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.
Construct confidence intervals for population proportions.
Construct confidence intervals for population means.
Compute probabilities of sample proportions.
Describe the distribution of sample means.
Perform tests for homogeneity of population.
Perform chi square tests for independence.
Perform chi square goodness of fit tests.
Inferential Methods in Regression
Construct prediction intervals for individual responses.
Construct confidence intervals for mean responses.
Verify that residuals are normally distributed.
Formulate a hypothesis test to determine if an independent variable is useful for making decisions.
Determine if a linear relationship exists between a dependent and independent variables.
Analysis of Variance (ANOVA)
Interpret the summary output of ANOVA tables.
Perform two-way ANOVA designs.
Perform hypothesis tests using one-way ANOVA.
Perform tests of hypothesis to determine whether the variances of two populations are equal.
Perform hypothesis tests about two means.
Compute the power of tests.
Compute the probability of Type II errors.
Perform hypothesis tests for population proportions.
Perform hypothesis tests for population means.
Utilize hypothesis testing to formulate a decision about a claim.
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