b. Using a = 0.05, test for overall significance.There exists significant relationship.c. Did the estimated regression equation provide a good fit to the data? Explain.|, because the R, value is lowerthan 0.50.Yesd. Use the t test and a = 0.05 to test Ho : B1 = 0 and Ho : B2 = 0. Use t table.For B1, the p-value is between 0.01 and 0.02 v, so rejectv Ho : B1 = 0.For B2, the p-value is between 0.05 and 0.10, so do not rejectv Ho : B2 = 0. The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA.ŷ = -1.41 + 0.0235x1 + 0.00486x2where¤1 = high-school grade point average12 = SAT mathemathics scorey = final college grade point averageRound test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations.a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVAdfMSSignificance FRegression1.76209ResidualTotal91.88CoefficientsStandard Errort Statp-valueIntercept-1.40530.4848X10.0234670.0086666X20.004860.001077

Solution: Given information: k= 2 independent variables n= 10 observation Sum of square of…

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and hi ŷ = -1.41 + 0.0235¤1 + 0.00486x2 where I1 = high-school grade point average 12 = SAT mathemathics score y = final college grade point average Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df MS F Significance F Regression 1.76209 Residual Total 9 1.88 Coefficients Standard Error t Stat P-value Intercept -1.4053 0.4848 X1 0.023467 0.0086666 X2 0.00486 0.001077

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and hi ŷ = -1.41 + 0.0235¤1 + 0.00486x2 where I1 = high-school grade point average 12 = SAT mathemathics score y = final college grade point average Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df MS F Significance F Regression 1.76209 Residual Total 9 1.88 Coefficients Standard Error t Stat P-value Intercept -1.4053 0.4848 X1 0.023467 0.0086666 X2 0.00486 0.001077

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 40RE: For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina...

See similar textbooks

Similar questions

For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.
For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. #1)A high-school average 84 corresponds to x1 = 84 and a score of 535 on the SAT mathematics test corresponds to x2 = 535. Substitute these values into the estimated regression equation to find the final college GPA, rounding the result to two decimal places. GPA = −1.39 + 0.0234x1 + 0.00482x2 = -1.39 +0.0234 (_____________) + 0.00482 (535) = __________________
The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. (a) Interpret the coefficients in this estimated regression equation. (b) Predict the final college GPA for a student who has a high-school average of 84 and a score of 535 on the SAT mathematics test.
The admissions officer fro Clearwater college developed the following estimated regression equation relating the final college GPA to the students SAT mathematics score and high school GPA. Y = -1.4053 + 0.235x1 + .0049x2 X1 = high score grade point average X2 = SAT mathematics score Y= final college grade point average A. completethe missing entries in this excel regression tool output. Enter negative values as a negative numbers. Regression Missing Significance F ? And Intercept P value ? Thank you
The following data on price ($) and the overall score for 6 stereo headphones that were tested by Consumer Reports were as follows. The estimated regression equation for these data is y = 26.239 + 0.309x. (NEED ANSWERS FOR A and C)
The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. #1) The given regression equation follows where x1 is the high-school grade point average, x2 is the SAT mathematics score, and y is the final college grade point average. ŷ = −1.39 + 0.0234x1 + 0.00482x2 We are to predict the final college GPA for a student who has a high-school average of 84 and scored 535 on the SAT mathematics test. Thus, the corresponding values to substitute into the regression equation are x1 = and x2 = .
The personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to his or her length of service and wage rate.y-hat = 14.4 - 8.69x1 +13.5x2 where: x1 = length of service (years)x2 = wage rate (dollars)y = job satisfaction test score (higher scoresindicate greater job satisfaction)Round your answers to 2 decimal places. a. Interpret the coefficients in this estimated regression equation. If the wage rate does not change, a one-year increase in length of service is associated with - Select your answer - in job satisfaction score by _______________ units. If the length of service does not change, a dollar increase in wage results in - Select your answer - in job satisfaction score by _______________ units. b. Predict the job satisfaction test score for an employee who has four years of service and makes $6.50 per hour. _________________
An admissions counselor is looking to determine an equation that relates the graduate grade point averages of students who are newly admitted to an academic program with their undergraduate GPA, their GRE scores, and the number of years they have been out of college. What is the correct format for a multiple regression equation? Select the correct answer below: yˆ=b0+b1x1+b2x2+b3x3 yˆ=b1x1+b2x2+b3x3 yˆ=b0+b1x1+b2x2+b3x3+b4x4 yˆ=b0+b1x1+b2x2
A group of students looked to see if there was a linear relationship between the number of hours spent on social media per day (x) and number of sit-ups a person can do in one minute (y).After gathering data from their class, the students ran LinReg regression on their calculator, which gave them: y = ax + b a = -1.794 b = 36.334 Based on that result, how many sit-ups would you expect a person who spends 6 hours of on social media to be able to do in one minute? Round to the nearest whole number of sit-ups.
The personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to length of service and wage rate. ŷ = 14.4 − 8.69x1 + 13.52x2 where x1 = length of service (years) x2 = wage rate (dollars) y = job satisfaction test score (higher scores indicate greater job satisfaction). #1) Find the value of the test statistic. (Round your answer to two decimal places.) F = Find the p-value. (Round your answer to three decimal places.) p-value = #2)Did the estimated regression equation provide a good fit to the data? Explain. (Round your answers to two decimal places.) Since R2 = Ra2 = #3) Find the value of the test statistic for ?2. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value =
The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade be