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SAT Math scores Is there a relationship between the percent of high school graduates in each state who took the SAT and the state’s mean SAT Math score? Here is a residual plot from a linear regression analysis that used data from all 50states in a recent year. Explain why the conditions for performing inference about the slope β1 of the population regression line are not met.

Short Answer

Expert verified

The relationship between mean SAT score and percent taking is linear.

Step by step solution

01

Given information:

We have been given that:

Residual plot from a linear regression analysis that used data from all50 states in a recent year

02

Explanation:

A residual plot shows "Percent of high school graduates taking the SAT" along the horizontal axis in increments of 10and "Residual" along the vertical axis in increments of 25. Horizontal line is drawn at 0on vertical axis across the graph. Dots are scattered across the graph on either side of the line and on the vertical axis between negative 30and 35. A dot is shown before 20on the horizontal axis and between negative 70on the vertical axis.

Explain how the residual plot indicates whether or not the Linear condition for performing slope inference is met.

The variability of the residuals in the vertical direction is roughly the same from the smallest to the largest -value, indicating that the relationship between mean SAT score and percent taking is not linear.

The residual plot shows a clear curvature, confirming that the relationship between mean SAT score and percent taking is linear.

The residual plot has significant curvature, indicating that the relationship between mean SAT score and percent taking is not linear.

The residual plot has significant curvature, indicating that the relationship between mean SAT score and residual values is not linear.

The variability of the residuals in the vertical direction is roughly the same from the smallest to the largest -value, confirming that the relationship between mean SAT score and percent taking is linear.

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Most popular questions from this chapter

A scatterplot of yversus xshows a positive, nonlinear association. Two different transformations are attempted to try to linearize the association: using the logarithm of the y-values and using the square root of the y-values. Two least-squares regression lines are calculated, one that uses x to predict log(y) and the other that uses x to predict y. Which of the following would be the best reason to prefer the least-squares regression line that uses x to predict log(y)?

a. The value of r2is smaller.

b. The standard deviation of the residuals is smaller.

c. The slope is greater.

d. The residual plot has more random scatter.

e. The distribution of residuals is more Normal.

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a. Transform both variables using logarithms. Then calculate and state the least-squares regression line using the transformed variables.

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T12.3 Inference about the slope β1 of a least-squares regression line is based on which of
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b. The standard Normal distribution
c. The chi-square distribution with n1 degrees of freedom
d. The t distribution with n-2 degrees of freedom
e. The Normal distribution with mean μ and standard deviation σ.

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