Detailed Course Outline
Introduction to statistical analysis
- • Identify the steps in the research process
- • Principles of statistical analysis
Examine individual variables
- • Identify measurement levels
- • Chart individual variables
- • Summarize individual variables
- • Examine the normal distribution
- • Examine standardized scores
Test hypotheses about individual variables
- • Identify population parameters and sample statistics
- • Examine the distribution of the sample mean
- • Determine the sample size
- • Test a hypothesis on the population mean
- • Construct a confidence interval for the population mean
- • Tests on a single variable: One-Sample T Test, Paired-Samples T Test, and Binomial Test
Test the relationship between categorical variables
- • Chart the relationship between two categorical variables
- • Describe the relationship: Compare percentages in Crosstabs
- • Test the relationship: The Chi-Square test in Crosstabs
- • Assumptions of the Chi-Square test
- • Pairwise compare column proportions
- • Measure the strength of the association
Test on the difference between two group means
- • Compare the Independent-Samples T Test to the Paired-Samples T Test
- • Chart the relationship between the group variable and scale variable
- • Describe the relationship: Compare group means
- • Test on the difference between two group means: Independent-Samples T Test
- • Assumptions of the Independent-Samples T Test
Test on differences between more than two group means
- • Describe the relationship: Compare group means
- • Test the hypothesis of equal group means: One-Way ANOVA
- • Assumptions of One-Way ANOVA
- • Identify differences between group means: Post-hoc tests
Test the relationship between scale variables
- • Chart the relationship between two scale variables
- • Describe the relationship: Correlation
- • Test on the correlation
- • Assumptions for testing on the correlation
- • Treatment of missing values
Predict a scale variable: Regression
- • What is linear regression?
- • Explain unstandardized and standardized coefficients
- • Assess the fit of the model: R Square
- • Examine residuals
- • Include 0-1 independent variables
- • Include categorical independent variables
Introduction to Bayesian statistics
- • Bayesian statistics versus classical test theory
- • Explain the Bayesian approach
- • Evaluate a null hypothesis: Bayes Factor
- • Bayesian procedures in IBM SPSS Statistics
Overview of multivariate procedures
- • Overview of supervised models
- • Overview of models to create natural groupings