[Dec 09, 2024] Latest SASInstitute Certification A00-485 Actual Free Exam Questions [Q51-Q67]

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[Dec 09, 2024] Latest SASInstitute Certification A00-485 Actual Free Exam Questions

SASInstitute Certification A00-485 Dumps Updated Practice Test and 190 unique questions

Q51. Refer to the exhibits:

An analyst is evaluating which model to use.
What changed from Comparison 1 to Comparison 2 to select a different champion model?

Prediction Cutoff reduced from .5 to .19

Percentile changed from 5th percentile to 40th percentile

Analyst clicked on Model 2 to highlight it

Misclassification was used instead of Cumulative Lift

Q52. Refer to the exhibit:

How many predictor variables would be included in the score code produced by this model?

Q53. Refer to the exhibit from SAS Visual Statistics:

What can be concluded from the lift plot shown in the exhibit?

The 20% of cases with the highest predicted probability of the modeled event level is expected to capture 2.75 times as many events as a random sample of the same size.

The response rate for the best 20% is predicted to increase 5 times under the fitted model.

The 20% of cases with the lowest predicted probability of the modeled event level is predicted to capture 2.75 times as many events as a random sample of 20%.

The response rate for the best 20% is predicted to be 2.75 times greater than the sample fitted in the model.

Q54. In SAS Visual Statistics, how can you use a derived cluster ID variable in another visualization?

By exporting it as a separate dataset

By linking it to a table in a database

By including it as a dimension in a new visualization

By embedding it within a scatter plot

Q55. How can you interpret model results using the advanced group-by feature in SAS Visual Analytics?

Analyze the impact of different levels of the group-by variable on the model outcome

Explore interaction effects between the group-by variable and other predictors

Visualize the predicted values for each level of the group-by variable

Review the model coefficients for each level of the group-by variable

Q56. In cluster analysis, what does the term “centroid” refer to?

The total number of data points in a cluster

The center point of a cluster in the feature space

The number of variables used in the analysis

The minimum distance between two clusters

Q57. A champion model has been selected and you want to export the score code.
Score code is exported as:

PMML

SAS DS2

SAS Data Step

Q58. In the context of assessing model results, what information can be interpreted from the Fit Summary window?

A list of all predictor variables used in the model

A summary of the model’s goodness of fit and performance metrics

A detailed description of the data preprocessing steps

The distribution of the response variable in the dataset

Q59. When filtering data for a model in SAS Visual Analytics, what can you do to exclude selections and filter data?

Use the exclude option when setting up a filter

Apply a data filter on the visualization

Specify exclusion criteria in the data source properties

Define a filter condition using the interactive filter pane

Q60. Refer to the exhibit from a linear regression model in SAS Visual Statistics:

Based on the table above and assuming a significance level of 0.05, what can be concluded about the linear regression model?

The Intercept is an important predictor of the response.

Age is a significant predictor of the response.

For one one-unit increase in Average Sales, there is an expected increase in the response of
4475.443.

For a 1371.5 unit decrease in Total Promos, there is an expected one-unit increase in the response.

Q61. What is the primary purpose of scoring functionality in SAS Visual Statistics?

To evaluate model performance on a test dataset

To generate code for deploying models in production

To assess the distribution of predictor variables

To select the best model for a given dataset

Q62. Which statement is true regarding the number of polylines created in a Parallel Coordinates plot during Cluster Analysis?

It is calculated using the number of variables visible in the plot.

It is calculated using the variable with the greatest number of bins.

It cannot exceed 3,000.

It is calculated using the number of variables used in the cluster analysis.

Q63. Which statement is TRUE regarding a generalized additive model (GAM) in SAS Visual Analytics?

GAM assumes a strict linear relationship between the predictors and the response function.

The roughness penalty controls the balance between goodness of fit and the roughness of the spline curve.

Specification of a spline effect is optional.

A larger maximum degrees of freedom for the univariate spline term enforces a less complex fit.

Q64. Refer to the exhibit:

A retailer wants to use a decision tree to select one segment to mail 35,000 coupons to existing customers for a new line of organic products.
Assuming that customers who have purchased organic products in the past are likely to want new organic products in the future, select the single best Leaf ID for the mailing.