I have conducted a linear regression model to predict student scores on an exam based on...

I have conducted a linear regression model to predict student scores on an exam based on the number of hours they studied. I get a coefficient (slope) of +2.5 for the variable of hours studied. The pvalue for this coefficient is 0.45 and the 95% confidence interval is [-2.5, +7]. Which of the following conclusions CANNOT be drawn from these results?

At an alpha of 0.05, we can say that the effect of hours studied on exam score is significant
		Our model predicts that, on average, one hour of studying increases exam score by 2.5 points
		One hour of studying could lead to a 7.5 point increase in exam score
		One hour of studying could lead to a 2.5 point decrease in exam score

Expert Solution

a coefficient (slope) of +2.5 for the variable of hours studied

Mean with increase in one hour of study the score improves by 2.5

Our model predicts that, on average, one hour of studying increases exam score by 2.5 points

This is the correct interpretation

One hour of studying could lead to a 7.5 point increase in exam score - This is false as it should be

One hour of studying could lead to a 2.5 point increase in exam score

One hour of studying could lead to a 2.5 point decrease in exam score - this is false as it should be

One hour of studying could lead to a 2.5 point increase in exam score

As p value = 0.45 and alpha = 0.05

p > alpha hence the value is not signifcant

At an alpha of 0.05, we can say that the effect of hours studied on exam score is significant - this is false as it should be

At an alpha of 0.05, we can say that the effect of hours studied on exam score is insignificant

orchestra answered 1 year ago

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