Course Requirements For a Minor in Statistics

The student must finish 24 credit hours including (Stat231 or Stat236), Stat331, Stat332, Stat333, Stat334, Stat431 and two of the courses Stat336, Stat335, Stat432 and Stat438.

Course Description:

231- Basic Statistics For Science:

Classification of data, averages, dispersion, probability, frequency distributions, confidence intervals, tests of significance for one and two means , Statistical packages.
Prerequisite: No prerequisite .

236- Basic Statistics for Business students:

Statistical measures, data description, probability, Random variables probability distribution, estimation, Test of hypothesis correlation , expectation.

331- Statistical Methods:

Estimation, inference, multiple regression, and correlation. Elementary decision theory.
Prerequisite: Stat 231

332- Introduction to Mathematical Statistics:

Probability, probability distributions, sampling, sampling distributions.
Prerequisite: Math 237 or Stat 231 or Math236

333- Introduction to Mathematical Statistics II:

Introduction to the theory of point estimation and Statistical inference, including confidence intervals and hypothesis testing.
Prerequisite: Stat 332.

334- Regression Analysis:

Simple and multiple regression, least squares, curve fitting, graphic techniques, and tests and confidence intervals for regression coefficients.
Prerequisite: Stat 333, Stat 331.

335- Analysis of Variance:

Single -Factor ANOVA model and tests, analysis of factor level effects, two-factor analysis of variance, multifactor studies, analysis of covariance.
Prerequisite: Stat 331, Stat 333.

336- Categorical Data Analysis:

Measures and tests of association; Mantel-Haenszel procedure; weighted least squares and maximum likelihood estimators in linear models.
Prerequisite: Stat. 333.

431- Sampling Techniques(I):

Simple random sampling, sampling proportions and percentages, estimation of sample size, stratified random sampling.
Prerequisite: Stat 332, Stat 331

432- Sampling Techniques(II):

Ratio estimators, regression estimators, systematic sampling, single-stage cluster sampling, subsampling, double sampling.
Prerequisite: Stat 431.

438- Special Topics