# SAS Institute A00-240 SAS Statistical Business Analysis SAS9: Regression and Model Exam Practice Test

Demo: 14 questions
Total 99 questions

## SAS Statistical Business Analysis SAS9: Regression and Model Questions and Answers

Question 1

A marketing campaign will send brochures describing an expensive product to a set of customers. The cost for mailing and production per customer is \$50. The company makes \$500 revenue for each sale.

What is the profit matrix for a typical person in the population?

#### Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 2

A non-contributing predictor variable (Pr > |t| =0.658) is added to an existing multiple linear regression model.

What will be the result?

#### Options:

A.

An increase in R-Square

B.

A decrease in R-Square

C.

A decrease in Mean Square Error

D.

No change in R-Square

Question 3

Refer to the following odds ratio table:

What is a correct interpretation of the estimate?

#### Options:

A.

The odds of the event are 1.142 greater for each one dollar increase in salary.

B.

The odds of the event are 1.142 greater for each one thousand dollar increase in salary.

C.

The probability of the event is 1.142 greater for each one dollar increase in salary.

D.

The probability of the event is 1.142 greater for each one thousand dollar increase in salary.

Question 4

Refer to the lift chart:

At a depth of 0.1, Lift = 3.14. What does this mean?

#### Options:

A.

Selecting the top 10% of the population scored by the model should result in 3.14 times more events than a random draw of 10%.

B.

Selecting the observations with a response probability of at least 10% should result in 3.14 times more events than a random draw of 10%.

C.

Selecting the top 10% of the population scored by the model should result in 3.14 times greater accuracy than a random draw of 10%.

D.

Selecting the observations with a response probability of at least 10% should result in 3.14 times greater accuracy than a random draw of 10%.

Question 5

Suppose training data are oversampled in the event group to make the number of events and non-events roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than 0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).

The following SAS program was used.

What does this program calculate?

#### Options:

A.

Depth

B.

Sensitivity

C.

Specificity

D.

Positive predictive value

Question 6

An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to converge. The analyst prints the summarized data, showing the number of defaulted loans per agent. See the partial output below:

What is the most likely reason that the model fails to converge?

#### Options:

A.

There is quasi-complete separation in the data.

B.

There is collinearity among the predictors.

C.

There are missing values in the data.

D.

There are too many observations in the data.

Question 7

Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by investigating the association between which function of the input variables?

#### Options:

A.

Concordant and discordant pairs of ranked observations

B.

C.

Rank-ordered values of the variables

D.

Weighted sum of chi-square statistics for 2x2 tables

Question 8

Which SAS program will detect collinearity in a multiple regression application?

#### Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 9

An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.

Which statement and option combination will generate these statistics?

#### Options:

A.

Score data=valid1 out=roc;

B.

Score data=valid1 outroc=roc;

C.

mode1 resp(event= '1') = gender region/outroc=roc;

D.

mode1 resp(event"1") = gender region/ out=roc;

Question 10

Refer to the exhibit:

Which SAS program produced the graph?

#### Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 11

Which SAS program will correctly use backward elimination selection criterion within the REG procedure?

#### Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 12

A marketing analyst assessed the effect of web page design (A, B, or C) on customers' intent to purchase an expensive product. The focus group was divided randomly into three sub-groups, each of which was asked to view one of the web pages and then give their intent to purchase on a scale from 0 to 100. The analyst also asked the customers to give their income, which was coded as: I (lowest), II (medium), or III (highest). After analyzing the data, the analyst claimed that there was significant interaction and the webpage design mainly influenced high income people.

Which graph supports the analyst's conclusion?

A)

B)

C)

D)

#### Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 13

Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.

Which statement is true?

#### Options:

A.

The SCORE statement in the LOGISTIC procedure returns only predicted probabilities, whereas the SCORE procedure returns only predicted logits.

B.

The SCORE statement in the LOGISTIC procedure returns only predicted logits, whereas the SCORE procedure returns only predicted probabilities.

C.

Unlike the SCORE procedure, the SCORE statement in the LOGISTIC procedure produces both predicted probabilities and predicted logits.

D.

The SCORE procedure and the SCORE statement in the LOGISTIC procedure produce the same output.

Question 14

Refer to the exhibit:

SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each subset are given.

Based on the AIC statistic, which model is the champion model?

#### Options:

A.

Age Weight RunTime RunPulse MaxPulse

B.

Age Weight RunTime RunPulse RestPulse MaxPulse

C.

RestPulse

D.

RunTime

Demo: 14 questions
Total 99 questions