Data on advertising expenditures and revenue (in thousands of dollars) for the Four Seasons Restaurant follow. Advertising Expenditures Revenue 20 2 33 4 45 6 40 10 53 14 54 20 55 a. Let equal advertising expenditures and y equal revenue. Use the method of least squares to develop a straight line approximation of the relationship between the two variables (to 2 decimals). + b. Test whether revenue and advertising expenditures are related at a 0.05 level of significance. Compute the following (to 2 decimals). SSE SST SSR MSR MSE
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- Data on advertising expenditures and revenue (in thousands of dollars) for the Four Seasons Restaurant follow. Advertising Expenditures Revenue 1 19 2 32 4 45 6 41 10 52 14 53 20 54 a. Let x equal advertising expenditures and y equal revenue. Use the method of least squares to develop a straight line approximation of the relationship between the two variables (to 2 decimals). y= + x b. Test whether revenue and advertising expenditures are related at a 0.05 level of significance. Compute the following (to 2 decimals). SSE SST SSR MSR MSE Compute the F test statistic (to 2 decimals).while using the t-test to test whether regression is significant, in the model yi=β0+β1xi+εiyi=β0+β1xi+εi, what is the calculated student-t statistics (H0:β1=0H0:β1=0 versus H1:β1≠0H1:β1≠0). Calculate the least squares estimates of β0β0 in the model yi=β0+β1xi+εi Calculate the sum of squares of y denoted by Syy , the sum of squares of x denoted by Sxx and sum of squares (products) of x and y denoted by Sxy while using analysis of variance (ANOVA) to test whether regression is significant, in the model yi=β0+β1xi+εiyi=β0+β1xi+εi, what is the residual or error sum of squares due to regression, SSE. kindly help with this questionFor a sample of 15 rural counties in one state, a researcher has collected information about the rate of deaths due to traffic accidents per 1,000,000 population and the percentage of the population which consists of males, age 16 to 25. For these variables, find the least squares regression line and compute r and r squared. Write a sentence or two summarizing and explaining your results. RATE OF % OF POPULATION County Traffic Deaths Young Males County Traffic Deaths Young Males A 15 4 B 16 5 C 22 10 D 23 9 E 20 8 F 25 11 G 18 2 H 15 6 I 19 12 J 10 3 K 9 2 L 18 15 M 15 9 N 24 16 O 9 3
- The following data show the number of class sessions missed during a semester of SOC221 and the final grade for a sample of 8 students selected at random. Number of Sessions Missed Final Grade (x) (y) 0 96 2 88 12 68 6 91 8…Show that Var(Y − a − bX) ≤ Var(Y) where a and b are the intercept and the slope of the linear least-squares model.Records at a company for the last 55 years show the following relationship between the units sold (in thousands) and the price of a product. Sales Price (y) $8.80$8.80 $8.00$8.00 $7.50$7.50 $6.90$6.90 $6.20$6.20 Units Sold (x) (in thousands) 3.63.6 5.75.7 6.46.4 8.58.5 9.59.5 Find the least-squares regression line for the price in terms of thousands of units sold. Round the coefficients to three decimal places. Estimate the price that should be charged in order to sell 10,00010,000 units. Round your answer to the nearest cent.
- For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: x 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 75.4 71.3 58.1 48.5 74.1 73.7 67.7 59.5 58.0 48.6 (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)y = Interpret the slope. A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope.A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope. (b) Calculate the coefficient of determination.…For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: x 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 74.6 71.1 57.5 48.4 74.0 72.9 68.3 59.8 57.6 48.0 (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)y = −32.6485+0.9943x Interpret the slope. A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope. (b) Calculate the coefficient of…The table shows the numbers of master’s degrees y (in thousands) conferred in the United States from 2009 through 2012. Find the least squares regression line for the data. Then use the model to predict the number of degrees conferred in 2019. Let t represent the year, with t = 9 corresponding to 2009. (Source: U.S. National Center for Education Statistics)
- Records at a company for the last 5 years show the following relationship between the units sold (in thousands) and the price of a product. Sales Price (y) $8.80 $8.00 $7.50 $6.90 $6.20 Units Sold (x) (in thousands) 3.7 5.5 6.7 7.8 9.3 a. Find the least-squares regression line for the price in terms of thousands of units sold. Round the coefficients to three decimal places. b. Estimate the price that should be charged in order to sell 10,000 units. Round your answer to the nearest cent.In order to study the relationship between age and length of time that a smoker has been smoking, the following data were collected. x= age of a smoker y= years since he or she started smoking. x = y= 26 8 32 9 27 7 24 6 34 10 20 4 Compute the coorelation and find the least squares line.The peanut crop was harvested from five fields of various area. The following data are the mass of the crop from each field y (in kilograms) and the field area x (in hectares). y 7360 15760 13690 20080 12910 x 2.34 3.92 3.35 4.56 2.56 Round your intermediate answers to four decimal places (e.g. 98.7654).(a) Fit the simple linear regression model using the method of least squares. Find the estimate of σ2.Round your answer to the nearest integer (e.g. 9876).σ^2= (b) What change in the mean mass is expected when the field area changes by 1 hectare?Round your answer to the nearest integer (e.g. 9876).β^1= (c) Calculate the fitted value of y corresponding to x=3.92. Find the corresponding residual.Round your answer to the nearest integer (e.g. 9876).y^= Round your answer to the nearest integer (e.g. 9876).e= (d) Estimate the mean mass of the crop harvested from 4.5 hectares.Round your answer to the nearest integer (e.g. 9876).y^=