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November 14, 2024

Practicing with SAS Certified Associate: Modeling Using SAS Visual Statistics A00-485 exam dumps questions can help you build confidence and reduce exam anxiety. By familiarizing yourself with the types of questions you can expect to see on the A00-485 Modeling Using SAS Visual Statistics exam and mastering the concepts and skills required to answer them, you can approach the exam with greater confidence and a sense of calm. Besides, A00-485 dumps questions can help you achieve this level of knowledge and confidence. Study free SAS Institute A00-485 exam dumps below.

Page 1 of 6

1. You would like to compare multiple models that you've built in SAS Visual Statistics.

Which parameters must be the same for all models being compared? (choose 3)

Data Source

Assessment Bins

Model Type

Event Level

Response Variable

Link Function

2. 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

3. When examining the Cluster Summary tab, what information is typically available?

The number of variables in the analysis

Statistics for each cluster, such as mean and standard deviation

The number of iterations performed during clustering

The decision tree structure for each cluster

4. When performing decision tree analysis in SAS Visual Statistics, how does the property setting for "include missing" modify the usage of missing values within categorical discrete predictors?

imputes the mean of the predictor's known values

imputes the median of the predictor's known values

assigns its own level

assigns the smallest available machine value

5. When evaluating a Misclassification plot, what does it typically show?

The distribution of predictor variables in the dataset

The relationship between two predictor variables

The trade-off between false positives and false negatives at different thresholds

The p-values associated with the predictor variables

6. What does adding an interaction effect in linear regression modeling allow you to capture?

The joint impact of two or more predictors on the response variable

The presence of outliers in the data

The multicollinearity among predictors

The effect of missing data on the model

7. Given a scenario, what fit statistic can be used to select a champion model in model comparison?

The p-value of the intercept term

The R-squared value

The AUC (Area Under the Curve)

The learning rate of the model

8. What is the maximum number of response variables that SAS Visual Statistics allows for a decision tree?

9. Which statement is correct about using a multinomial response variable (with 3 or more levels) in the logistic regression task in SAS Visual Statistics?

You cannot assign a response variable with 3 or more levels to the logistic regression visualization.

The resulting model is a binary logistic regression model with a selected level as the event.

The resulting model is a multinomial logistic regression model with a generalized logit link.

The resulting model is an ordinal logistic regression model with the lowest level of the response as the reference.

10. What is the purpose of applying a prediction cut-off in model assessment?

To divide the dataset into training and testing sets

To identify influential data points in the dataset

To determine the optimal threshold for classifying outcomes

To calculate the p-values of predictor variables

Page 2 of 6

11. How can you interpret a Parallel Coordinates plot in cluster analysis?

It shows the distribution of data within a cluster.

It visualizes the relationship between clusters.

It displays the hierarchical structure of clusters.

It provides a summary of cluster statistics.

12. What conditions might make models less comparable in SAS Visual Statistics?

If they use the same dataset and response variable

If they have different learning rates

If they are both logistic regression models

If they have similar AUC values

13. What are the benefits of applying filters to both visualization and data source in SAS Visual Analytics?

Increased performance by reducing data retrieval from the source

Consistency in data presentation across multiple visualizations

Improved security by restricting access to specific data

Enhanced user experience by providing more interactive filtering options

14. In generalized linear models, what is the purpose of the link function?

To determine the distribution of the response variable

To specify the relationship between the predictor and response variables

To calculate the p-values of predictor variables

To adjust the model for multicollinearity

15. In logistic regression modeling, how is the probability of an event typically estimated?

By calculating the mean of the predictor variables

By fitting a linear regression model to the data

By applying the link function to the linear predictor

By assigning roles to variables

16. In linear regression modeling, what roles are typically assigned to variables?

Input, Target, and Nominal

Dependent, Independent, and Categorical

Predictor, Response, and Interaction

Intercept, Slope, and Error

17. In a generalized linear model, what is the role of the link function in transforming the linear predictor?

It determines the distribution of the response variable.

It scales the predictor variables.

It ensures that the linear predictor is always positive.

It maps the linear predictor to the range of the response variable.

18. Refer to the following exhibit:

After creating a decision tree in SAS Visual Statistics, what is the value in deriving a Leaf ID Variable?

Use the leaf ID data item in filters in other types of visualizations.

Use the leaf ID to rank order by posterior probabilities.

Use the leaf ID to identify clusters.

Use the leaf ID to identify the most important variables.

19. How does SAS Data Integration Studio facilitate scoring new data using exported score code?

By generating score code automatically during ETL processes

By providing a visual interface for connecting to external data sources

By enabling the scheduling of batch scoring jobs

By automatically tuning hyperparameters for scoring

20. When interpreting an Influence plot, what does it typically show?

The distribution of residuals in the model

The effect of each predictor variable on the response

The interaction between two predictor variables

The relationship between the response variable and the intercept term

Page 3 of 6

21. When combining multiple categories into fewer levels in SAS Visual Analytics, what technique is often used?

Data imputation

Principal Component Analysis (PCA)

Binning or grouping

Variable transformation

22. Given a scenario where the response variable represents the number of accidents in a day, what distribution and link function might be appropriate for modeling?

Poisson distribution with a log link function

Normal distribution with an identity link function

Exponential distribution with a square root link function

Logistic distribution with a logit link function

23. Given a scenario, what condition makes models comparable in SAS Visual Statistics?

If they use different response variables

If they have different sample sizes

If they use the same dataset and response variable

If they use different link functions

24. What is the purpose of deriving a cluster ID variable in cluster analysis?

To assign cluster labels to data points

To create a scatter plot of data points

To calculate the distance between clusters

To set parallel coordinate properties

25. Select the best distribution to model with linear regression.

A)

Option A

Option B

Option C

Option D

26. When building a Generalized Linear Model in SAS Visual Statistics, which link function is available?

Poisson

Gaussian

Negative Binomial

Log

27. You would like to see the minimum and maximum values for all of your measures so that you can filter variables as needed.

Which is the most efficient way to do that?

Create aggregated measures using the Min and Max aggregations.

Select a histogram object for each measure.

Select View Measure Details within the Actions menu to the right of the dataset name.

Create a calculated item subtracting the Min aggregation from the Max aggregation.

28. 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

29. When assigning variable roles for a decision tree, which role typically represents the target variable you want to predict?

Input

Predictor

Output

Splitter

30. Refer to the exhibit:

Using the lift chart above to evaluate a decision tree model where the event level is Purchase, what is the expected performance of the model for the best 20% of cases predicted?

About 4 times better than a random sample of the same size

About 1.5 times better than a random sample of the same size

About 1.25 times better than a random sample of the same size

About 1.1 times better than a random sample of the same size

Page 4 of 6

31. What are some properties that can be defined in a generalized linear regression model?

Coefficients and p-values

Distribution and link function

Number of predictors

Residuals and intercept

32. What is the primary purpose of imputing a variable in SAS Visual Analytics?

To remove missing values

To replace incorrect values

To create new variables

To aggregate data

33. What are some properties that can be defined in a linear regression model?

Learning rate and number of iterations

Coefficients, p-values, and R-squared

Maximum depth and minimum leaf size

Confusion matrix and accuracy

34. Refer to the Parallel Coordinates Plot shown on the Exhibit.

Which two statements about cluster 0 in the Parallel Coordinates Plot are correct? (Choose two.)

It contains the most observations.

In relation to the other clusters, it consists of people from the lower income group.

In relation to the other clusters, it consists of people who are younger.

In relation to the other clusters, it consists of people whose house values are lower.

35. When applying interactive group-by in SAS Visual Analytics, what happens when you select a specific group?

The visualization updates to show data only for the selected group

The selected group is highlighted within the visualization

The other groups are temporarily hidden from the visualization

The measures are aggregated for the selected group

36. An analyst wants to limit data to a certain demographic and build a decision tree model.

Which approach should the analyst take?

Create a report filter.

Create a new data hierarchy.

Create an SQL query from the filters tab.

Create a new ranks variable on age and sort descending on that variable.

37. When examining the summary table for group-by processing, what information can you find?

The number of observations in each group

The mean value of the target variable for each group

The standard deviation of the target variable for each group

The distribution of the group-by variable

38. What does a Group-by Variable enable you to do in SAS Visual Statistics?

Fit a model for every value of a measure's distribution.

Use variable selection.

Leverage informative missingness for measure and category variables.

Fit a model for each data segment defined by one or more category variables.

39. Explain what an icicle plot represents in decision tree analysis.

It displays the hierarchical structure of the decision tree.

It visualizes the distribution of data points in each leaf node.

It shows the feature importance for each variable in the tree.

It summarizes the performance metrics of the decision tree.

40. Refer to the exhibits:

Exhibit 1:

Exhibit 2:

An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.

Why are there 5 cluster IDs in Exhibit 2 based on these settings?

Cluster Matrix Visible Roles setting is 5.

There are observations with missing values.

Variable Standardization has been chosen.

Parallel Coordinates Visible Roles setting is 5.

Page 5 of 6

41. You have a regression model effect that represents the total amount of sales. In addition to that, you would like to create a model effect that represents the average amount of sales.

Which option should you use?

Create an aggregated measure using the Avg aggregation on total amount of sales.

Create a calculated item that divides total amount of sales by the total amount of items sold.

Create a calculated item by duplicating the original model effect and changing its default aggregation to Average.

Create an aggregated measure using the Sum aggregation of total amount of sales divided by the Sum aggregation of total amount of items sold.

42. 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

43. What information can you gather from Leaf statistics in a decision tree analysis?

The total number of data points in each leaf node

The distribution of target variable values in each leaf node

The tree's decision rules for each leaf node

The tree's overall accuracy and error rate

44. Which statement is true regarding model comparison within SAS Visual Statistics?

Two generalized linear models cannot be compared if they use different underlying distributions.

Two cluster analyses cannot be compared if they have different initial seed assignments.

A logistic regression and a decision tree cannot be compared.

A linear regression and a generalized linear model cannot be compared.

45. Interactive group-by analysis can be performed for each of the following in Visual Statistics except:

Logistic regression

Linear regression

Decision tree

Generalized linear model

46. Prior to fitting a regression model, data binning of a continuous effect should be used for what purpose?

Improve the accuracy of your predictions.

Reduce the impact of minor observation errors.

Reduce the cardinality of a continuous effect.

Gain information due to discretization.

47. When implementing score code in SAS Enterprise Guide, which step is typically involved in the process?

Dragging and dropping the score code file into the project

Running a SQL query to generate predictions

Opening the code file and manually executing it

Converting the code to a macro for automation

48. How is prediction typically performed in logistic regression?

By calculating the mean of the response variable

By estimating the probability of an event for each observation

By fitting a straight line through the data points

By maximizing the likelihood of the response variable

49. When specifying Cluster Roles for Cluster Analysis in SAS Visual Statistics, which condition is correct?

Interaction items are allowed.

A target variable is required.

At least two variables are required.

Category items are not allowed.

50. What are the essentials of logistic regression?

Modeling binary or ordinal outcomes

Estimating probabilities of categorical outcomes

Assuming a linear relationship between predictors and response

Using the logit link function to model the probability of an event

Page 6 of 6

51. Interactions can be created and added to a linear regression model.

Which statement is true about interactions?

An interaction can be created for a squared category variable.

Measures and categories can be combined to create an interaction.

Each interaction is limited to 3 effects or fewer.

The maximum number of interactions allowed in a model is 3.

52. In SAS Visual Analytics, what can you use to choose the best fitting group-by model?

Fit statistics such as AIC and BIC

Variable Importance

Visualization of model residuals

Group-by variable with the highest p-value

53. What does it mean to prune a decision tree?

To remove all leaf nodes and keep only the root node

To trim branches of the tree to reduce complexity and overfitting

To increase the depth of the tree to improve accuracy

To convert the decision tree into a random forest model

54. How is the KS Statistic typically used when interpreting an ROC chart?

To measure the area under the ROC curve

To assess the balance between sensitivity and specificity

To identify the optimal prediction cut-off threshold

To evaluate the overall performance of a classification model

55. How can you appropriately change the number of clusters in a k-means cluster analysis?

By adjusting the learning rate

By modifying the random seed

By changing the K-value

By increasing the number of iterations

56. What is one advantage of using SAS Studio to score new data with exported score code?

It requires no additional software installation.

It provides advanced visualization capabilities.

It allows for direct integration with Hadoop clusters.

It automatically optimizes the scoring process.

57. Refer to the exhibit:

What does the Residual Plot from a linear regression model reveal?

It suggests the error variance is constant.

The model is not capturing all of the available signals in the data.

It suggests the errors are uncorrelated.

There is an approximately equal number of positive and negative residuals.

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