The distance between the Y value in the data and the predicted Y value from the regression equation is known as the residual. What is the value for the sum of the squared residuals?   a. ​SSresidual  =  r2(SSX)   b. ​SSresidual  =  r2(SSY)   c. ​SSresidual  =  (1 – r2)(SSX)   d. ​SSresidual  =  (1 – r2)(SSY)

The manager of a car dealership wants to predict the relationship between number of sales persons and the number of cars sold. He collects some data to develop a regression model, which is given below         Week Number of cars sold Number of salespersons 1 80 6 2 90 8 3 48 4 4 55 5 5 60 7 6 75 9 7 100 11 8 70 6 9 65 7 10 98 10   (i) Run a regression analysis which explains the number of cars sold in terms of number of salespersons, and estimate the regression line                                                                              (ii) Interpret the regression coefficient, and determine the significance of the regression coefficient                                                                                                                                             (iii) Interpret the overall model fit…

The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. The equation of the regression line is y = 46.360x + 18,657.31. Complete parts a and b 412 455 Issues, x. Proceeds, 17,955 27,527 43,371 30,734 66,292 65,063 22,264 11,783 31,116 27,537 685 476 483 384 54 75 194 170 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in proceeds that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is explained by the variation in issues. The coefficient of determination is the fraction of the variation proceeds that can be explained by the variation in issues. The remaining fraction of the variation is unexplained and is due to other factors or to sampling error. (b)…

The estimated regression line: a.    does not change the sum of squared residuals.b.    maximizes the sum of squared residuals.c.    minimizes the sum of squared residuals.d.    sometimes maximizes and sometimes minimizes the sum of squared residuals.can you also explain the answer, please

in multiple regression analysis, a residual is the difference between the value of a dependent variable and its corresponding independents variable value? True or false?

The sweetness, y, of the fruit is supposed to be related to the average daily sunshine hours, x. The following data shows the sweetness of the same type of fruit at different locations (sunshine hours). Fit the data to a simple linear regression model. x: 5, 6, 7, 6, 6, 8, 7, 5. y: 9, 10, 10, 11, 12, 13, 12, 8. Predict the true mean sweetness for average daily hours of 8 hours, and calculate the residual for average daily sunshine hours of 8 hours.

Explain Which of the following statements are true about studentized residuals? They are the deviations of the observed values from the fitted line. They're closely related to the errors of prediction of the observation. Large studentized residuals will lead to large influence on the regression model in all circumstances

If a correlation isr= 0.00, then SP = 0 and the regression equation is O Ý =X +0 O Ý =X + X O Ý =0 + X O Ý =Ÿ + 0

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

The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be 0.36 - 0.36 0.6 0.13 O 0.6 or + 0.6