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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.
## Explanation The slope coefficient in a linear regression model represents the expected change in the dependent variable for a 1-unit change in the independent variable. **Key Points:** - **Slope coefficient = 2** means that for every 1-unit increase in study hours, the average test score is predicted to increase by 2 units - This is the **rate of change** or the **marginal effect** of the independent variable on the dependent variable - The **intercept coefficient** (not given here) would represent the predicted score when study hours = 0 - Option A describes the intercept, not the slope - Option B is incorrect because it mentions percentages, but the coefficient is in units - Option D is incorrect for the same reason - the coefficient represents unit changes, not percentage changes **In simple terms:** If a student studies 1 more hour, their test score is predicted to increase by 2 points on average.
Author: Tanishq Prabhu
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Q.396 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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