A student was wondering whether spending a great deal of time on a test is worthwhile,...

A student was wondering whether spending a great deal of time on a test is worthwhile, so he obtains results from a sample of 10 previous students and conduct a linear regression analysis. The results appear below.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.814^a	.662	.620	7.38577
a. Predictors: (Constant), Time (min)

ANOVA^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	854.624	1	854.624	15.667	.004^b
	Residual	436.397	8	54.550
	Total	1291.021	9
a. Dependent Variable: Grade (%)
b. Predictors: (Constant), Time (min)

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	T	Sig.
		B	Std. Error	Beta
1	(Constant)	25.584	13.032		1.963	.085
	Time (min)	.407	.103	.814	3.958	.004
a. Dependent Variable: Grade (%)

Is there a significant linear association between time spent on the test and the grade? How do you know?

What percentage of variation in grade is explained by its relationship with time spent on the test?

If a student turned in her test after 100 minutes, predict her score.

A freshman who didn't take the course yet asks about the results from part a: “So, explain this to him / her. Does this mean that if a student wait and turn in the test at the last minute, he / she is going to get a good grade?” Respond as a competent biostatistician, based on your results and your understanding of the conceptual basis of the analysis.

Expert Solution

orchestra answered 2 years ago

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