Course Descriptions

STAT-I 350 - Introduction to Statistics

Credits:

3

Description:

A data-oriented introduction to the fundamental concepts and methods of applied statistics. The course is intended primarily for majors in the mathematical sciences (mathematics, actuarial sciences, mathematics education). The objective is to acquaint the students with the essential ideas and methods of statistical analysis for data in simple settings. It covers material similar to that of STAT-I 511, but with emphasis on more data-analytic material. Includes a weekly computing laboratory using Minitab.

Prerequisite:

MATH-I 166.

STAT-S 351 - Honors Introduction to Statistics

Credits:

3

Description:

This course introduces the basic concepts and methods of applied statistics in all areas of science and engineering. Three distinctive features of this honors course are: (1) self-learning and discovery of concepts and methods of statistical analysis through guided instructions, literature search, derivation and simulation; (2) classroom participation - both individually and collaboratively - in active learning of difficult concepts; and (3) communicating such learning to general readers. Students will acquire a basic competence in using statistical freeware R, in presenting data visually, in analyzing data appropriately, in interpreting the results in the context of research problems, and in communicating findings in plain but impactful language to readers not trained in Statistics. STAT-S 351 extends all material covered in STAT-I 350 to a deeper level and gives glimpses into some methodologies delegated to advanced courses, thereby motivating and preparing students to take advanced undergraduate statistics courses.

Prerequisite:

MATH-I 166.

STAT-S 352 - Data Modeling and Inference

Credits:

3

Description:

Intermediate-level survey of resampling, likelihood, and Bayesian methods of statistical inference. Distributional models of various data types. Categorical, count, time-to-event, time series, linear models, and hierarchical regression models.

Prerequisite:

STAT-I 350 or MATH-M 366 or MATH-M 466 or equivalent.

STAT-I 371 - Prep for Actuarial Exam I

Credits:

2

Description:

This course is intended to help actuarial students prepare for the SOA/CAS Exam P/1.

STAT-I 390 - Topics in Statistics for Undergraduates

Credits:

3

Description:

Supervised reading course or special topics course at the junior level. Prerequisites and course material vary with the topic.

STAT-I 414 - Introduction to Design of Experiments

Credits:

3

Description:

The course offers comprehensive coverage of the key elements of experimental design used by applied researchers to solve problems in the field. It shows students how to use applied statistics for planning, running, and analyzing experiments. The emphasis is placed on the basic philosophy of design. The course requires the use of the software such as SAS, Minitab, or R.

Prerequisite:

STAT-I 417 or STAT-I 512 or MATH-M 366 or MATH-M 466 or equivalent.

STAT-I 416 - Probability

Credits:

3

Description:

An introduction to mathematical probability suitable as preparation for actuarial science, statistical theory, and mathematical modeling. General probability rules, conditional probability, Bayes theorem, discrete and continuous random variables, moments and moment generating functions, continuous distributions and their properties, law of large numbers, and central limit theorem.

Prerequisite:

MATH-I 261.

STAT-I 417 - Statistical Theory

Credits:

3

Description:

An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Most powerful and likelihood-ratio tests. Distribution theory for common statistics based on normal distributions.

Prerequisite:

STAT-I 416.

STAT-I 421 - Modern Statistical Modeling Using R and SAS

Credits:

3

Description:

An introductory course on statistical computation. The primary goals of this course are (i) to introduce popular statistical software SAS and R and to develop basic data analysis skills, and (ii) to introduce basic statistical computation methods used in applications.

Prerequisite:

STAT-I 417 or equivalent.

STAT-I 432 - Introduction to Stochastic Process and Probability Modeling

Credits:

3

Description:

The course builds on elementary probability theory and introduces stochastic processes applied to the study of phenomena in fields such as engineering, computer science, management science, the life, physical and social sciences, and operations research. The approach is heuristic and non-rigorous. It develops students’ intuitive feel for the subject and enables them to think probabilistically. Computation is emphasized and requires use of software such as Excel, MINITAB, and R.

Prerequisite:

STAT-I 416 or equivalent.

STAT-I 433 - Introduction to Nonparametric Statistics

Credits:

3

Description:

The course acquaints students with rank-based, permutation-based and resampling-based methods of statistical analysis used in widely applicable settings where the data do not follow parametric models. It extends techniques taught in STAT-I 350 / STAT-I 511, where the normal theory is assumed, to situations where the normal theory does not hold. It includes computer projects which use statistical software such as R and SAS.

Prerequisite:

STAT-I 417 and STAT-I 421 or equivalents.

STAT-S 437 - Categorical Data Analysis

Credits:

3

Description:

The analysis of cross-classified categorical data. Loglinear models; regression models in which the response variable is binary, ordinal, nominal, or discrete. Logit, probit, multinomial logit models; logistic and Poisson regression.

Prerequisite:

STAT-I 417 or MATH-M 366 or MATH-M 466 or equivalent.

STAT-S 460 - Sampling

Credits:

3

Description:

Design of surveys and analysis of sample survey data. Simple random sampling, ratio and regression estimation, stratified and cluster sampling, complex surveys, nonresponse bias.

Prerequisite:

STAT-I 417 or MATH-M 366 or MATH-M 466 or equivalent.

STAT-I 472 - Actuarial Models I

Credits:

3

Description:

Mathematical foundations of actuarial science emphasizing probability models for life contingencies as the basis for analyzing life insurance and life annuities and determining premiums. This course, together with its sequel, STAT-I 473, provides most of the background for Exams MLC and MFE of the Society of Actuaries.

Prerequisite:

STAT-I 417 or equivalent.

STAT-I 473 - Actuarial Models II

Credits:

3

Description:

Continuation of STAT-I 472. Together, these courses cover contingent payment models, survival models, frequency and severity models, compound distribution models, simulation models, stochastic process models, and ruin models.

Prerequisite:

STAT-I 472.

STAT-I 479 - Loss Models

Credits:

3

Description:

This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models. Permission of instructor required.

Prerequisite:

STAT-I 417 and STAT-I 472 and STAT-I 473.

STAT-I 480 - Credibility and Simulation

Credits:

3

Description:

A continuation of the material covered in STAT-I 479, including Credibility Theory and Simulation calibration and evaluation of the models.

Prerequisite:

STAT-I 479.

STAT-I 490 - Topics in Statistics for Undergraduates

Credits:

1-5

Description:

Supervised reading and reports in various fields.

STAT-S 501 - Statistical Methods I: Introduction to Statistics

Credits:

3

Description:

This course takes a systematic approach to the exposition of the general linear model — focusing on correlation, simple linear and multiple regression. Students are introduced to the use of statistical analysis software. The first third of the course consists of a review of statistics, data analysis tools, significance tests, and confidence intervals. Students learn how to think creatively about the use of statistical methods in their own research.

Prerequisite:

One undergraduate course in statistics.

STAT-S 503 - Statistical Methods II: Generalized Linear Models and Categorical Data

Credits:

3

Description:

This course takes a systematic approach to the exposition of the general linear model — focusing on categorical data. Of primary concern will be models for which the response variable is categorical. Such models include probit, logit, ordered logit, and Poisson regression, among others. Students learn how to think creatively about the use of statistical methods in their own research.

Prerequisite:

STAT S501 or one undergraduate course in statistics.