# (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