SASInstitute Modeling Using SAS Visual Statistics

QUESTION NO: 1
Cluster Analysis in SAS Visual Statistics is categorized as which type of machine learning?

A. Unsupervised learning B. Semi-supervised learning C. Supervised learning D. Reinforcement learning

Correct Answer: A

QUESTION NO: 2
When assessing the quality of a linear regression model, what does a low p-value associated with the F-statistic suggest?

A. The model has a significant overall explanatory power. B. The model has a high level of multicollinearity. C. The model is a poor fit for the data. D. The model has a weak linear relationship with the response.

Correct Answer: A

QUESTION NO: 3
In linear regression, what does the coefficient of determination (R-squared) measure?

A. The goodness of fit of the model to the data B. The degree of multicollinearity among predictors C. The impact of outliers on the model D. The p-value associated with the intercept term

Correct Answer: A

QUESTION NO: 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?

A. assigns its own level B. imputes the mean of the predictor's known values C. imputes the median of the predictor's known values D. assigns the smallest available machine value

Correct Answer: A

QUESTION NO: 5
What is meant by "informative missingness" in the context of linear regression?

A. Missing data that is unrelated to the outcome variable B. Missing data that provides valuable information about the outcome C. Missing data that is randomly distributed across observations D. Missing data that leads to multicollinearity among predictors

Correct Answer: B

QUESTION NO: 6
Which modeling technique automatically includes missing values?

A. Logistic regression B. Linear regression C. Generalized linear model D. Decision tree

Correct Answer: D

QUESTION NO: 7
How is the KS Statistic typically used when interpreting an ROC chart?

A. To identify the optimal prediction cut-off threshold B. To evaluate the overall performance of a classification model C. To assess the balance between sensitivity and specificity D. To measure the area under the ROC curve

Correct Answer: C

QUESTION NO: 8
What does a Lift chart evaluate in terms of model performance?

A. The correlation between predictor variables B. The relative performance of the model compared to a random model C. The interaction effects between predictor variables D. The distribution of the response variable

Correct Answer: B

QUESTION NO: 9
When assigning variable roles for a decision tree, which role typically represents the target variable you want to predict?

A. Predictor B. Input C. Output D. Splitter

Correct Answer: C

QUESTION NO: 10
When reviewing Measure Details in SAS Visual Analytics, what information can you find related to measures?

A. Measure name and label B. Measure calculation method C. Measure format and informat D. Measure data type

Correct Answer: A,C,D

QUESTION NO: 11
What properties can be assigned when comparing models in SAS Visual Statistics?

A. The number of observations in the dataset B. The learning rate for gradient boosting models C. The color scheme for visualization D. The variables to include in the model comparison

Correct Answer: D

QUESTION NO: 12
Which statement is true about performing regressions in SAS Visual Statistics?

A. You can specify an ordinal classifier as the response variable with linear regression. B. You can build neither a linear regression nor a logistic regression with a generalized linear model. C. You can build both a linear regression or a logistic regression with a generalized linear model. D. You can specify a multinomial classifier as the response variable with linear regression.

Correct Answer: C

QUESTION NO: 13
How can predicted values be derived and described in terms of predicted probabilities in SAS Visual Statistics?

A. By fitting a linear regression model to the data B. By applying the link function to the linear predictor C. By calculating the mean of the predictor variables D. By summing the residuals of the model

Correct Answer: B

SASInstitute Modeling Using SAS Visual Statistics - A00-485 Exam Questions