# MAT 224 - Statistics II Review of probability fundamentals, discrete random variables and probability distributions. The F distributions, chi-squared distributions, hypothesis testing, analysis of variance, linear regression and correlation, nonlinear and multiple regression, the analysis of categorical data, nonparametric procedures, use of a statistical software package.
**Prerequisite- Corequisite** Prerequisite: MAT 124 Statistics I
Credits: 3
**Hours** 3 Class Hours
**Course Profile** Learning Outcomes of the Course:
Upon successful completion of this course the student will be able to:
1. Compute the mean and standard deviation for a discrete probability distribution and construct the probability histogram.
2. Solve probability problems using discrete probability distributions such as the binomial and Poisson.
3. Use the chi-square distribution to perform tests on multinomial experiments, goodness-of-fit and tests of homogeneity and independence.
4. Compute the probability of Type I and Type II errors associated with tests of hypotheses about means.
5. Compute the least squares regression line for a bivariate population and test it as a model for the population.
6. Compute, test, and interpret the meaning of the correlation coefficient for a bivariate population.
7. Use the F-distribution to test inferences about two variances.
8. Perform analysis of variance (ANOVA).
9. Test the assumptions for ANOVA.
10. Perform analysis using multiple regression and correlation models.
11. Use nonparametric statistics to conduct tests of hypotheses.
12. Use a statistical software package to conduct various data analyses.
This course prepares students to meet the Mathematics General Education requirement.
In the context of the course objectives listed above, upon successful completion of this course the student will be able to:
1. Interpret and draw inferences from mathematical models such as formulas, graphs, tables and schematics.
2. Represent mathematical information symbolically, visually, numerically and verbally.
3. Employ quantitative methods such as arithmetic, algebra, geometry, or statistics to solve problems.
4. Estimate and check mathematical results for reasonableness.
5. Recognize the limitations of mathematical and statistical methods.
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