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A00-240 Sample Questions Answers

Questions 4

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.

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Questions 5

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.

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Questions 6

Refer to the REG procedure output:

The Intercept estimate is interpreted as:

Options:

A.

The predicted value of the response when all the predictors are at their current values.

B.

The predicted value of the response when all predictors are at their means.

C.

The predicted value of the response when all predictors = 0.

D.

The predicted value of the response when all predictors are at their minimum values.

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Questions 7

Refer to the REG procedure output:

Click on the calculator button to display a calculator if needed.

Options:

A.

0.4115

B.

0.6994

C.

0.5884

D.

0.1372

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Questions 8

Refer to the exhibit.

Output from a multiple linear regression analysis is shown.

What is the most appropriate statement concerning collinearity between the input variables?

Options:

A.

Collinearity is a problem since all variance inflation values are less than 10.

B.

Collinearity is not a problem since all variance inflation values are less than 10.

C.

Collinearity is not a problem since all Pr>|t| values are less than 0.05.

D.

Collinearity is a problem since all Pr>|t| values are less than 0.05.

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Questions 9

What is a benefit to performing data cleansing (imputation, transformations, etc.) on data after partitioning the data for honest assessment as opposed to performing the data cleansing prior to partitioning the data?

Options:

A.

It makes inference on the model possible.

B.

It is computationally easier and requires less time.

C.

It omits the training (and test) data sets from the benefits of the cleansing methods.

D.

It allows for the determination of the effectiveness of the cleansing method.

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Questions 10

The standard form of a linear regression model is:

Which statement best summarizes the assumptions placed on the errors?

Options:

A.

The errors are correlated, normally distributed with constant mean and zero variance.

B.

The errors are correlated, normally distributed with zero mean and constant variance.

C.

The errors are independent, normally distributed with constant mean and zero variance.

D.

The errors are independent, normally distributed with zero mean and constant variance.

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Questions 11

Refer to the lift chart:

What does the reference line at lift = 1 corresponds to?

Options:

A.

The predicted lift for the best 50% of validation data cases

B.

The predicted lift if the entire population is scored as event cases

C.

The predicted lift if none of the population are scored as event cases

D.

The predicted lift if 50% of the population are randomly scored as event cases

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Questions 12

Select the equivalent LOGISTIC procedure model statements. (Choose two.)

Options:

A.

Mode1 Purchase * Gender Age Region;

B.

Mode1 Purchase * Gender | Age | Region;

C.

Mode1 Purchase * Gender|Age|Region @1;

D.

Mode1 Purchase * Gender|Age|Region @2;

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Questions 13

Refer to the exhibit.

Given alpha=0.02, which conclusion is justified regarding percentage of body fat, comparing small (S), medium (M), and large (L) wrist sizes?

Options:

A.

Medium wrist size is significantly different than small wrist size.

B.

Large wrist size is significantly different than medium wrist size.

C.

Large wrist size is significantly different than small wrist size.

D.

There is no significant difference due to wrist size.

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Questions 14

The question will ask you to provide a missing statement. Given the following SAS program:

Which SAS statement will complete the program to correctly score the data set NEW_DATA?

Options:

A.

Score data data=MYDIR.NEW_DATA out=scores;

B.

Score data data=MYDIR.NEW_DATA output=scores;

C.

Score data=HYDIR.NEU_DATA output=scores;

D.

Score data=MYDIR, NEW DATA out=scores;

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Questions 15

Refer to the REG procedure output:

Calculate the coefficient of determination, R-Square.

Enter your numeric answer in the space below. Round to 4 decimal places (example: n.nnnn).

Options:

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Questions 16

The PROC LOGISTIC options SELECTION=SCORE and BEST=2 are used in a MODEL statement to generate a series of predictive models. The models are assigned numbers in order from 1 to 99 reflecting the fact that there are 50 candidate input variables. Results from the collection of derived models are used to generate the following plot of overall average profit by model number. Results are restricted to models with at least 9 inputs and at most 40 inputs.

The maximum value for the training data occurs for model number 46, and the maximum value for the validation data occurs for model number 43.

If you base model selection solely on overall average profit, what is the correct choice?

Options:

A.

Select model 46

B.

Select model 43

C.

Select model 45

D.

Select model 21

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Questions 17

Given the following GLM procedure output:

Which statement is correct at an alpha level of 0.05?

Options:

A.

School*Gender should be removed because it is non-significant.

B.

Gender should be removed because it is non-significant.

C.

School should be removed because it is significant.

D.

Gender should not be removed due to its involvement in the significant interaction.

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Questions 18

This question will ask you to provide a missing option.

Complete the following syntax to test the homogeneity of variance assumption in the GLM procedure:

means Region / =levene ;

Options:

A.

test

B.

adjust

C.

var

D.

hovtest

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Questions 19

A linear model has the following characteristics:

  • A dependent variable (y)
  • Three continuous predictor variables (x1-x3)
  • One categorical predictor variable (c1 with 3 levels)

Which SAS program fits this model?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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Questions 20

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

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Questions 21

Refer to the exhibit:

Which SAS program produced the graph?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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Questions 22

Refer to the ROC curve:

As you move along the curve, what changes?

Options:

A.

The priors in the population

B.

The true negative rate in the population

C.

The proportion of events in the training data

D.

The probability cutoff for scoring

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Questions 23

Which SAS program will divide the original data set into 60% training and 40% validation data sets, stratified by county?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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Questions 24

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.

Logit link (log (p/1-p))

C.

Rank-ordered values of the variables

D.

Weighted sum of chi-square statistics for 2x2 tables

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Questions 25

Refer to the exhibit:

On the Gains Chart, what is the correct interpretation of the horizontal reference line?

Options:

A.

the proportion of cases that cannot be classified

B.

the probability of a false negative

C.

the probability of a false positive

D.

the prior event rate

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Questions 26

Screening for non-linearity in binary logistic regression can be achieved by visualizing:

Options:

A.

A scatter plot of binary response versus a predictor variable.

B.

A trend plot of empirical logit versus a predictor variable.

C.

A logistic regression plot of predicted probability values versus a predictor variable.

D.

A box plot of the odds ratio values versus a predictor variable.

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Questions 27

This question will ask you to provide a missing option.

A business analyst is investigating the differences in sales figures across 8 sales regions. The analyst is interested in viewing the regression equation parameter estimates for each of the design variables.

Which option completes the program to produce the regression equation parameter estimates?

Options:

A.

Solve

B.

Estimate

C.

Solution

D.

Est

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Questions 28

Including redundant input variables in a regression model can:

Options:

A.

Stabilize parameter estimates and increase the risk of overfitting.

B.

Destabilize parameter estimates and increase the risk of overfitting.

C.

Stabilize parameter estimates and decrease the risk of overfitting.

D.

Destabilize parameter estimates and decrease the risk of overfitting.

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Questions 29

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

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Exam Code: A00-240
Exam Name: SAS Statistical Business Analysis SAS9: Regression and Model
Last Update: Jul 10, 2024
Questions: 99
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