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Answer: a) Identify response and predictors from the R table. Write the linear regression model

Answer: a) Identify response and predictors from the R table. Write the linear regression model

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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c) If a student scored 82 on the admissions test and was 17 years old at the time of application, what would be your prediction of their GPA? ( d) If another student scored 97 on the admissions test and was 19 years old at the time of application, what would be your prediction of their GPA? Senior
Transcribed Image Text:c) If a student scored 82 on the admissions test and was 17 years old at the time of application, what would be your prediction of their GPA? ( d) If another student scored 97 on the admissions test and was 19 years old at the time of application, what would be your prediction of their GPA? Senior
Question 22 After building the regression model we receive the results shown here: Call: 1m (formula = gpa - test + age) Residuals: 1 test age Answer: 8 0.00307 2 3 4 -0.16842 0.02851 -0.07939 0.13158 0.07456 0.12807 -0.11798 5 6 Coefficients: oplica Estimate Std. Error t value Pr (>|t|) (Intercept) -1.900439 0.984841 -1.930 0.11153 0.025702 0.004937 5.206 0.00345 ** 0.182456 0.064412 2.833 0.03656 * Signif. codes: 01*** 0.001 ** 0.01 0.05. 0.11 Residual standard error: 0.1332 on 5 degrees of freedom Multiple R-squared: 0.9328, Adjusted R-squared: 0.9059 F-statistic: 34.71 on 2 and 5 DF, p-value: 0.00117 7 a) Identify response and predictors from the R table. Write the linear regression model b) According to this model, what impact would a single point increase in admissions test score have on the prediction of a student's GPA? How about a single year increase in age?
Transcribed Image Text:Question 22 After building the regression model we receive the results shown here: Call: 1m (formula = gpa - test + age) Residuals: 1 test age Answer: 8 0.00307 2 3 4 -0.16842 0.02851 -0.07939 0.13158 0.07456 0.12807 -0.11798 5 6 Coefficients: oplica Estimate Std. Error t value Pr (>|t|) (Intercept) -1.900439 0.984841 -1.930 0.11153 0.025702 0.004937 5.206 0.00345 ** 0.182456 0.064412 2.833 0.03656 * Signif. codes: 01*** 0.001 ** 0.01 0.05. 0.11 Residual standard error: 0.1332 on 5 degrees of freedom Multiple R-squared: 0.9328, Adjusted R-squared: 0.9059 F-statistic: 34.71 on 2 and 5 DF, p-value: 0.00117 7 a) Identify response and predictors from the R table. Write the linear regression model b) According to this model, what impact would a single point increase in admissions test score have on the prediction of a student's GPA? How about a single year increase in age?
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