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- A random sample of twelve students were chosen, and their midterm test score (y), as- signment score (x1), and missed classes (x2) were recorded as follows: Midterm Score, y Assignment Score, x1 Classes Missed, x2 85 74 76 90 85 87 94 98 81 91 76 74 65 50 55 65 55 70 65 70 55 70 50 55 5 7 5 2 6 3 2 5 4 3 1 4 (i) What is the fitted multiple linear regression equation of the form yˆ = b0 + b1x1 + b2x2? (ii) From part (i) above, estimate the midterm test score grade for a student who has an assignment score of 60 and missed 4 classes.In order to determine the relationship between the number of units sold of a company's product (yy) in 8 cities with their major competitor's price (x1x1) in dollars, and the number of stores (x2x2) the competitor has in each city, the following data were collected. Units sold CompetitorPrice CompetitorStores 545 35 3 550 35 3 590 40 2 570 39 4 540 40 5 600 40 2 575 46 6 560 39 3 Generate a linear multiple regression output for the data.Interpret the estimated regression coefficient corresponding to the Z variable. Data Salary Education Experience Sex 29.7985 15 3 1 21.8219 4 0 0 22.8978 4 0 0 22.0917 1 1 0 21.8993 5 0 0 22.4829 3 1 1 28.0772 15 0 0 y=salary 23.6292 6 1 1 x1=education level in schooling years 32.3595 0 15 1 x2=experience level in employment level 21.794 1 0 0 d=sex (1 for male,0 for female) 19.8762 3 0 0 Ln(Y) = alpha +beta1X1 +Beta2X2+ Beta3D +Beta4Z +e 21.0253 3 0 0 where z =X2D 24.6323 0 5 1 19.0247 0 0 0 18.8857 0 0 0 21.8552 1 0 0 24.2675 6 1 0 18.7931 0 0 0 18.9276 0 0 0 23.4441 5 1 1 20.8047 2 0 0 18.26 0 0 0 20.6726 0 2 1 21.7815 3 0 0…
- The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. The equation of the regression line is y=1.228x+331.966 Company_1,_x Company_2,_y4093 49293976 48203557 48003411 47323296 46193102 44872859 40482488 38091970 29191625 20021946 2176 Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) A. There is a 99% chance that the predicted new-vehicle sales for Company 2 is between enter your response here and enter your response here thousand, given that the new-vehicle sales for Company 1 is 2600 thousand.…The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. The equation of the regression line is y=1.228x+331.966 Company_1,_x Company_2,_y4093 49293976 48203557 48003411 47323296 46193102 44872859 40482488 38091970 29191625 20021946 2176In order to determine the relationship between the number of units sold of a company's product (yy) in 9 cities with their major competitor's price (x1x1) in dollars, and the number of stores (x2x2) the competitor has in each city, the following data were collected. Units sold CompetitorPrice CompetitorStores 510 35 5 600 44 3 600 41 2 600 40 2 650 45 1 590 40 2 600 41 1 540 40 5 590 40 2 Generate a linear multiple regression output for the data.a) Report the regression coefficients accurate to 3 decimal places:ˆyy^= + x1 + x2b) Report the coefficient of determination accurate to 3 decimal places:R2=
- Using 25 observations on each variable, a computer program generated the following multiple regression model: yhat=69.2+2.87x1+5.81x21.83x3 If the standard errors of the coefficients of the independent variables are, respectively, 1.34, 4.84, and 0.70, can you conclude that the independent variable x1 is needed in the regression model? Let β1, β2, and β3 denote the coefficients of the 3 variables in this model, and use a two-sided hypothesis test and significance level of 0.05 to determine your answer. Carry your intermediate computations to at least three decimal places and round your answers as specified in the table. The null hypothesis: H0: The alternative hypothesis: H1: The type of test statistic: (Choose one)ZtChi squareF The value of the test statistic:(Round to at least two decimal places.) The two critical values at the 0.05 level of significance:(Round to at least two decimal places.) and Can you…The following table displays the mathematics test scores for a random sample ofcollege 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 whoscored 60 on their achievement test. What would their SY16C gradebe? Mathematics test(x) SY16C grades(y)1 39 652 43 783 21 524 64 825 57 926 47 897 28 738 75…Years of Work Experience and number of Job Offers of 10 job-seekers were as follows: Work Exp. 4 2 5 3 7 12 2 5 4 9 No. of Offers 7 1 8 4 13 19 3 11 9 15 a. Fit the regression equation of No. of Job Offers on Years of Work Experience. b. What will be the predicted number of offers for an applicant with 6 years of experience? c. Verify the relationship between the number of job offers and years of work experience using at least two relevant methods
- A seafood-sales manager collected data on the maximum daily temperature, T, and the daily revenue from salmon sales, R, using sales receipts for 30 days selected at random. Using the data, the manager conducted a regression analysis and found the least-squares regression line to be Rˆ=126+2.37T. A hypothesis test was conducted to investigate whether there is a linear relationship between maximum daily temperature and the daily revenue from salmon sales. The standard error for the slope of the regression line is SEb1=0.65. Assuming the conditions for inference have been met, which of the following is closest to the value of the test statistic for the hypothesis test? t=0.274 A t=0.65 B t=1.54 C t=3.65 D t=193.85 EA researcher collected data on the cholesterol level, CC, and the age, AA, of 24 people selected at random. Using the data, the researcher calculated the least-squares regression line to be Cˆ=182+2.2AC^=182+2.2A and the standard error of the slope to be 0.38. If the conditions for inference are met, which of the following is closest to the value of the test statistic to test the hypotheses H0:β=0H0:β=0 versus Ha:β≠0Ha:β≠0 ?The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. The equation of the regression line is y=32.824x+17,659.242. Issues, x 418 475 683 477 492 379 59 51 196 154 Proceeds, y 17,703 28,601 43,966 31,686 36,833 36,916 21,908 10,311 31,407 28,337 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. We can be 95% confident that when there are 646 issues, the proceeds will be between $____ and $____. B. There is a 95% chance…
