The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? *
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- The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the equation of the resulting multiple linear regression? starting_salary = 3008.61 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15000.00 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15001.00 + 41.43*GPA + 84.71*years_of_experience + 37.32*civil_service_ratings starting_salary = 2366.77 + 130.25*GPA + 396.39*years_of_experience + 21.67*civil_service_ratingsWhat percentage of the variability in the amout of fuel used can be explained by the variability in the distance? Determine the regression line for distance and amount of fuel used?Describe about how to place a regression line?
- Bloomberg Intelligence listed 50 companies to watch in 2018 (bloomberg.com/features/companies-to-watch-2018). Twelve of the companies are listed here with their total assets and 12-month sales. Let sales be the dependent variable and total assets the independent variable. Draw a scatter plot Compute the correlation coefficient Determine the regression equation For a company with $100 billion in assets, predict the 12- month sales.NextThe coefficient of determination of a set of data points is 0.98 and the slope of the regression line is -4.28. Determine the linear correlation coefficient of the data.
- Use the Manufacturing database from “Excel Databases.xls” on Blackboard. Use Excel to develop a multiple regression model to predict Cost of Materials by Number of Employees, New Capital Expenditures, Value Added by Manufacture, and End-of-Year Inventories. Use Excel to perform a test of the overall model. Write the test statistic. Round your answer to 2 decimal places SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials Value of Indus. Shipmnts New Cap. Exp. End Yr. Inven. Indus. Grp. 201 433 370 23518 78713 4 1833 3630 1 202 131 83 15724 42774 4 1056 3157 1 203 204 169 24506 27222 4 1405 8732 1 204 100 70 21667 37040 4 1912 3407 1 205 220 137 20712 12030 4 1006 1155 1 206 89 69 12640 13674 3 873 3613 1 207 26 18 4258 19130 3 487 1946 1 208 143 72 35210 33521 4 2011 7199 1 209 171 126 20548 19612 4 1135 3135 1 211 21 15 23442 5557 3 605 5506 2 212 3 2 287 163 1 2 42 2 213 2 2 1508 314 1 15 155 2 214 6 4 624 2622 1 27 554 2 221…Home Price Sales. Where we considered the regression of sale price of a home on size, presence of a pool, lot area, age, number of baths, number of stories, number of garage stalls, presence of traffic, and type of roof based on data for 88 homes in northeast Phoenix. Describe and discuss problems that could have arisen in the collection of the data for this regression analysis.create graph of the two-variable data with a regression line, r, r2, and separate residual plot
- < Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 4 of 6: Find the estimated value of y when x = 61. Round your answer to three decimal places. Table Copy DataConstruct a residual plot.Which criterion is used for deciding which regression line fits best?