SASInstitute New 2024 A00-485 Test Tutorial (Updated 190 Questions) [Q18-Q38]

NO.18 What do cluster properties refer to in the context of cluster analysis?

Descriptive statistics of individual data points

Characteristics shared by data points within a cluster

The number of clusters in the analysis

A measure of data point centrality

NO.19 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.

NO.20 What is the primary purpose of specifying the link function in logistic regression?

To control the significance level of predictor variables

To determine the distribution of the response variable

To ensure that all predictor variables are used

To establish the relationship between the linear predictor and the probability of an event

NO.21 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.

NO.22 You would like to build a cluster analysis using several variables related to demographics. You noticed that the variable Inferred HH Education is a nominal variable with values of “High School Grad”,
“College Grad”, etc.
Which action allows you to incorporate this variable in the cluster analysis without returning a warning?

NO.23 How can you assign a group-by variable to a predictive model in SAS Visual Analytics?

Drag and drop the group-by variable into the predictor field of the model

Select the group-by variable from a dropdown menu in the model settings

Specify the group-by variable in the data source properties

Click on the group-by variable and choose “Assign as predictor” from the context menu

NO.24 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

NO.25 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.

NO.26 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

NO.27 Which statement is true for negative binomial and Poisson regression models?

Poisson regression models are used for count data, and negative binomial models are used for binary responses.

The canonical link function for Poisson regression is the log, while for negative binomial it is the logit.

Poisson regression is a special case of negative binomial regression.

Negative binomial models accommodate negative integers while Poisson regression does not.

NO.28 When performing linear regression modeling, what is the primary goal of assessing multicollinearity among predictors?

To identify influential outliers

To detect non-linear relationships

To ensure that predictor variables are not highly correlated

To calculate the coefficient of determination (R-squared)

NO.29 When would you typically use a linear regression model instead of a generalized linear model (GLM)?

When the dependent variable is binary

When there is no assumption of linearity in the data

When dealing with count data

When the goal is to model categorical outcomes

NO.30 In group-by modeling, when is the p-value for the group-by variable considered significant?

When the p-value is less than 0.05

When the p-value is greater than 0.05

When the p-value is exactly 0.05

When the p-value is less than 0.01

NO.31 What are the benefits of applying filters to both visualization and data source in SAS Visual Analytics?

Enhanced user experience by providing more interactive filtering options

Consistency in data presentation across multiple visualizations

Improved security by restricting access to specific data

Increased performance by reducing data retrieval from the source

NO.32 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

NO.33 In model assessment, why might you need to assess residuals and other model diagnostics to choose an appropriate distribution and link function?

To calculate the p-values of predictor variables

To determine the order of predictor variables in the model

To ensure that predictor variables are not highly correlated

To verify if the chosen model assumptions are met and make adjustments if necessary

NO.34 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.

NO.35 You want to fit a Poisson regression and use the log link function to predict skin cancer from weather, pollution, and demographic variables. Each row in the data is a geographic region.
The response, Melanoma, is stored as the number of melanoma skin cancer cases in each region.
Because some regions have many people and some have few, your data also includes a variable with the region population.
What is the best way to include population in this model?

Add Population as an offset.

Add the log of Population as an offset.

Add Population as an effect.

Add the log of Population as an effect.

NO.36 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.

NO.37 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

NO.38 When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?

Normal distribution with an identity link function

Poisson distribution with a log link function

Binomial distribution with a logit link function

Exponential distribution with a square root link function

SASInstitute New 2024 A00-485 Test Tutorial (Updated 190 Questions) [Q18-Q38]

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