[Oct-2024] Dumps Brief Outline Of The A00-485 Exam - ValidBraindumps [Q75-Q97] : Free valid test braindumps : http://free.validbraindumps.com

Q75. In SAS Visual Analytics, what is the purpose of creating an aggregated measure?

To combine multiple categories into fewer levels

To replace dirty data with missing values

To calculate summary statistics for a measure

To transform a categorical variable into a numerical one

Q76. 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

Q77. When assigning variable roles for a decision tree, which role typically represents the target variable you want to predict?

Input

Predictor

Output

Splitter

Q78. 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

Q79. What does the Variable Importance feature help with when choosing the best fitting group-by model?

Identifying the most influential predictors

Assessing the significance of each predictor

Evaluating the multicollinearity among predictors

Understanding the distribution of the target variable

Q80. 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.

Q81. What information is conveyed by a Summary bar in model assessment?

The standard deviation of the predictor variables

The summary statistics of the response variable

The performance metrics of the model, such as AUC and KS Statistic

The distribution of residuals in the model

Q82. Which statement is true for the Informative Missingness property in SAS Visual Statistics?

Missing values are imputed and indicator variables are created for missing predictors.

Missing values are flagged on diagnostic plots.

A table of missingness patterns for the predictor variables is displayed in the model output.

The user is prompted to fill in a value to impute for missing predictor variables.

Q83. Refer to the exhibit:

An economist is predicting demand using a linear regression model.
If all of the effect variables equal 1, what is the predicted demand?

352.415433

352.405432

362.415133

352.454433

Q84. You want to build a model that predicts whether a customer will default on a loan assuming an underlying binomial distribution.
Which model within SAS Visual Statistics would you use?

generalized linear model using the binomial distribution and the log link function

logistic regression model using the Probit link function

logistic regression model using the Tobit link function

logistic regression model using the Logit link function

Q85. You want to use a generalized linear model to predict donation amount from a set of demographics predictors. Donation amount is known to be right-skewed, with many non-donors (donation amount = 0).
Which settings in the Generalized Linear Model task are most appropriate for modeling this response?

Q86. What does the interactive group-by feature in SAS Visual Analytics allow you to do?

Dynamically change the group-by variable during analysis

Apply group-by modeling to multiple measures simultaneously

Interactively explore different levels of the group-by variable

Create subgroups within the group-by variable

Q87. 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.

Q88. 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

Q89. What roles can be assigned to variables in logistic regression?

Input

Target

Nominal

Interval

Q90. 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

Q91. Which statement is true about performing regressions in SAS Visual Statistics?

You can specify a multinomial classifier as the response variable with linear regression.

You can specify an ordinal classifier as the response variable with linear regression.

You can build neither a linear regression nor a logistic regression with a generalized linear model.

You can build both a linear regression or a logistic regression with a generalized linear model.

Q92. 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

Q93. What is the primary purpose of modeling effects in linear regression?

To assess multicollinearity among predictors

To identify outliers in the data

To capture the relationship between predictors and the response variable

To calculate the p-values of the predictors

Q94. How are split points determined in a decision tree?

Randomly assigned

By maximizing information gain or Gini impurity reduction

Based on the order of appearance in the dataset

By minimizing the number of leaf nodes

Q95. Which equation does NOT represent a linear model? Note: bi are parameters and Xi are variables.

y = b0 + b1X1 + b2X2

y = b0 + b1X1 + b2X2 + b3(X1X2)

y = b0 + b1X1 + (b2/b1)X2

y = b0 + b1X1 + b2X1 3

Q96. 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

Q97. Which of the following are common distributions used in generalized linear models?

Normal

Poisson

Exponential

Logistic