Tufts University offers a number of courses on statistics and qualitative analysis. These courses are taught throughout all three campuses and hosted in a number of different schools and departments. Below is an overview of available courses:

The School of Arts & Sciences and The School of Engineering

Advanced Statistics EC – 0150 – Fall 2017
Advanced Statistics I – PSY – 0170 – Fall 2017/Spring 2018
Advanced Statistics II – PSY – 0108 – Spring 2018
Applied Data Analysis – CD – 0146 – Fall 2017
Applied Multivariate Analysis – CD – 0249 – Spring 2018
Biostatistics – Bio – 0132 – Fall 2017
Ecological Models and Data – Bio – 0133 – Spring 2018
Introduction to Statistics for Health Applications- CH – 0031 – Fall 2017
Introductory Statistics – Math – 0021 – Fall 2017/Spring 2018
Political Science Research Methods – PS – 0103 – Fall 2017/Spring 2018
Principles of Biostatistics – CEE – 194 – Fall 2017/Spring 2018
Quantitative Research Methods – Soc – 0101 – Fall 2017
Probs Research: Statistics – CD – 0140 – Spring 2018
Public Health – CEE – 0137 – Fall 2017
Quantitative Reasoning – UEP – 0254 – Fall 2017/Spring 2018
Quantitative Research Methods – Soc – 0101 – Fall 2017
Quantitative Research Methods – Intr – 0092 – Spring 2018
Statistics – EC – 0013 – Fall 2017/Spring 2018
Statistics – Math – 0162 – Spring 2018

The Sackler School of Medicine & The Friedman School of Nutrition Science and Policy

Biostatistics I – CTS – 0527/Nutr 0206 – Fall 2017
Biostats in Public Health – CMPH 0132 – Spring 2017
Introduction to SAS – Ph 0265 – Spring 2017
Intro to SAS Programming – Nutr 0237 – Spring 2017
Introduction to Bio Stats Regression Methods – Nutr 0323 – Fall 2017
Nutritional Epidemiology – Nutr 0305 – Fall 2017
Principles of Biostatistics – PH 0205/BMS 0201 – Spring 2017
Probability and Statistics Basics – Nutr 0307 – Spring 2017
Regression Analysis for Nutrition Policy – Nutr 0307 – Fall 2016 / Spring 2017
Statistical Methods for Nutritional Science & Policy – Nutr 0207 – Fall 2016 / Spring 2017
Statistical Methods II – Nutr 0309 – Spring 2017

The Fletcher School of Law and Diplomacy

Analytic Frameworks – DHP P203 – Spring 2017
Econometrics – EIB E213 – Fall 2016 / Spring 2017
Data Analysis & Statistical Methods – EIB B205 – Spring 2017
Applied Microeconometrics – EIB E218 – Spring 2017
Econometric Impact Evaluation for Development – EIB 247 – Fall 2017
Data Analysis and Statistical Methods for Business – EIB B206 – Spring 2017
International Economic Policy Analysis – EIB E214 – Fall 2017

The Cummings School of Veterinary Medicine

Statistics I – APP 516 – Fall 2017
Statistics II: Intermediate – APP 517 – Spring 2017


The School of Arts & Sciences and The School of Engineering

Advanced Statistics – EC-0150
Offered Fall 2017
Instructor: David Garman

Statistical inference, including elements of probability theory, hypothesis testing, and multivariate analysis. Fall.

Advanced Statistics I – PSY – 0107
Offered Fall 2017 / Spring 2018
Instructor: Richard Chechile

Development of statistical concepts for the design and analysis of research. Consideration of the logic of statistical inference, analysis of variance, and nonparametric analysis. Recommendations: PSY 31 or CD 193 or graduate standing.

Advanced Statistics II – PSY – 0108
Offered Spring 2018
Instructor: Richard Chechile

Consideration of certain multivariate designs, regression, and the analysis of covariance. Recommendations: PSY 107.

Applied Data Analysis – CD – 0146
Offered: Fall 2017
Instructor: Kristina Lauren, Schmid Callina

An examination of statistical methods for designing, analyzing, and interpreting biological experiments and observations. Topics include probability, parameter estimation, inference, correlation, regression, analysis of variance, and nonparametric methods. (Group Q.) Recommended: BIO 13 and 14, or equivalent, plus one additional biology course above BIO 14.

Applied Multivariate Analysis – CD – 0249
Offered Spring 2018
Instructor: Sara Johnson

Introduction to multivariate statistics, with a special emphasis on methods for studying change and the effects of context. Topics: general linear hypothesis testing, logistic regression, multilevel models, cluster analysis, principal components analysis, and exploratory factor analysis. Focus on using computer spreadsheet Excel and a statistical package such as SPSS or SAS to analyze real data with statistical techniques introduced through lectures, interpreting results, and writing about the findings. A good background in multiple regression analysis, including use and interpretation of dummy variables and interactions, is required. Recommendations: Two semesters of statistics and data analysis methods.

Biostatistics – Bio – 0132
Offered Fall 2017
Instructor: Sara Lewis

An examination of statistical methods for designing, analyzing, and interpreting biological experiments and observations. Topics include probability, parameter estimation, inference, correlation, regression, analysis of variance, and nonparametric methods. (Group Q.) Recommended: BIO 13 and 14, or equivalent, plus one additional biology course above BIO 14.

Ecological Models and Data – Bio – 0133
Offered Spring 2018
Instructor: Elizabeth Crone

Probability and likelihood, fitting simple statistical models to data, and using these models to make predictions. Examples come from problems in ecology, with emphasis on monitoring plant and animal populations and forecasting how these populations will respond to changing environments. Includes use of discrete probability distributions (binomial and Poisson), building mixed and compounded probability distributions, an introduction to Bayesian statistics, and use of the open-source statistics program, R. Students should have a good working knowledge of high school algebra and an interest in ecology.

Introduction to Statistics for Health Applications- CH – 0031
Offered Fall 2017
Instructor: Karen Kosinski

Statistics as it relates to community health, public health, and research in the health fields. Introductory level course, does not require calculus and emphasizes applications of statistics in the health field rather than mathematical derivations of statistical equations. Student will learn to use the computer program SPSS.

Introductory Statistics – Math – 0021
Offered Fall 2017 / Spring 2018
Instructor: Linda Garant

Descriptive data analysis, sampling and experimentation, basic probability rules, binomial and normal distributions, estimation, regression analysis, one and two sample hypothesis tests for means and proportions. The course may also include contingency table analysis, and nonparametric estimation. Applications from a wide range of disciplines. Recommendations: High school algebra and geometry.

Political Science Research Methods – PS – 0103
Offered Fall 2017 / Spring 2018
Instructor: Natalie Masuoka

The study of quantitative methods for investigating political issues and policy controversies. Focuses on collecting, analyzing, and presenting data. Emphasizes hands-on training that provides useful skills for academic and professional settings. Topics covered include: measurement, hypothesis development, survey design, experiments, content analysis, significance tests, correlation, and regression. No prior statistics background necessary. Prerequisites: PS 11, 21, 41, 42, or 61. A methodologically focused course.

Principles of Biostatistics – CEE – 194
Offered Fall 2017 / Spring 2018
Instructor: Mark Woodin

Guided independent study of an approved topic at the graduate level. Credit as arranged. Recommendations: Consent of instructor.

Probability and Statistics – ES – 0056
Offered Fall 2017 / Spring 2018
Instructor: Wayne Chudyk

Application of the concepts of probability and statistics to problem solving in engineering systems. Topics include data reduction techniques, probability, probability distribution functions, error propagation, sampling distributions, estimation, hypothesis testing, simple comparative experiments, and linear regression. Examples are drawn from a variety of disciplines, including the environment, materials, manufacturing, computing, and process design. Recommendations: MATH 42 (formerly MATH 13)

Probs Research: Statistics – CD – 0140
Offered Spring 2018
Instructor: Andrea Vest Ettekal

Elementary statistics procedures up through and including analysis of variance. Instruction and practice in use of prepackaged computer programs useful in social science research. Recommendations: Senior or graduate status and background in fundamental mathematics or elementary statistics.

Public Health – CEE – 0137
Offered Fall 2017
Instructor: Dr. David Gute

An introduction to the public health approach is provided. The epidemiological model of the disease process is used to study a variety of infectious and noninfectious diseases. The wide variety of nonmedical approaches to disease control is emphasized. The public health aspects of vital statistics, evaluation, and administrative decision making are introduced and applied to current problems in public health. Recommendations: Consent of instructor.

Quantitative Reasoning – UEP – 0254
Offered Fall 2017/ Spring 2018
Instructor: Shomon Shamsudin

Required core course for M.A. and M.P.P. students. Introduction to the use of quantitative thinking. Designed to develop basic statistical skills as indispensable tools for policy research, planning and decision making. Students learn how to choose and apply statistical tools to data sources, when and how statistical tools can be used to analyze data, and how to interpret and understand others’ quantitative research. Statistical software is used to facilitate learning through active application of statistical tools. Although prior coursework in statistics is not required, students are required to have a solid understanding of college-level algebra. Waiver permitted for students with an undergraduate major or substantial work-related experience in statistics subject to faculty approval. Recommendations: College-level algebra

Quantitative Research Methods – Soc – 0101
Offered Fall 2017
Instructor: Jill Weinberg

Data analysis and statistics for the social sciences. Sampling, describing data, and logic of inference, especially with surveys. Introduction to microcomputer tools for analysis and graphic display. Answering research questions through individual or group projects. Recommendations: One introductory social science course.

Quantitative Research Methods – Intr – 0092
Offered Spring 2018
Instructor: Drusilla Brown

An interdisciplinary exploration of quantitative research methods commonly used in International Relations. Students learn quantitative methods in International Relations, pose significant questions, obtain and evaluate complex data and organize and articulate their findings. Topics may include, but are not limited to, IRB certification, Excel for data analysis, GIS, statistical analysis, case study methodology, and program evaluation. Full credit. Spring term.

Statistics – EC – 0013
Offered Fall 2017 / Spring 2018
Instructor: Thoma Downes

An introduction to basic statistical techniques that are used in economic analysis. Major topics include probability, discrete random variables, continuous random variables, sampling distributions, estimation, and hypothesis testing. The course will conclude with some theory and applications of the linear regression model. Required of all economics majors.

Statistics – Math – 0162
Offered Spring 2018
Instructor:Patricia Garmirian

Statistical estimation, sampling distributions of estimators, hypothesis testing, regression, analysis of variance, and nonparametric methods. Recommendations: MATH 161 or permission of instructor.


The Sackler School of Medicine & The Friedman School of Nutrition Science and Policy

Biostatistics I – CTS – 0527/Nutr 0206
Offered Fall 2017
Instructor: Farzad Noubary, Angie Rodday

This course introduces basic principles and applications of statistics to problems in clinical research. Topics covered include descriptive statistics, probability and random variation, sampling, hypothesis testing, proportions, measures of frequency, t-tests, chi-square tests, one-way analysis of variance, correlation, linear regression and nonparametric statistics.

Biostats in Public Health – CMPH 0132
Spring 2018
Instructor: Alice Tang

Biostatistical procedures used in the majority of biomedical investigations. Emphasizes the use of each procedure, how and when to apply it, and how to interpret the results. Each lecture is followed by a computer laboratory session that requires students to use appropriate methods when analyzing a specific data set. Students progress from a reading knowledge of biostatistics to the beginnings of conversant facility.

Introduction to SAS – Ph 0265
Offered Spring 2018
Instructor: David Tybor

This intensive course will introduce students to the concepts and syntax necessary for basic data management and analysis using the SAS System for Windows. Emphasis will be placed upon learning methods for data manipulation and gaining the necessary skills to prepare data for statistical analysis. SAS procedures for descriptive statistics will be covered, and methods for data visualization will be introduced. Weekly homework assignments and in-class exercises will allow students to gain practical experience solving SAS programming problems.

Intro to SAS Programming – Nutr 0237
Offered Spring 2018
Instructor: Richard Chechile

This first half-semester course will provide students with sufficient knowledge of how to obtain, manage, clean and prepare data in SAS for Windows. Emphasis will be placed on the basics of SAS programming and data manipulation. Upon completion, students should be able to use data in SAS and be familiar with the procedure steps required to import and export data, create SAS data sets, produce descriptive statistics, and clean and transform data in preparation for statistical analyses. In-class exercises and weekly homework assignments will allow students to acquire hands-on experience solving common SAS programming tasks. Important to Note: This course is designed for students with no SAS programming experience. Students with a basic knowledge of SAS should not take this course. If you are an NEPI student, it is strongly encouraged that you register for this course and acquire SAS Programming skills as you work toward completing your degree. Prerequisite: Graduate standing or instructor consent.

Introduction to Bio Stats Regression Methods – Nutr 0323
Offered: Fall 2017
Instructor: Kenneth Kwan Ho Chui

This course provides a survey of regression techniques for outcomes common in biomedical and public health data including continuous, count, binary, and time series data. Emphasis is on developing a conceptual understanding of the application of these techniques to solving problems, rather than to the numerical details. The objectives of this course are to (1) recognize when data can be described and analyzed by a regression model;(2) develop and interpret regression models; (3) plan and conduct an appropriate analysis; (4) summarize the results of the analysis in terms of the research question in both verbal and written formats suitable for targeted audiences. Prerequisites: PH 205 with a grade B or better, or NUTR 207 or NUTR 206 or NUTR 209 with a grade B- or better. Students who wish to use other statistics course as prerequisites please gather a syllabus of the said course and contact the course director for consent before the end of the add/drop period. This course is cross-listed with Public Health (PH 206).

Nutritional Epidemiology – Nutr 0305
Offered Fall 2017
Instructor: Fang Fang Zhang

This course is designed for graduate students at either the Master’s or Ph.D. level, who are interested in conducting or better interpreting epidemiologic studies relating diet and nutrition to health and disease. There is an increasing awareness that various aspects of diet and nutrition may be important contributing factors in chronic disease. There are many important problems, however, in the implementation and interpretation of nutritional epidemiologic studies. The purpose of this course is to examine epidemiologic methodology in relation to nutritional measures, and to review the current state of knowledge regarding diet and other nutritional indicators as etiologic factors in disease. This course is designed to enable students to better conduct nutritional epidemiologic research and/or to better interpret the scientific literature in which diet or other nutritional indicators are factors under study. Prerequisites: NUTR 0202: Principles of Nutrition Science and NUTR 0204/PH 0201: Principles of Epidemiology and NUTR 0206: Biostatistics I/PH 0205: Principles of Biostatistics. Prerequisites may not be taken concurrently with NUTR 0305.

Principles of Biostatistics – PH 0205/BMS 0201
Offered Spring 2018
Instructor: David Tybor

This course provides an introduction to the basic principles and applications of statistics as they are applied to problems in clinical and public health settings. Topics include the description and presentation of data, random variables and distributions, descriptive statistics, introduction to probability, estimation, elements of hypothesis testing, and one- and two-sample tests, ANOVA (including repeated-measures), non-parametric tests, and an introduction to linear and logistic regression. Lectures, problem sets, and computer output are used to develop these and additional concepts. Graduate standing.

Probability and Statistics Basics – Nutr 0307
Offered Spring 2018
Instructor: Daniel Cox

This course provides an introduction to the principles of probability and statistics and emphasizes the application of these disciplines to the analysis of basic science biomedical research data. Topics include: summarizing data, testing for differences between means, analysis of variance, laws of probability, common probability distributions, the analysis of categorical data, correlation, linear regression, nonlinear curve fitting, and exponential processes

Regression Analysis for Nutrition Policy – Nutr 0307
Offered Fall 2017 /Spring 2018
Instructor: Parke Wilde

Part two of a one-year, two-semester course sequence in statistics. This course is intended for students whose main focus is non-experimental or survey-based research. The course covers non-experimental research design, simple linear regression, multiple regression, analysis of variance, non-linear functional forms, heteroskedasticity, complex survey designs, and real-world statistical applications in nutrition science and policy. Students will make extensive use of Stata for Windows. NOTE: Students cannot receive credit for both NUTR 307 and its second semester counterpart NUTR 309. Pre-requisites: NUTR 207 or NUTR 206/209 and graduate standing or instructor consent.

Statistical Methods for Nutritional Science & Policy – Nutr 0207
Offered Fall 2017 /Spring 2018
Instructor: Farzad Noubary

Part one of a one-year, two-semester course covering descriptive statistics, graphical displays, confidence intervals, hypothesis testing, t test, chi-square test, nonparametric tests, multiple linear regression, multiple logistic regression, experimental design, multi-factor and multiple comparisons procedures. Students will learn how to use Stata statistical analysis software. This course was formerly listed as NUTR 209A-02. Prerequisite: Graduate standing or instructor consent.

Statistical Methods II – Nutr 0309
Offered Spring 2018
Instructor: Farzad Noubary

Part two of a one-year, two-semester course covering descriptive statistics, graphical displays, confidence intervals, hypothesis testing, t test, chi-square test, nonparametric tests, multiple linear regression, multiple logistic regression, experimental design, multi-factor and multiple comparisons procedures. Students will make extensive use of SPSS for Windows.NOTE: Students cannot receive credit for both NUTR 309 and NUTR 307. Pre-requisites: NUTR 206/209 and graduate standing or instructor consent.


The Fletcher School of Law and Diplomacy

Analytic Frameworks – DHP P203
Offered Spring 2018
Instructor: Carolyn Friedman

Introduction to the basic tools of policy analysis and decision making, providing students with analytic skills to make policy decisions in many types of organizations. The course includes an introduction to public policy objectives, decision making, and the role of analysis. Students then learn powerful analytic decision-making techniques, including decision trees, Bayes theorem, utility theory, prospect theory, game theory, benefit-cost analysis, and tipping models. Case studies are used to learn the policy analysis tools while applying them to real world policy problems. Cases come from developed and developing countries, and cover many different policy fields. No background in economics or statistics is required.

Econometrics – EIB E213
Offered Fall 2017 and Spring 2018
Instructor: Julie Schaffner

This course introduces students to the primary tools of quantitative data analysis employed in the study of economic and social relationships. It equips students for independent econometric research and for critical reading of empirical research papers. The course covers ordinary least squares, probit, fixed effects, two-stage least squares and weighted least squares regression methods, and the problems of omitted variables, measurement error, multicollinearity, heteroskedasticity, and autocorrelation. Prerequisites include familiarity with (1) basic probability and statistics (B205), and (2) basic concepts of functions and derivatives (E210m or an introductory calculus course).

Data Analysis & Statistical Methods – EIB B205
Offered Spring 2018
Instructor: Robert Nakosteen

This course provides an overview of classical statistical analysis and inference. The language and methods of statistics are used throughout the Fletcher curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing, as well as media reporting. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary.

Applied Microeconometrics – EIB E218
Offered Spring 2018
Instructor: Shinsuke Tanaka

This course is designed for students who are interested in learning advanced econometric techniques to answer a broad array of academic empirical research questions. To this end, this course covers a set of theoretical and practical econometric techniques for conducting high-quality empirical research. The curriculum is oriented toward applied practitioners by focusing on research design and methods for causal inference. The topics include several of the most commonly used estimation techniques (i.e., matching, fixed effects, difference-in-differences, instrumental variables, and regression discontinuity). Econometrics (at the level of E213) is a strict prerequisite and may not be taken concurrently

Econometric Impact Evaluation for Development – EIB 247
Offered Fall 2017
Instructor: Jenny C. Aker

The course will cover econometric impact evaluation theory and empirical methods for measuring the impact of development programs (including randomization, difference-in-differences, regression discontinuity, and propensity score matching). The curriculum will combine theory and practice. The primary objectives of the course are to provide participants with the skills to understand the value and practice of impact evaluation within development economics, design and implement impact evaluations and act as critical consumers of impact evaluations. Econometrics (at the level of E213) is a strict prerequisite and may not be taken concurrently.

Data Analysis and Statistical Methods for Business – EIB B206
Offered Spring 2018
Instructor: Robert Nakosteen

This course provides an overview of classical statistical analysis and inference. The goal is to provide you with an introduction to statistical thinking, concepts, methods, and vocabulary. This will give you some tools for dealing with statistical methods you may encounter in your coursework or research while at The Fletcher School, especially “regression analysis,” which is covered at the end of the course. In addition, this section of the course has a particular emphasis on business applications. Students who plan to or have completed B205 are not permitted to take this course.

International Economic Policy Analysis – EIB E214
Offered Fall 2017
Instructor: Michael W. Klein

This seminar teaches skills that enable students to bridge the gap between coursework in economics and the types of economic analysis used in both government and private sector settings. These skills and tools build on material taught in Econometrics. The topics addressed in the seminar include a range of timely and policy-relevant issues in international economics and macroeconomics. The seminar will also focus on the use of empirical analysis for writing concise, effective policy memorandums. Open to students who have completed E213, which may be taken concurrently.


The Cummings School of Veterinary Medicine

Statistics I – APP 516
Offered Fall 2017
Instructor: Allen Rutber

This course introduces students to the basics of statistical methods and research design. Students learn to state hypotheses, evaluate sampling procedures, create and manage data sets, and carry out basic statistical testing. Examples are drawn from research in veterinary medicine, animal science, human-animal relationships, and animal ecology.

Statistics II: Intermediate – APP 517
Offered Spring 2018
Instructor: Megan Mueller, Phyllis Mann

Intended for advanced research track students and tailored to their interests, this course will focus on experimental design and analysis of survey data, exploring the use of analysis of variance (ANOVA) and regression models, factor analysis, and other advanced techniques using SPSS or an equivalent statistical package.