Undergraduate Course Directory

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Courses by Subject Area

Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses. See the Ratcliffe Hicks Courses page for a list of those courses.

1000Q. Introduction to Statistics I

4.00 credits

Prerequisites: Students can receive no more than four credits from STAT 1000Q and 1100Q. Students who have passed a 2000-level or above STAT course cannot take 1000-level STAT courses.

Grading Basis: Graded

A standard approach to statistical analysis primarily for students of business and economics; elementary probability, sampling distributions, normal theory estimation and hypothesis testing, regression and correlation, exploratory data analysis. Learning to do statistical analysis on a personal computer is an integral part of the course. GEOC

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1100Q. Elementary Concepts of Statistics

4.00 credits

Prerequisites: Students can receive no more than four credits from STAT 1000Q and 1100Q. Students who have passed a 2000-level or above STAT course cannot take 1000-level STAT courses.

Grading Basis: Graded

Standard and nonparametric approaches to statistical analysis; exploratory data analysis, elementary probability, sampling distributions, estimation and hypothesis testing, one- and two-sample procedures, regression and correlation. Learning to do statistical analysis on a personal computer is an integral part of the course.

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2215Q. Introduction to Statistics II

3.00 credits

Prerequisites: STAT 1000 or STAT 1100 .

Grading Basis: Graded

Analysis of variance, multiple regression, chi-square tests, and non-parametric procedures.

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3005. Biostatistics for Health Professions

Also offered as: AH 3005

3.00 credits

Prerequisites: A course in pre-calculus or higher; STAT 1000Q or 1100Q or higher. Open to CAHNR students and Statistics majors, juniors or higher; others with instructor consent. Not open for credit to students who have passed STAT 4625.

Grading Basis: Graded

Introduction to biostatistical techniques, concepts, and reasoning using in a broad range of biomedical and public health related scenarios. Specific topics include description of data, statistical hypothesis testing and its application to group comparisons, and tools for modeling different type of data, including categorical, and time-event, data. Emphasis on the distinction of these methods, their implementation using statistical software, and the interpretation of results applied to health sciences research questions and variables.

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3025Q. Statistical Methods

3.00 credits

Prerequisites: MATH 1132 or 1152; students may not receive more than three credits from STAT 3025 and 3345. Not open for credit to students who have passed STAT 3445

Grading Basis: Graded

Basic probability distributions, point and interval estimation, tests of hypotheses, correlation and regression, analysis of variance, experimental design, non-parametric procedures.

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3115Q. Analysis of Experiments

3.00 credits

Prerequisites: STAT 2215 or 3025 or instructor consent. Credit may not be received for both STAT 3115 and 5315.

Grading Basis: Graded

Straight-line regression, multiple regression, regression diagnostics, transformations, dummy variables, one-way and two-way analysis of variance, analysis of covariance, stepwise regression.

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3345Q. Probability Models for Engineers

3.00 credits

Prerequisites: MATH 2110 or 2130. Students may not receive more than three credits from STAT 3025 and STAT 3345 or from STAT 3345 and STAT 3375.

Grading Basis: Graded

Probability set functions, random variables, expectations, moment generating functions, discrete and continuous random variables, joint and conditional distributions, multinomial distribution, bivariate normal distribution, functions of random variables, central limit theorms, computer simulation of probability models.

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3375Q. Introduction to Mathematical Statistics I

3.00 credits

Prerequisites: A grade of C+ or better in MATH 2110 or 2130. Students may not receive credits from both STAT 3345 and 3375 nor from both STAT 3375 and 5585. Cannot be taken after passing STAT 3445.

Grading Basis: Graded

The mathematical theory underlying statistical methods. Probability spaces, distributions in one and several dimensions, generating functions, and limit theorems.

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3445. Introduction to Mathematical Statistics II

3.00 credits

Prerequisites: STAT 3375. Students may not receive credit for both STAT 3445 and 5685. Cannot be taken for credit after STAT 4875.

Grading Basis: Graded

Sampling distributions and parameter estimation. Neyman-Pearson theory of hypothesis testing, correlation, regression, analysis of variance.

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3494W. Undergraduate Seminar

1.00 credits

Prerequisites: STAT 2215 or 3115; STAT 3025 or 3375; ENGL 1010 or 1011 or 2011.

Grading Basis: Graded

The student will attend 6-8 seminars per semester, and choose one statistical topic to investigate in detail. The student will write a well-revised, comprehensive paper on this topic, including a literature review, description of technical details, and a summary and discussion.

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3515Q. Design of Experiments

3.00 credits

Prerequisites: STAT 2215 or 3025 or instructor consent. Credits may not be received for both STAT 3515 and BIST/STAT 5515.

Grading Basis: Graded

Methods of designing experiments utilizing regression analysis and the analysis of variance.

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3675Q. Statistical Computing

4.00 credits

Prerequisites: STAT 3025 or 3375. Recommended preparation: An applied statistics course.

Grading Basis: Graded

Introduction to computing for statistical problems; obtaining features of distributions, fitting models and implementing inference (obtaining confidence intervals and running hypothesis tests); simulation-based approaches and basic numerical methods. One hour per week devoted to computing and programming skills.

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3965. Elementary Stochastic Processes

Also offered as: MATH 3170

3.00 credits

Prerequisites: STAT 3025 or 3345 or 3375 or MATH 3160.

Grading Basis: Graded

Conditional distributions, discrete and continuous time Markov chains, limit theorems for Markov chains, random walks, Poisson processes, compound and marked Poisson processes, and Brownian motion. Selected applications from actuarial science, biology, engineering, or finance.

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4188. Variable Topics

3.00 credits | May be repeated for credit.

Prerequisites: Prerequisites and recommended preparation vary.

Grading Basis: Graded

With a change in topic, may be repeated for credit.

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4190. Field Study Internship

1.00 - 6.00 credits

Prerequisites: Completion with a grade of 'C' or better of STAT 3025 or 3375 and STAT3115 or 3515. Completion of Freshmen-Sophomore General CLAS requirements.

Grading Basis: Satisfactory/Unsatisfactory

Supervised field work relevant to some area of Statistics with a regional industry, government agency, or non-profit organization. Evaluated by the field supervisor and by the instructor (based on a detailed written report submitted by the student. Students taking this course will be assigned a final grade of S (satisfactory) or U (unsatisfactory).

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4299. Independent Study

1.00 - 6.00 credits | May be repeated for credit.

Prerequisites: None.

Grading Basis: Graded

May be repeated for credit.

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4389. Undergraduate Research

3.00 credits | May be repeated for credit.

Prerequisites: None.

Grading Basis: Graded

Supervised research in probability or statistics. A final written report and oral presentation are required. May be repeated for credit.

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4525. Sampling Theory

3.00 credits

Prerequisites: STAT 3445.

Grading Basis: Graded

Sampling and nonsampling error, bias, sampling design, simple random sampling, sampling with unequal probabilities, stratified sampling, optimum allocation, proportional allocation, ratio estimators, regression estimators, super population approaches, inferences in finite populations.

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4625. Introduction to Biostatistics

3.00 credits

Prerequisites: STAT 3025.

Grading Basis: Graded

Rates and proportions, sensitivity, specificity, two-way tables, odds ratios, relative risk, ordered and non-ordered classifications, trends, case-control studies, elements of regression including logistic and Poisson, additivity and interaction, combination of studies and meta-analysis.

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4825. Applied Time Series

3.00 credits

Prerequisites: STAT 3445.

Grading Basis: Graded

Introduction to prediction using time-series regression methods with non-seasonal and seasonal data. Smoothing methods for forecasting. Modeling and forecasting using univariate, autoregressive, moving average models.

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4875. Nonparametric Methods

3.00 credits

Prerequisites: STAT 3445.

Grading Basis: Graded

Basic ideas, the empirical distribution function and its applications, uses of order statistics, one- two- and c-sample problems, rank correlation, efficiency.

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