|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
3.00 Credits
Credits: 3. Basic statistical concepts presented in a conceptual fashion, emphasizing data collection and analysis rather than theory. Topics include exploratory data analysis, design of surveys and experiments, introduction to estimation and significance tests and use of statistics in social sciences and media. (M) (MR)
-
2.00 Credits
Credits: 3; Prereq: STA 2023 or the equivalent. An introduction to the analysis of variance. Nonparametric statistical methods and applications. Analysis of count data: chi-square and contingency tables. Simple and multiple linear regression methods with applications. (M) (MR)
-
3.00 Credits
Credits: 3; Prereq: MAC 2312. Measurement of simple and compound interest, accumulated and present value. Annuities, yield rates, amortization schedules, sinking funds, bonds, securities and related funds.
-
3.00 Credits
Credits: 3; Prereq: STA 2023, STA 3032 or STA 4322. Simple linear regression and multiple linear regression models. Inference about model parameters and predictions, diagnostic and remedial measures about the model, independent variable selection, multicolinearity, autocorrelation, and nonlinear regression. SAS implementation of the above topics. (M) (MR)
-
3.00 Credits
Credits: 3; Prereq: STA 4210. An introduction to the basic principles of experimental design: analysis of variance for experiments with a single factor; randomized blocks and Latin square designs: multiple comparison of treatment means; factorial and nested designs; analysis of covariance; response surface methodology. (MR)
-
3.00 Credits
Credits: 3; Prereq: STA 2023 or STA 4322. An introduction to the design of sample surveys and the analysis of survey data, the course emphasizes practical applications of survey methodology. Topics include sources of errors in surveys, questionnaire construction, simple random, stratified, systematic and cluster sampling, ratio and regression estimation, and a selection of special topics such as applications to quality control and environmental science. (M) (MR)
-
1.00 Credits
Credits: 3; Prereq: grade of C or better in MAC 2313, and STA 2023 or STA 3032, or instructor permission. Introduction to the theory of probability, counting rules, conditional probability, independence, additive and multiplicative laws, Bayes Rule. Discrete and continuous random variables, their distributions, moments and moment generating functions. Multivariate probability distributions, independence, covariance. Distributions of functions of random variables, sampling distributions, central limit theorem. (M) (MR)
-
2.00 Credits
Credits: 3; Prereq: STA 4321 or the equivalent. Sampling distributions, central limit theorem, estimation, properties of point estimators, confidence intervals, hypothesis testing, common large sample tests, normal theory small sample tests, uniformly most powerful and likelihood ratio tests, linear models and least squares, correlation. Introduction to analysis of variance. (M) (MR)
-
3.00 Credits
Credits: 3; Prereq: STA 2023 or STA 3032 or STA 4210 or STA 4322. Introduction to nonparametric statistics, including one- and two-sample testing and estimation methods, one- and two-way layout models and correlation and regression models.
-
3.00 Credits
Credits: 3; Prereq: STA 3024 or STA 3032 or STA 4210 or STA 4322. Description and inference using proportions and odds ratios, multi-way contingency tables, logistic regression and other generalized linear models, loglinear models applications.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2025 AcademyOne, Inc.
|
|
|