Reference no: EM133019803

1. Do not exclude variables even if they are not significant

Hint:Analyze/Fit Model

Use the Validation column provided in the data file for this analysis (where the data set is partitioned into Training and Validation (70/30) sets) to build this multiple LR model. Build a Logistic Regression model with Status as dependent variable; Quote, Time to Delivery, and Part Type as independent variables; and Validation column for Validation in the dialog box. . Save Script to data table as Q3 and answer the following questions. ( )

a. Is the overall model significant? Which variables - Quote, Time to Delivery and Part Type are significant?

i. Overall Model: Not significant, Quote: Significant, Time to Delivery: Not Significant, Part Type: Significant

ii. Overall Model: Significant, Quote: Significant, Time to Delivery: Not Significant, Part Type: Significant

iii. Overall Model: Not significant, Quote: Not significant, Time to Delivery: Significant, Part Type: Significant

iv. Overall Model: Significant, Quote: Not significant, Time to Delivery: Significant, Part Type: Significant

b. Copy and paste your confusion matrices for both Training and Validation sets below? Calculate the Accuracy rates for Training & Validation Sets and answer the following questions:

i. Accuracy rate for Training set is 58.18%

ii. Accuracy rate for Validation set is 58.79%

c. (Odds ratio between OE and AM parts) The Part Type OE is ____________ as likely to result in losing the contract when compared to AM.

i. 1.9041239

ii. 0.5251759

iii. 0.964881

iv. 1.017168

d. What is the probability of losing when Quote price is $2000, Time to Delivery is 25 days and Part Type is AM (use the Prediction Profiler to answer this question)?

i. 0.585

ii. 0.415

iii. 0.575

iv. 0.425

a. What is the probability of Status = Won, if Quote = $10,000; Time to Delivery = 50 days; and Part Type = AM (use the Prediction Profiler to answer this question)?

i. .47

ii. .52

iii. .32

iv. .68

b. Which Independent Variable contributes the most to the outcome variable Status?

i. Quote, because _________________________

ii. Time to Delivery, because it is significant with alpha less than 0.05, having highest log worth = 5.291 and high chi square value =17.97

iii. Part Type, because __________________

c. There is room for more predictors in the model. (Hint: if you don't remember how to answer this question, please refer to the class notes and the JMP tutorial)

i. True, because __ _________________________

ii. False, because ___________________________