- Explain why probability is a concern when conducting educational research.
- State the purpose of inferential statistics.
- Differentiate sampling error from measurement error. Describe the relevance of both to inferential statistics.
- Define the term null hypothesis and describe its role in inferential statistics.
- Define the term level of significance and describe its use in inferential statistics. Describe the formats used to report the level of significance associated with an inferential test.
- Explain the difference between Type I and Type II errors.
- Explain the meaning of the term statistically significant. Differentiate statistical significance from educational (i.e., practical) significance and describe the ways researchers report the latter.
- Explain the logic of inferential testing.
- Identify situations in which you would use a t-test. Differentiate independent samples from dependent samples.
- Identify situations in which you would use a one factor ANOVA. Describe the purpose of post-hoc analyses and planned comparisons. Identify five post-hoc procedures.
- Differentiate a one factor ANOVA from a factorial ANOVA. Define the terms main effect and interaction effect.
- Identify the unique characteristics of ANCOVA. Define the term covariate.
- Describe the unique characteristics of MANOVA.
- Explain the difference between parametric and non-parametric tests. Identify situations in which you would use a Chi-Square test.
- Evaluate the inferential analyses found in a research report in terms of the appropriateness of the inferential test used, statistical significance, practical significance, and the relationship between the results and the research problem.
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