TO BAYESIAN STATISTICS
• STAT 1661 - LINEAR REGRESSION
• STAT 1731 - STOCHASTIC PROCESSES
• STAT 1741 - APPLIED PROBABILITY THEORY
• STAT 1900 - INTERNSHIP
• STAT 1902 - DIRECTED STUDY
• STAT 1961 - STATISTICAL DATA SCIENCE IN ACTION
• STAT 2131 - APPLIED STATISTICAL METHODS 1
• STAT 2132 - APPLIED STATISTICAL METHODS 2
• STAT 2381 - SUPERVISED STATISTICAL CONSULTING
• STAT 2730 - STOCHASTIC PROCESSES

Return to: Kenneth P. Dietrich School of Arts and Sciences