# Inferential Statistics – mth464 (3 credits)

This course presents techniques for analyzing data and uses of inferential statistics. Students examine the applications of hypothesis testing using normal probability distribution, t-distribution, analysis of variance (ANOVA), linear regression, and nonparametric data.

This undergraduate-level course is 5 weeks. This course is available to take individually or as part of a degree or certificate program. To enroll, speak with an Enrollment Representative.

### Applications of Normal Distribution, Sampling Distributions, and Confidence Intervals

• Describe the distribution of sample proportions.

• Compute probabilities of sample proportions.
• Construct confidence intervals for population means.

• Construct confidence intervals for population proportions.
• Describe the distribution of sample means.

### Hypothesis Testing

• Compute the power of tests.
• Utilize hypothesis testing to formulate a decision about a claim.

• Perform hypothesis tests for population means.
• Perform hypothesis tests for population proportions.
• Compute the probability of Type II errors.

• Perform hypothesis tests about two means.

### Inferential Methods in Regression

• Verify that residuals are normally distributed.

• Determine if a linear relationship exists between a dependent and independent variables.
• Formulate a hypothesis test to determine if an independent variable is useful for making decisions.
• Construct confidence intervals for mean responses.
• Construct prediction intervals for individual responses.

### Analysis of Variance (ANOVA)

• Perform two-way ANOVA designs.
• Interpret the summary output of ANOVA tables.

• Perform hypothesis tests using one-way ANOVA.
• Perform tests of hypothesis to determine whether the variances of two populations are equal.

### Nonparametric Tests

• Perform chi square goodness of fit tests.
• Perform tests for homogeneity of population.
• Perform chi square tests for independence.