Supply the answers to the incorrect answers. Please write the question # and the question part (ex. 1a, 1b, 2a, 2b, etc...).

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Given are five observations for two variables, @ and y. 1 2 3 4 5 yi 3 7 7 12 15 The estimated regression equation for these data is y = 0.1 + 2.9x. a. Compute SSE, SST, and SSR using the following equations (to 1 decimal). SSE = > (yi - 92)2 SST = _ ( yi - 3)2 SSR = [ ( y: - J) 2 SSE SST SSR b. Compute the coefficient of determination r2 (to 3 decimals). Does this least squares line provide a good fit? Yes, the least squares line provides a very good fit c. Compute the sample correlation coefficient (to 4 decimals).Given are five observations for two variables, a: and g. 1-1. 4 6 14 17 19 yi 50 56 48 12 13 The estimated regression equation for these data is 3] = 68.77 2.7592. 3. Compute SSE, SST, and SSR. SSE 0 (to 2 decimals) SST 0 (to 2 decimals) SSR 0 (to 2 decimals) b. Compute the coefficient of determination 1'2. Comment on the goodness of fit. 0 (to 3 decimals) The least squares line provided an wfit; 0 % of the variability in y has been explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. 0 (to 3 decimals) Given are five observations for two variables, a and y. Excel File: data14-17.xIsx 2 6 9 13 20 yi 7 18 9 26 23 The estimated regression equation for these data is y = 7.6 + 0.9x . Compute SSE, SST, and SSR (to 1 decimal). SSE SST SSR What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? % What is the value of the sample correlation coefficient (to 3 decimals)?A B C D E F G H I J K L IN 6 13 20 N Vi 7 18 9 26 23 - W 12 13 14 15 16 17 18 19 20 21 22 23The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is 3} = 25.2769 + 0.2972m , where a: 2 price ($) and y 2 overall score. Brand Price ($) Score Bose 180 76 Scullcandy 160 71 Koss 95 62 Phillips/O'Neill 60 57 Denon 60 40 JVC 45 24 a. Compute SST, SSH, and SSE (to 3 decimals). SST = 0 SSR = 0 SSE = e b. Compute the coefficient of determination 1'2 (to 3 decimals). ,2 = 0 Comment on the goodness of fit. Hint: If T2 is greater than 0.70, the estimated regression equation provides a good fit. The least squares line K20 a good fit as \\'0 proportion of the variability in g has been explained by the least squares line. c. What is the value of the sample correlation coefficient (to 3 decimals)? 0 rxy A sales manager collected the following data on y = annual sales and a: = years of experience. The estimated regression equation for these data is Q = 80 + 4.7:. Click on the datafile logo to reference the data. DATAr Years of Annual Sales Salesperson Experience ($10005) 1 1 80 2 3 97 3 4 92 4 4 102 5 6 103 6 8 111 7 10 119 8 10 123 9 11 117 10 13 136 a. Compute SST, SSR, and SSE. SSE 0 SST 0 SSR 0 2 b. Compute the coefficient of determination r . 0% Comment on the goodness of fit. The least squares line provides a very good fit v w c. What is the value of the sample correlation coefficient (to 2 decimals)? 0 \fBicycling, the world's leading cycling magazine, reviews hundreds of bicycles throughout the year. Their "Road-Race" category contains reviews of bikes used by riders primarily interested in racing. One of the most important factors in selecting a bike for racing is the weight of the bike. The following data show the weight (pounds) and price ($) for 10 racing bikes reviewed by the magazine (Bicycling website). DATA file Brand Weight Price ($) FELT F5 17.8 2100 PINARELLO Paris 16.1 6250 ORBEA Orca GDR 14.9 8370 EDDY MERCKX EMX-7 15.9 6200 BH RC1 Ultegra 17.2 4000 BH Ultralight 386 13.1 8600 CERVELO S5 Team 16.2 6000 GIANT TCR Advanced 2 17.1 2580 WILIER TRIESTINA Gran Turismo 17.6 3400 SPECIALIZED S-Works Amira SL4 14.1 8000 a. Use the data to develop an estimated regression equation that could be used to estimate the price for a bike given the weight. If required, enter negative values as negative numbers. Price = + * Weight (to whole number) b. Compute r2 (to 3 decimals) Did the estimated regression equation provide a good fit? The estimated regression equation provided a very good V fit. c. Predict the price for a bike that weighs 15 pounds. (to whole number)\fAn important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 3,700 450 4,700 550 5,100 600 5,600 700 6,100 750 6,700 3. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Compute b1 and be (to 1 decimal). Do not round intermediate calculations. b1 110 Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations. A y= + :1: b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations. $ c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report 7'2 between 0 and 1. 1'22 What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations. % d. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)? Do not round intermediate calculations. $