# Statistics Course Descriptions

**STAT 13000. Statistics and Contemporary Life**

*(Class 3, Cr. 3) 3) General Education*

Introduction to statistical ideas and their impact on various aspects of modern life. Topics will include the organization, manipulation, and understanding of numerical data, the art of data presentation, interpretation of statistical information as presented in the media, the concept of randomness in gambling and lotteries, and some discussion of statistical fallacies.

**STAT 30100. Elementary Statistical Methods I**

*(Class 3, Cr. 3)*

*Prerequisites: MA 14700*

A basic introductory statistics course with applications shown to various fields and emphasis placed on assumption, applicability, and interpretations, or various statistical techniques. Subject matter includes frequency distributions, descriptive statistics, elementary probability, normal analysis of variance, with emphasis on distribution applications, sampling distribution, estimation, hypothesis testing and linear regression.

**STAT 31500. Introduction To Probability And Statistics**

*(Class 3, Cr. 3)*

Probability theory with a short-introduction to statistics. Not enough statistics to serve as a preparation for a second course in statistics.

*(Class 3, Cr. 3)*

*Prerequisites: MA 15300 and BIOL 10100 and BIOL 10200 or BIOL 10800 and BIOL 10900*

*(Not open to students with credit in BIOL 33000.)*

This course will explore fundamental concepts of statistical methods and their application in biological research. The following topics will be included: experimental and sampling designs; descriptive statistics; basic probability and probability distribution; tests of hypothesis; one-way analysis of variance; linear regression. Emphasis will be placed on the collection, organization, analysis and interpretation of data from biological experiments and observations.

*(Class 3, Cr. 3)*

*Prerequisites: MA 16400*

Topics from exploratory data analysis and inferential statistics will be covered, along with a necessary introduction to probability. Statistical and probabilistic simulations will be used to enhance students’ understanding of randomness and variation. Extensive use of a statistical computer package will be required.

**STAT 49000. Topics In Statistics For Undergraduates**

*(Class 0 to 5, Cr. 1 to 5)*

Supervised reading and reports in various fields. Open only to students with the consent of the department.

**STAT 50100. Experimental Statistics I**

*(Class 3, Cr. 3)*

*Prerequisites: MA 15300 or MA 15900*

*(Primarily intended for students who have not had calculus.)*

*(Not open to students in mathematics, statistics, or computer science.)*

*(Credit should not be allowed in more than one of STAT 30100, STAT 50100,or STAT 51100.)*

Fundamental concepts and methods of statistics for students interested in the analysis of experimental data. Subjects include descriptive statistics, basic probability theory, normal distribution, tests of hypotheses and confidence intervals for normal and Bernoulli populations, contingency tables, tests of goodness-of-fit, linear regression and non parametric test.

**STAT 50200. Experimental Statistics II**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 50100*

Continuation of STAT 50100. Subject matter includes multiple regression and analysis of variance, with emphasis on statistical inference and applications to various fields.

**STAT 51100. Statistical Methods**

*(Class 3, Cr. 3)*

*Prerequisites: MA 26100*

Descriptive statistics; elementary probability; sampling distributions; inference, testing hypotheses, and estimation; normal, binomial, poison, hypergeometric distributions; one way analysis of variance; contingency tables; regression.

**STAT 51200. Applied Regression Analysis**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 51100 or STAT 51700*

Inference in simple and multiple linear regression, residual analysis, transformations, polynomial regression, model building with real data, nonlinear regression. One-way and two-way analysis of variance, multiple comparisons, fixed and random factors, analysis of covariance. Use of existing statistical computer programs.

**STAT 51300. Statistical Quality Control**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 51100 or STAT 51600*

A strong background in control charts including adaptations, acceptance plans, sequential analysis, statistics of combinations, moments and probability distributions, applications.

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**STAT 51400. Design Of Experiments**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 51100 or STAT 51200*

Fundamentals, completely randomized design; randomized complete blocks; latin square; multi-classification; nested factorial; incomplete block and fractional replications for 2n,3n,2m x 3n; confounding; lattice designs; general minded factorials; split plot; analysis of variance in regression models; optimum design. Use of existing statistical programs.

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**STAT 51600. Basic Probability and Applications**

*(Class 3, Cr. 3)*

*Prerequisites: MA 16400 or MA 22400*

*Co-requisite: MA 26100*

A first course in probability intended to serve as a background for statistics and other applications. Sample spaces and axioms of probability, discrete and continuous random variables, conditional probability and Bayes’ theorem, joint and conditional probability distributions, expectations, moments and moment generating functions, law of large numbers and central limit theorem. (The probability material in Course 1 of the Society of Actuaries and the Casualty Actuarial Society is covered in this course.)

**STAT 51700. Statistical Inference**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 51600 or STAT 51900*

A basic course in statistical theory covering standard statistical methods and their applications. Estimation including unbiased, maximum likelihood and moment estimation; testing hypothesis for standard distributions, and contingency tables; confidence intervals and regions; introduction to non-parametric tests and linear regression.

**STAT 53200. Elements Of Stochastic Processes**

*(Class 3, Cr. 3)*

*Prerequisites: STAT 51900*

A basic course in stochastic models, including discrete and continuous time Markov Chains and brownian motion, as well as an introduction to topics such as Gaussian processes, renewal processes, replacement, and reliability problems.