What are degrees of freedom? How are the calculated?

What do inferential statistics allow you to infer?

What is the General Linear Model (GLM)? Why does it matter?

Compare and contrast parametric and nonparametric statistics. Why and in what types of cases would you use one over the other?

Why is it important to pay attention to the assumptions of the statistical test? What are your options if your dependent variable scores are not normally distributed?

Part II
Part II introduces you to a debate in the field of education between those who support Null Hypothesis Significance Testing (NHST) and those who argue that NHST is poorly suited to most of the questions educators are interested in. Jackson (2012) and Trochim and Donnelly (2006) pretty much follow this model. Northcentral follows it. But, as the authors of the readings for Part II argue, using statistical analyses based on this model may yield very misleading results. You may or may not propose a study that uses alternative models of data analysis and presentation of findings (e.g., confidence intervals and effect sizes) or supplements NHST with another model. In any case, by learning about alternatives to NHST, you will better understand it and the culture of the field of education.

Answer the following questions:

What does p = .05 mean? What are some misconceptions about the meaning of p =.05? Why are they wrong? Should all research adhere to the p = .05 standard for significance? Why or why not?

Compare and contrast the concepts of effect size and statistical significance.

What is the difference between a statistically significant result and a clinically or "real world" significant result? Give examples of both.

What is NHST? Describe the assumptions of the model.

Describe and explain three criticisms of NHST.

Describe and explain two alternatives to NHST. What do their proponents consider to be their advantages?

Which type of analysis would best answer the research question you stated in Activity 1? Justify your answer.