Statistics (BS)

Limits, continuity, the derivative and applications, transcendental functions, L'Hopital's Rule, and development of the Riemann integral.

Prerequisites: Satisfy Placement Table in this section, MATH 115 or both MATH 112 and MATH 113 with "C" (2.0) or better.

Goal Areas: GE-04

This course provides conceptual and logical tools for students planning to major in a computing-based major. Programming in a high-level language such as C++, Python, or Java, and the development of skills in abstraction, problem-solving, and algorithmic thinking are emphasized.

Prerequisites: MATH 112 or MATH 113 or MATH 115 or MATH 121

This course is a continuation of CIS 121. Students develop a basic knowledge of programming skills and object-oriented concepts, and use fundamental data structures such as lists, stacks, queues, and trees.

Prerequisites: MATH 113 or MATH 115 or MATH 121; and CS 110 or CIS 121 or IT 210

Techniques of integration, applications of integration, improper integrals, numerical integration, the calculus of parametric curves, and infinite series and sequences.

Prerequisites: MATH 121 with "C" (2.0) or better or consent

Surfaces, vector-valued functions, partial differentiation, multiple integration, and vector calculus.

Prerequisites: MATH 122 with "C" (2.0) or better, or consent

Matrices, determinants, systems of linear equations, vector spaces, linear transformations, and characteristic value problems.

Prerequisites: MATH 122 with "C" (2.0) or better or consent

An introduction to statistical concepts and methods that is applicable to all disciplines. Topics include descriptive measures of data, probability and probability distributions, statistical inference, tests of hypotheses, confidence intervals, correlation, linear regression, and analysis of variance. The use of statistical software will be emphasized. Prereq: ACT Math sub-score of 19 or higher, successful completion of MATH 098 or appropriate placement scores (see Placement Information under Statistics) Fall, Spring, Summer GE-4

Prerequisites: Satisfy Placement Table in this section, or MATH 098 with grade of P.

Goal Areas: GE-02, GE-04

A calculus based introduction to probability and statistics. Topics include probability, random variables, probability distributions (discrete and continuous), joint probability distributions (discrete and continuous), statistical inference (both estimation and hypothesis testing), confidence intervals for distribution of parameters and their functions, sample size determinations, analysis of variance, regression, and correlation. This course meets the needs of the practitioner and the person who plans further study in statistics. Same as MATH 354. Prereq: MATH 122 with C or better or consent Fall, Spring, Summer

Prerequisites: MATH 122 with C or better or consent

Introduction to basic programming techniques: creating DATA and PROC statements, libraries, functions, programming syntax, and formats. Descriptive and Inferential statistics in SAS. Emphasis is placed on using these tools for statistical analyses. Working with arrays, loop and SAS macro.

Prerequisites: STAT 154 or instructor's approval

Simple and multiple linear regression, model adequacy checking and validation, identification of outliers, leverage and influence, polynomial regression, variable selection and model building strategies, nonlinear regression, and generalized linear regression.

Prerequisites: MATH 354 / STAT 354 or STAT 455 with "C" (2.0) or better or consent

Randomized complete block design, Latin squares design, Graco- Latin squares design, balanced incomplete block design, factorial design, fractional factorial design, response surface method, fixed effects and random effects models, nested and split plot design.

Prerequisites: MATH 354 / STAT 354 or STAT 455 with "C" (2.0) or better or consent

A mathematical approach to statistics with derivation of theoretical results and of basic techniques used in applications. Includes probability, continuous probability distributions, multivariate distributions, functions of random variables, central limit theorem and statistical inference. Same as MATH 455. Prereq: MATH 223 with C or better or consent

Prerequisites: MATH 223 with "C" (2.0) or better or consent

A mathematical approach to statistics with derivation of theoretical results and of basic techniques used in applications, including sufficient statistics, additional statistical inference, theory of statistical tests, inferences about normal models and nonparametric methods. Same as MATH 456. Prereq: MATH/STAT 455 with C or better or consent

Prerequisites: MATH 455, STAT 455 with "C" (2.0) or better or consent

Sampling distributions: means and variances. Bias, robustness and efficiency. Random sampling, systematic sampling methods including stratified random sampling, cluster sampling and two-stage sampling, ratio, regression, and population size estimation. Suitable statistical software is introduced, for example, MATLAB, R, SAS, etc.

Prerequisites: Either MATH/STAT 354 or both MATH 121 adn STAT 154 with "C" (2.0) or better, or consent.

Forms of multivariate analysis for discrete data, two dimensional tables, models of independence, log linear models, estimation of expected values, model selection, higher dimensional tables, logistic models and incompleteness. Logistic regression. Suitable statistical software is introduced, for example, MATLAB, R, SAS etc.

Prerequisites: Either MATH/STAT 354 or both MATH 121 and STAT 154 with "C" (2.0) or better, or consent.

Derivation and usage of nonparametric statistical methods in univariate, bivariate, and multivariate data. Applications in count, score, and rank data, analysis of variance for ranked data. Nonparametric regression estimation. Suitable statistical software is introduced, for example, MATLAB, R, SAS, etc.

Prerequisites: Either MATH/STAT 354 or both STAT 154 and MATH 121 with "C" (2.0) or better, or consent.

This course is designed to allow undergraduate students an opportunity to integrate their statistics experiences by engaging each student in working on problems in applied or theoretical statistics. Spring

Prerequisites: STAT 457, STAT 458, STAT 459, STAT 450 (at least two of these)

The accounting process, financial statement preparation, and analysis. Includes the accounting cycle, asset, liability, and equity accounting. Emphasis on the use of accounting data.

Prerequisites: MATH 112 or MATH 115or MATH 121 or MATH 130 or MATH 181

An introduction to finance relating to problems, methods, and policies in financing business enterprise.

Prerequisites: ACCT 200

Formulation of investment policy of individuals and institutions, factors influencing the values of securities, and techniques of portfolio selection and management.

Prerequisites: FINA 362

This course applies probabilistic methods to problems encountered in actuarial science that prepares students for the Society of Actuaries Exam P/1.

Prerequisites: (MATH 354, STATS 354, MATH 455 or STAT 455) and MATH 223

This course covers all the topics in the mathematical theory of interest of the Society of Actuaries Exam FM/2. Topics include time value of money, measurement of interest, annuities certain, arithmetic and geometric annuities, amortization schedules and sinking fund, bonds and other securities, yield rates, and interest rate immunization.

Prerequisites: MATH 122 with C (2.0) or better or consent.