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Answer: For every one unit change in the number of study hours, the model predicts that the average score will change by 2 units
The slope coefficient in a linear regression model represents the expected change in the dependent variable (average test score) for a 1-unit change in the independent variable (study hours). **Key points:** - A slope coefficient of 2 means that for every additional hour of study, the model predicts the average test score will increase by 2 units. - Option A describes the intercept (constant term), not the slope coefficient. - Option B incorrectly describes the intercept and adds a percentage sign. - Option D incorrectly states the change is 2% rather than 2 units. - The intercept coefficient represents the predicted value of the dependent variable when the independent variable is zero, while the slope coefficient represents the rate of change.
Author: Nikitesh Somanthe
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A graduate school constructs a linear regression model to estimate the effect of increased study hours on the average performance of students in a test. The slope coefficient is found to be equal to 2. What does this mean?
A
The average score when the number of study hours is zero is 2
B
The predicted score when the number of study hours is zero is 2%
C
For every one unit change in the number of study hours, the model predicts that the average score will change by 2 units
D
For every one unit change in the number of study hours, the model predicts that the average score will change by 2%
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