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NEW QUESTION # 49
In decision tree modeling, what is the purpose of setting a minimum split count?
- A. To determine the maximum depth of the tree
- B. To specify the minimum number of data points required to perform a split
- C. To prevent any splits in the tree
- D. To control the learning rate of the model
Answer: B
NEW QUESTION # 50
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?
- A. For one one-unit increase in Average Sales, there is an expected increase in the response of
4475.443. - B. For a 1371.5 unit decrease in Total Promos, there is an expected one-unit increase in the response.
- C. The Intercept is an important predictor of the response.
- D. Age is a significant predictor of the response.
Answer: A
NEW QUESTION # 51
Which SAS tools can be used to score new data using score code generated by SAS Visual Statistics?
- A. SAS Data Integration Studio
- B. SAS Studio
- C. SAS Enterprise Guide
- D. SAS Enterprise Miner
Answer: A,B,C,D
NEW QUESTION # 52
How are split points determined in a decision tree?
- A. By maximizing information gain or Gini impurity reduction
- B. By minimizing the number of leaf nodes
- C. Based on the order of appearance in the dataset
- D. Randomly assigned
Answer: A
NEW QUESTION # 53
In the context of assessing model results, what information can be interpreted from the Fit Summary window?
- A. A detailed description of the data preprocessing steps
- B. A summary of the model's goodness of fit and performance metrics
- C. A list of all predictor variables used in the model
- D. The distribution of the response variable in the dataset
Answer: B
NEW QUESTION # 54
What is the maximum number of response variables that SAS Visual Statistics allows for a decision tree?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
NEW QUESTION # 55
Refer to the exhibit:
What does the Residual Plot from a linear regression model reveal?
- A. It suggests the error variance is constant.
- B. There is an approximately equal number of positive and negative residuals.
- C. The model is not capturing all of the available signals in the data.
- D. It suggests the errors are uncorrelated.
Answer: C
NEW QUESTION # 56
Which of the following criteria are commonly used for pruning a decision tree?
- A. Minimum split count
- B. Maximum depth
- C. Maximum leaf nodes
- D. Maximum tree height
Answer: A,B,C
NEW QUESTION # 57
Which SAS tool is most suitable for managing explorations and visualizations in a business intelligence context?
- A. SAS Studio
- B. SAS Visual Data Builder
- C. SAS Enterprise Guide
- D. SAS Enterprise Miner
Answer: B
NEW QUESTION # 58
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?
- A. logistic regression model using the Probit link function
- B. generalized linear model using the binomial distribution and the log link function
- C. logistic regression model using the Tobit link function
- D. logistic regression model using the Logit link function
Answer: D
NEW QUESTION # 59
In the context of linear regression, what does the term "linearity" refer to?
- A. The absence of any relationship between variables
- B. The requirement for variables to be categorical
- C. The use of a straight line to model relationships
- D. The use of polynomial functions for modeling
Answer: C
NEW QUESTION # 60
What are the benefits of applying filters to both visualization and data source in SAS Visual Analytics?
- A. Consistency in data presentation across multiple visualizations
- B. Increased performance by reducing data retrieval from the source
- C. Improved security by restricting access to specific data
- D. Enhanced user experience by providing more interactive filtering options
Answer: A,B
NEW QUESTION # 61
What is the primary purpose of scoring functionality in SAS Visual Statistics?
- A. To assess the distribution of predictor variables
- B. To evaluate model performance on a test dataset
- C. To generate code for deploying models in production
- D. To select the best model for a given dataset
Answer: B,C
NEW QUESTION # 62
Which equation does NOT represent a linear model? Note: bi are parameters and Xi are variables.
- A. y = b0 + b1X1 + (b2/b1)X2
- B. y = b0 + b1X1 + b2X2
- C. y = b0 + b1X1 + b2X1 3
- D. y = b0 + b1X1 + b2X2 + b3(X1X2)
Answer: A
NEW QUESTION # 63
What can be interpreted from the Summary Table for model comparison, including statistics and variable importance?
- A. The number of iterations performed by each model
- B. Model performance metrics and their relative importance
- C. The correlation matrix of predictor variables
- D. The distribution of predictor variables
Answer: B
NEW QUESTION # 64
The Leaf size property within a decision tree is changed from 5 to 10 and no other stopping rules were met.
How will the tree change?
- A. The tree will be simpler.
- B. The tree will be harder to interpret.
- C. The tree will train more slowly.
- D. The tree will be more complex.
Answer: A
NEW QUESTION # 65
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?
- A. The Intercept is an important predictor of the response.
- B. For a .03696 unit decrease in RunPulse, there is an expected one-unit increase in the response.
- C. RestPulse is a significant predictor of the response.
- D. For one one-unit increase in RunTime, there is an expected increase in the response of 2.6287.
Answer: D
NEW QUESTION # 66
What are some properties that can be defined in a linear regression model?
- A. Learning rate and number of iterations
- B. Confusion matrix and accuracy
- C. Coefficients, p-values, and R-squared
- D. Maximum depth and minimum leaf size
Answer: C
NEW QUESTION # 67
When applying interactive group-by in SAS Visual Analytics, what happens when you select a specific group?
- A. The visualization updates to show data only for the selected group
- B. The measures are aggregated for the selected group
- C. The selected group is highlighted within the visualization
- D. The other groups are temporarily hidden from the visualization
Answer: A,C,D
NEW QUESTION # 68
In SAS Visual Analytics, which of the following tasks involves converting a categorical variable into a numerical one?
- A. Creating a dummy variable
- B. Aggregating a measure
- C. Replacing dirty data
- D. Transforming a variable
Answer: A
NEW QUESTION # 69
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