A study wants to examine the relationship between student anxiety for an exam and the number of hours studied. The data is as follows:
Student Anxiety Scores 5 10 5 11 12 4 3 2 6 1
Study Hours 1 6 2 8 5 1 4 6 5 2
1.Why is a correlation the most appropriate statistic?
2.What is the null and alternate hypothesis?
3.What is the correlation between student anxiety scores and number of study hours? Select alpha and interpret your findings. Make sure to note whether it is significant or not and what the effect size is.
4.How would you interpret this?
5.What is the probability of a type I error? What does this mean?
6.How would you use this same information but set it up in a way that allows you to conduct a t-test? An ANOVA?
Explain why a correlation is the most appropriate statistic.
List the null and alternate hypothesis.
Compute and correctly present the correlation between student anxiety scores and number of study hours.
List the alpha, statistical significance of the results and the effect size. Provide an interpretation of the results.
List the probability of a type I error and explain what it means.
Explain how the same information would be set up to allow one to conduct a t-test and an ANOVA.
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