Star, Incorporated, used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R R Square Observations Standard Error T Stat 61,315 Intercept Production (X) 0.9270 What total cost would Star predict for a month in which production is 2,000 units? Multiple Choice $198,535 O $175.395 0.9777 0.9539 30 $63,369 Coefficients 174,715 11.91 2.85 12.85 P-Value 0.021 0.000
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4According to human capital theory, a person’s earning is linked to her level of education – there is a relationship between workers income and years of education. Using data from the Labour Force Survey, a researcher found the following regression results for earnings on intercept, years of education, experience, and experience squared: Earnings = 5.24 + 0.035 educ + 0.165 exper – 0.003 exper2 (2.45) (0.012) (0.031) (0.001) Construct a 95% confidence interval for the effect of years of education on earnings ? 2. Consider an individual with 8 years of experience. What would you expect to be the return to two (2) additional years of experience (the effect on earnings)? 3. According to economic theory,…A researcher is interested in predicting the number of homessold from years in business as a real estate agent and their level of education. Use the realestate.xlsx data to respond to the following: what type of regression analysis would you conduct, simple linear regression or multiple linear regression? Why? I WAS GIVEN AN ANSWER SEE PICTURE FOR THE ANSWER I WAS GIVEN. i would like it explained though
- A study investigated how the content of vitamin A in carrots is affected by the time being cooked. In this example: X represents the amount of time, in minutes, that the carrot slices were cooked Y represents the content of vitamin A (in milligrams) in the carrot slices The least-squares regression equation for this relationship is: Y = 23.4 – 0.55X In this study, which variable is the explanatory variable?what % of the variation is ( height, or head circumference) explained by the least-squares regression model. (Round to one decimal place as needed.)Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept 3.996 1.161268 3.441065 0.004885 x 0.358 0.102397 3.496205 0.004413 Source df SS MS F Se = 0.898 Regression 1 9.858769 9.858769 12.22345 r2 = 0.526341 Residual 11 8.872 0.806545 Total 12 18.73077 Using a = 0.05, Louis should ________________.
- A city boy started an orchard in his native village. He consulted an agricultural extension officer and used fertilizer and insecticide per his advice. He wanted to estimate the contribution of fertilizer and insecticide on output and decided to use regression analysis. Following table gives the MINITAB output. Regression Analysis: Mango Output versus fertilizer and insecticide. Predictor сoef SE Coef Constant 75.6752 10.0451 X Fertilizer 2.310 1.96 Insecticide 4.2150 2.015 X X S= 13.1459 R-Sgr = 89.1% R-sgr (Adjusted) = 85.64 Analysis of Variance Source DF SS MS Regression 2 20,200.35 X Residual Error 37 140.50 Total a) Fill-up the blanks as marked. b) Can you conclude that application of fertilizers have increased mango output significantly at 5% level of significance. c) Construct a 95% confidence interval for Fertilizer coefficient. d) What is the value coefficient of multiple determinations. Why is the adjusted coefficient of multiple determination is less than the coefficient of…A researcher is interested in predicting the number of homessold from years in business as a real estate agent and their level of education. Use the realestate.xlsx data to respond to the following: what type of regression analysis would you conduct, simple linear regression or multiple linear regression? Why?A large city hospital conducted a study to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employees. A sample of 10 employees was selected and the following data were collected. Develop a scatter diagram for these data. Does a linear relationship appear reasonable? Explain. Develop the least squares estimated regression equation that relates the distance to work to the number of days absent. Predict the number of days absent for an employee that lives 5 miles from the hospital.
- The following MINITAB output is for a multiple regression. Something went wrong with the printer, so some of the numbers are missing. Fill in the missing numbers. Predictor Coef SE Coef (a)0.086 (b) 4.300.005 (c) 0.3944-0.620.560 Constant -0.58762 0.2873 X1 1.5102 X2 (d)0.003 R-Sq(adj) = 85.3% ХЗ 1.8233 0.3867 R-Sq = 90.2% 0.869 Analysis of Variance SS MS F P 3 41.76 (e) (f) 0.000 (g) 0.76 (h) 46.30 Source DF Regression Residual Error 6. TotalUse least squares regression to fit a line to the table data below.Sage, Incorporated, used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R R Square Observations Intercept Production 0.9800 0.9604 20 Coefficients 21,239 3.29 a. Total Fixed Cost b. Variable Cost c. Total Cost Standard Error 6,922 0.5309 (X) Required: a. What is Sage's total fixed cost? b. What is Sage's variable cost per unit? Note: Round your answer to 2 decimal places. c. What total cost would Sage predict for a month in which it sold 12,000 units? Note: Round your intermediate calculations to 2 decimal places. T Stat P-Value 3.07 0.007 6.20 0.000 per unit