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