We're still actively developing this site. If you encounter any issues, please report them! - Report an issue

INTRODUCTION TO STATISTICAL METHODS

STAT 301
Course Description

Distributions, measures of central tendency, dispersion and shape, the normal distribution; experiments to compare means, standard errors, confidence intervals; effects of departure from assumption; method of least squares, regression, correlation, assumptions and limitations; basic ideas of experimental design.

Prerequisties

Satisfied Quantitative Reasoning (QR) A requirement. Not open to students with credit for STAT 302, STAT 324 , or STAT 371

Satisfies
Credits

3

Offered

Fall, Spring, Summer

Grade Point Average
2.85

-5.09% from Historical

Completion Rate
92.72%

-0.32% from Historical

A Rate
24.8%

-16.07% from Historical

Class Size
371

-35.38% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

Similar Courses

BASIC STATISTICS FOR PSYCHOLOGY

PSYCH 210

Measures of central tendency, variability; probability, sampling distributions; hypothesis testing, confidence intervals; t-tests; Chi-square; regression and correlation (linear) and introduction to analysis of variance (1-way).

STATISTICAL METHODS I

STAT 601

Provides a thorough grounding in modern statistical methods. The specific learning outcomes for the course are to understand data collection in context (how/why data were collected, key questions under study); explore data by effective graphical and numerical summaries; understand probability concepts and models as tools for studying random phenomena and for statistical inference; analyze data using appropriate, modern statistical models, methods, and software; understand the statistical concepts underlying methods; develop the ability to interpret results and critically evaluate the methods used; communicate data analysis and key findings in context.

STATISTICAL METHODS FOR DATA SCIENCE

STAT 613

Provides a thorough grounding in modern statistical methods. Introduces statistical techniques and methods of data analysis, including data description, linear regression models, diagnostic tools, prediction and model selection, and experimental design.

INTRODUCTION TO STATISTICAL INFERENCE

STAT 610

Conditioning, distribution theory, approximation to distributions, modes of convergence, limit theorems, statistical models, parameter estimation, comparision of estimators, confidence sets, theory of hypothesis tests, introduction to Bayesian inference and nonparametric estimation.

STATISTICAL METHODS II

STAT 602

Provides a thorough grounding in modern statistical methods. The specific learning outcomes for the course are to understand data collection in context (how/why data were collected, key questions under study); explore data by effective graphical and numerical summaries; understand probability concepts and models as tools for studying random phenomena and for statistical inference; analyze data using appropriate, modern statistical models, methods, and software; understand the statistical concepts underlying methods; develop the ability to interpret results and critically evaluate the methods used; communicate data analysis and key findings in context.