Chapter 12, Problem 12.86CRP

State whether the slope of a simple linear regression line is statistically significant, then the correlation will also always be significant?

Describe the five-step process used to calculate the variance in the rate of return for an investment

Use the Financial database from “Excel Databases.xls” on Blackboard.  Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company.  Use Excel to perform a forward selection regression analysis.  Assume a 5% level of significance.  Based on your final model, what is the p-value from the test of the overall model?  Write your answer as a number and round to 3 decimal places.   Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287 32489 16.7 2.76 3.1 1.4 16.1 Arco Chemical 2 3995 4116 6.2 1.14 6.1 2.8 40.4…

To monitor and improve its productivity, a company made an investigation and found out that the factor that affects the productivity the most is the absenteeism. The company data analytics department have collected data about the two variables (Productivity and Absenteeism) for the 12 past years as shown in the table below. Now the purpose of the company is to determine, through regression analysis, whether the productivity is statistically affected by the absenteeism level or not. Year Absenteeism Productivity (in number of absent worker) (in Million AED) 1 204 342 2 352 336 3 154 406 4 206 410 5 422 278 6 530 214 7 750 138 8 482 268 9 374 262 10 120 356 11 188 396 12 634 152 Questions: Construct a scatter diagram for the data about productivity and absenteeism then interpret the possible relationship that can be found. Construct a simple regression model to predict the…

In simple regression, the percentage of variance in Y that can be explained by X is identified by

Can that regression be used to estimate the effect of the national unemployment rate on an individual’s earnings? Explain.

What are some examples of ways in which  linear regression to create a beneficial statistical outcome, in a business setting?

6. another retail merchant who sells face masks spent a total $55 for advertising its product. using the regression model in (4), predict the sale of this merchant.

A researcher uses a regression equation to predict home heating bills (dollar cost), based on home size (square feet). The correlation between predicted bills and home size is 0.70. What is the correct interpretation of this finding? (A) 70% of the variability in home heating bills can be explained by home size. (B) 49% of the variability in home heating bills can be explained by home size. (C) For each added square foot of home size, heating bills increased by 70 cents. (D) For each added square foot of home size, heating bills increased by 49 cents. (E) None of the above.