Refer to the Baseball 2018 data given below, which report information on the 30 Major League Baseball teams for the 2018 season.  Let the number of games won be the dependent variable and the following variables be independent variables:  team batting average, team earned run average (ERA), number of home runs and whether the team plays in the American or National league (American League is 1 and National League is 0). a.  Develop a correlation matrix.   (i)  Which independent variables have strong or weak correlations with the dependent variable.   (ii)  Do you see any problems with multicollinearity?  Explain your answer. b.  Use Excel to determine the multiple regression equation.   (i)  Write out the regression equation and determine its practical application (i.e., interpret the equation).   (ii)  Report and interpret the R-square. c. Conduct a global test on the set of independent variables.  Interpret. d.  Conduct a test of hypothesis on each of the independent variables.  Would you consider deleting any of the variables?   (i)  If so, which ones? (ii)  If so, what is your new equation? e.  Develop a histogram of the residuals from the final regression equation developed in part (d-ii).  Is it reasonable to conclude that the normality assumption has been met?  Why or Why not? f.  Plot the residuals against the fitted values from the final regression equation developed in part (d-ii).  Plot the residuals on the vertical axis and the fitted values on the horizontal axis.  What regression assumption is supported?  Why is it supported?

The following data represents the grades of a sample of 12 students instatistics and economics as followsStatistics grade A C B B D B F F D C B CEconomic Grade B F C B C A C F B B A CCalculate the correlation between the student's grade in Statistics and Economics.What its type and strength.

Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day.   a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? 484 534 Lemon Imports Crash Fatality Rate 229 15.8 266 15.7 359 15.5 15.3 14.8 What are the null and alternative hypotheses? OA. H₂: p=0 H₁: p0 OD. Ho: p*0 H₁: p=0 OC. Ay 17+ 16- ܕ 15 14+ HHHH ▬▬▬▬▬ % do 6 200 400 600 G O D. Aу 17- 16 :|||||||* 15- 14+ 0 H °. C M o do 200 400 600 Q C sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05.

Does a major league baseball team's record during spring training indicate how the team will play during the regular season? Over a six-year period, the correlation coefficient between a team's winning percentage in spring training and its winning percentage in the regular season is . Shown are the winning percentages for the American League teams during a season. Team SpringTraining RegularSeason   Team SpringTraining RegularSeason               Baltimore Orioles 0.409 0.424   Minnesota Twins 0.492 0.542 Boston Red Sox 0.426 0.588   New York Yankees 0.579 0.559 Chicago White Sox 0.411 0.535   Oakland A's 0.690 0.468 Cleveland Indians 0.578 0.492   Seattle Mariners 0.492 0.379 Detroit Tigers 0.578 0.459   Tampa Bay Rays 0.722 0.601 Kansas City Royals 0.540 0.461   Texas Rangers 0.640 0.491 Los Angeles Angels 0.724 0.619   Toronto Blue Jays 0.442 0.533   a. What is the correlation coefficient between the spring training and the regular season winning percentages…

Refer to the Baseball 2018 data given below, which report information on the 30 Major League Baseball teams for the 2018 season.  Let the number of games won be the dependent variable and the following variables be independent variables:  team batting average, team earned run average (ERA), number of home runs and whether the team plays in the American or National league (American League is 1 and National League is 0). a.  Develop a correlation matrix.   (i)  Which independent variables have strong or weak correlations with the dependent variable.   (ii)  Do you see any problems with multicollinearity?  Explain your answer. b.  Use Excel to determine the multiple regression equation.   (i)  Write out the regression equation and determine its practical application (i.e., interpret the equation).   (ii)  Report and interpret the R-square. c. Conduct a global test on the set of independent variables.  Interpret. d.  Conduct a test of hypothesis on each of the independent variables.  Would…

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 229 266 359 480 530 15.9 15.6 15.5 15.3 14.9 Construct a scatterplot. Choose the correct graph below. OA. В. Ос. D. Ay 17- Ay 17- Ay 17- Ay 17- 16- 16- 16- 16- 15- 15- 15- 15- 14+ 14+ 14- 14+ 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient r is (Round to three decimal places as needed.)

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 231 266 359 480 532 15.9 15.7 15.4 15.2 14.8 Ay 17- Ay 17- Ay 17+ Ay 17- 16- 16- 16- 16- 15- 15- 15- 15- X 14- 14+ 14- 14- 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient r is (Round to three decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value is than the significance level 0.05, there sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a…

A national study conducted by a market research firm, evaluated the top technology companies and their reputations. The following shows how 10 technology companies ranked in reputation and how the companies ranked in percentage of respondents who said they would purchase the company's stock. A positive rank correlation is anticipated because it seems reasonable to expect that a company with a higher reputation would have the more desirable stock to purchase. Company Company A Company B Company C Company D Company E Company F Company G Company Hi Company I Company J Ho: Ps ≤0 Ha: Ps > 0 O Ho: P₂ > 0 H₂: Ps = 0 Reputation Stock Purchase O Ho: Ps+0 Ha: Ps = 0 1 O Ho: Ps 20 Ha: Ps <0 2 3 4 5 6 7 8 9 10 3 1 4 2 9 5 10 6 (a) Compute the rank correlation between reputation and stock purchase. (Round your answer to three decimal places.) 's = 0.709 ✓ (b) Test for a significant positive rank correlation. State the null and alternative hypotheses. Ho: P₂ = 0 Ha: Ps0 7 8 Find the value of the…

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 228 264 358 482 531 15.9 15.7 15.5 15.3 14.9