Data Analysis Plan

The four variables in this test are the number of correct answers in quiz 1, previous GPA, total points earned in class, and the number of correct answers in the final exam. This data is continuous because it represents a difference in magnitude from low to high scores from the students. From this data one can determine if there is a significant relationship between the number of correct answers in quiz 1 to the number of correct answers in the final exam. The null hypothesis is that there is no significant relationship between the number of correct answers in Quiz 1 and the number of correct answers in the final exam. The alternative hypothesis is there is a significant relationship between the number of correct answers in Quiz 1 and the number of correct answers in the final exam.

Testing Assumptions

Descriptive Statistics
	quiz1	final	total	gpa
Skewness		-0.851		-0.341		-0.757		-0.220
Std. Error of Skewness		0.236		0.236		0.236		0.236
Kurtosis		0.162		-0.277		1.146		-0.688
Std. Error of Kurtosis		0.467		0.467		0.467		0.467

The kurtosis values for number of correct answers in quiz 1, total points earned in class, and the number of correct answers in the final exam are positive. The kurtosis value for previous GPA is negative. The data is not normally distributed because the p-values for all the variable are less than .05 and therefore the assumption of normality was violated.

Results and Interpretation

Pearson's Correlations
Variable		gpa	quiz1	final	total
1. gpa		Pearson's r
		p-value
2. quiz1		Pearson's r		0.152
		p-value		0.121
3. final		Pearson's r		0.379	***	0.499	***
		p-value		<.001		<.001
4. total		Pearson's r		0.318	***	0.797	***	0.875	***
		p-value		<.001		<.001		<.001
*p < .05, ** p < .01, *** p < .001

The lowest magnitude correlation in the intercorrelation matrix is between quiz1 and gpa. With 105 degrees of freedom, a correlation coefficient of 0.152, a p-value of 0.121, and an effect size of 0.062. This effect size shows a small but significant correlation between quiz1 and gpa. Therefore, the null hypothesis can be rejected for this correlation. The highest magnitude correlation in the intercorrelation matrix is between final and total, with 105 degrees of freedom, a correlation coefficient of 0.875, a p-value of 0.001, and an effect size of 0.743. This suggests a significantly large correlation between final and total. Therefore, the null hypothesis can be rejected for this correlation. The correlation between GPA and final is 105 degrees of freedom, acorrelation coefficient of 0.379, a p-value of 0.001, and an effect size of 0.227. This effect size shows a significant correlation between GPA and final. Therefore, the null hypothesis can be rejected for this correlation.

• Provide a brief summary of the analysis and the conclusions drawn.
• Analyze the limitations of the statistical test.
• Provide any possible alternate explanations for the findings and potential areas for future exploration.