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Topic 7 Homework (Nonadaptive) Question 9 of 16 (1 point)|Question Attempt: 3 of Unlimited

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Question 9 Suppose we are examining the relationship between scores on a popular standardized test and performance in college. We have chosen a random sample of 45 students just finishing their first year of college, and for each student we've recorded her score on this standardized test (from 400 to 1600) and her grade point average (on a four-point scale) for her first year in college. Letting x denote score on the standardized test and y denote first-year college grade point average, the least-squares regression equation computed from the data is =y+0.90320.0015x. We're now interested in predicting the first-year grade point average of a student who scored 1010 on the standardized test. We're also interested in a prediction interval for this grade point average and a confidence interval for the mean first-year grade point average of students who scored 1010 on the standardized test. We have already computed the following for our data.

mean square error ≈MSE 0.326 ≈+145−1010x2Σ=i145−xix2 0.0376, where x1, x2, ..., x45 denote the standardized test scores in the sample, and x denotes their mean Based on this information, and assuming that the regression assumptions hold, answer the questions below.

(If necessary, consult a list of formulas.)

(a)What is the 99% prediction interval for an individual value for grade point average when the standardized test score is 1010? (Carry your intermediate computations to at least four decimal places, and round your answer to at least two decimal places.)

Lower limit:

Upper limit:

(b)Consider (but do not actually compute) the 99% confidence interval for the mean grade point average when the standardized test score is 1010. How would this confidence interval compare to the prediction interval computed above (assuming that both intervals are computed from the same sample data)?

The confidence interval would be identical to the prediction interval. The confidence interval would be positioned to the right of the prediction interval. The confidence interval would have the same center as, but would be wider than, the prediction interval. The confidence interval would be positioned to the left of the prediction interval. The confidence interval would have the same center as, but would be narrower than, the prediction interval.

(c)For the standardized test score values in this sample, 1310 is more extreme than 1010 is, that is, 1310 is farther from the sample mean standardized test score than 1010 is. How would the 99% prediction interval for the mean grade point average when the standardized test score is 1010 compare to the 99% prediction interval for the mean grade point average when the standardized test score is 1310?

The interval computed from a standardized test score of 1010 would be narrower but have the same center.

The interval computed from a standardized test score of 1010 would be wider but have the same center.

The intervals would be identical.

The interval computed from a standardized test score of 1010 would be narrower and have a different center.

The interval computed from a standardized test score of 1010 would be wider and have a different center.

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Math Problem Analysis

Mathematical Concepts

Regression Analysis
Prediction Intervals
Confidence Intervals
Least-Squares Method
Mean Square Error (MSE)

Formulas

y = 0.9032 + 0.0015x (Least-Squares Regression Equation)
Prediction Interval Formula: ŷ ± t * √[MSE(1 + 1/n + (x - x̄)^2/Σ(x_i - x̄)^2)]
Confidence Interval Formula: ŷ ± t * √[MSE/n]

Theorems

Central Limit Theorem
Properties of t-distribution
Regression Assumptions

Suitable Grade Level

College Level (Statistics, Regression Analysis)