(Solved): CIS 375 Software Lab #3 : Score for this quiz: 4 out of 4 | This attempt took 34 minutes....

CIS 375
Software Lab #3 
Score for this quiz: 4 out of 4
This attempt took 34 minutes.

Instructions
**Purpose:  To learn about various options to manage missing data, transformation of extreme or unusual input values, and handling non-numeric input variables all for the purposes of creating a Regression predictive model using SAS Enterprise Miner application.**
 
Instructions: In order to finish Software Lab #3,
•    Read Software Tutorial #3 file:  Regressions, perform its respective demonstrations (pp. 4-14 to 4-23; 4-27 to 4-33; 4-35 to 4-43; 4-45 to 4-46; 4-50 to 4-59; and 4-62 to 4-67)
•    Answer the questions in Software Lab #3 (by clicking "Take the Quiz") .
 
Attempt History
LATEST    Attempt 1

 
Question 1
1 / 1 pts
Which of the following is NOT an essential aspect of a Regression model?

• Prediction formula
• Selection of useful input variables
• Selection of useful target variable
• Complexity reduction (via optimization)

 
 
Question 2
1 / 1 pts
In linear regression, the parameter estimates (i.e. coefficients of input variables) are chosen so as to ______ the (squared)error between the observed and predicted target values.

• Increase
• Maximize
• Minimize
• None of the above

  
Question 3
1 / 1 pts
In complete-case-analysis (which is SAS’ default method of handling missing values in most regression tools), all cases are used in the analysis (regardless of any missing values for the input variables). 

• True
• False

 
Question 4
1 / 1 pts
The three sequential selection methods for building regression model (forward, backward, and stepwise) can never lead to the same model for the same dataset.

• True
• False