A. Fit a logistic regression model to predict the probability of successful completion of the MBA program based on undergraduate grade point average and GMAT score.
b. Explain the meaning of the regression coefficients for the model fit in (a).

c. Predict the probability of successful completion of the program for a student with an undergraduate grade point average of 3.25 and a GMAT score of 600.
d. At the .05 level of significance, is there evidence that a logistic regression model that uses undergraduate grade point average and GMAT score to predict probability of success in the MBA program is a good-fitting model?
e. At the .05 level of significance, is there evidence that undergraduate grade point average and GMAT score each makes a significant contribution to the logistic regression model?

a. Fit a logistic regression model to predict the probability of successful completion of the MBA program based on undergraduate grade point average and GMAT score.
b. Explain the meaning of the regression coefficients for the model fit in (a).

c. Predict the probability of successful completion of the program for a student with an undergraduate grade point average of 3.25 and a GMAT score of 600.
d. At the .05 level of significance, is there evidence that a logistic regression model that uses undergraduate grade point average and GMAT score to predict probability of success in the MBA program is a good-fitting model?
e. At the .05 level of significance, is there evidence that undergraduate grade point average and GMAT score each makes a significant contribution to the logistic regression model?

Simple Linear Regression and Multiple Regression.
I'd like to ask whether you think multiple regression (the use of more IV's) is always better than simple regression? Why or why not?
What problems may exist with multiple regression that are not an issue for simple linear regression?

1)Given the regression equation: Y = 1.3479 + 0.3978 X, what is the fitted value (orY ? ) if X = -3?
2) Calculate bo, b1 for the information provide below
X Y
-2 9
0 5
-0.5 7
1 100

From a management policy perspective, which regression result is the most useful?
a regression equation that passes the F-test.
a regression equation whose explanatory variables all passed the t-test.
a regression equation that has the highest R2.
a regression equation that has the least n

Ho: Total home cost increases with additional square feet
Ha: Total home cost does not increase with additional square feet
Define bivariate regression, discuss fitted regression and using regression for prediction purposes.
Please see attached data and help me to understand what each section means.

A)Show the scatter diagram and explain whether it displays a linear relationship.
b)Enter the regression equation
c)Interpret the coefficients in the regression.
d)Predict the amount of ice cream sold for one day with a temperature of 950C.