Apple case - Statistical Methods for management decisions
The Apple returns as response to whole market return and IBM return as explanatory variables gives the following regression equation :
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables gives the following regression equation :
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables gives the following regression equation :
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables gives the following regression equation :
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables gives the following regression equation :
a. Apple Return = 0.0048 + 1.31 (Whole Market Return) + 0.22 (IBM Return)
b. Both the variables have a VIF below 10 however after accounting for standard error both do not contain zero hence they are significant variables and explain the variation in apple returns by 21.13 percent which is the value of adjusted R square for the mentioned model.
c. Therefore, the scatter plots appear straight enough for multiple regressions since more than 1 variable is required to estimate Apple Return.
The Apple returns as response to whole market return and IBM return as explanatory variables