Hypothesis formulation and testing; estimation and confidence limits; one and two-sample tests; and statistical decision theory. Study inferences arising from distribution functions: t, F, chi-square, binomial, normal.
An overview and basic understanding of qualitative analysis software including preparation of data files, managing text and images, creating codes, memos, queries models and reports.
The course is designed to familiarize students with the use of statistical packages on both the mainframe and microcomputer platforms. Students will learn to organize, input, and analyze data.
Course will acquaint students with the data management, data transformation and statistical analysis procedures available in SPSS for Windows.
Concurrent Prerequisite
SRM 602 with a minimum grade of C
The R programming language is an important and current research tool for statisticians. Students will receive an introduction to data manipulation, graphical techniques, model building and some programming using R.
This course provides an introduction to the Structured Query Language (SQL). Students will learn to write retrieval queries and manage data in a relational database.
The goal of this course is to familiarize students with the use of the Mplus software (Muthen and Muthen, 1998-2017). Students will become acquainted with the basics of Mplus. The course will focus on using Mplus for latent variable modeling.
This course is intended to present an introduction to the concepts and issues surrounding statistical consulting. Students will learn and practice the process of consulting and communicating with clients.
Study of probability, random variables, distributions, moments, expected values and standard probability laws, probability bounds and point estimation.
Continuation of
SRM 551. Sampling distributions, estimation techniques, maximum likelihood, tests of hypothesis, confidence intervals, regression and chi-square tests.
Specialized topics or contemporary issues. Topics vary.