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  1. What are degrees of freedom? How are the calculated?
  2. What do inferential statistics allow you to infer?
  3. What is the General Linear Model (GLM)? Why does it matter?
  4. Compare and contrast parametric and nonparametric statistics. Why and in what types of cases would you use one over the other?
  5. 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?
  6. 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?
  7. Compare and contrast the concepts of effect size and statistical significance.
  8. What is the difference between a statistically significant result and a clinically or “real world” significant result? Give examples of both.
  9. What is NHST? Describe the assumptions of the model.
  10. Describe and explain three criticisms of NHST.
  11. Describe and explain two alternatives to NHST. What do their proponents consider to be their advantages?

Support your paper with a minimum of 5 resources. In addition to these specified resources, other appropriate scholarly resources, including older articles, may be included.

Length: 5-7 pages not including title and reference pages
References: Minimum of 5 scholarly resources.

apa style

 
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