Free SAS Institute A00-225 Exam Questions
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SAS Institute A00-225 Exam Questions
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Provided By: SAS Institute
- Exam: SAS Advanced Predictive Modeling
- Certification: SAS Administration
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Total Questions: 347
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Updated On: Sep 26, 2024
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Rated: 4.9 |
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Online Users: 694
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Question 1
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A data analyst is using the RANDOMFOREST procedure to create a predictive model. They want to specify the number of trees to be generated in the random forest for a robust prediction. Which option in the RANDOMFOREST statement correctly sets the desired number of trees?
Answer: B
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A data analyst is using the RANDOMFOREST procedure to create a predictive model. They want to specify the number of trees to be generated in the random forest for a robust prediction. Which option in the RANDOMFOREST statement correctly sets the desired number of trees?
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Question 2
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You are evaluating the relationship between a binary target variable and a continuous predictor variable using an empirical logit plot. The plot shows that for low values of the predictor, the logit of the target variable is also low, and as the predictor value increases, the logit of the target variable increases linearly. However, for high values of the predictor, the logit of the target variable levels off, forming an S-shape. Which of the following interpretations is correct?
Answer: C
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You are evaluating the relationship between a binary target variable and a continuous predictor variable using an empirical logit plot. The plot shows that for low values of the predictor, the logit of the target variable is also low, and as the predictor value increases, the logit of the target variable increases linearly. However, for high values of the predictor, the logit of the target variable levels off, forming an S-shape. Which of the following interpretations is correct?
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Question 3
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When preparing data for a predictive modeling project, a data scientist notices that the categorical variable 'payment_type' with four categories ('credit card', 'debit card', 'paypal', 'other') exhibits a high degree of variability in the outcome variable (purchase amount). To improve the model's predictive accuracy, what strategy can the data scientist use to handle the 'payment_type' variable?
Answer: B
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Question 4
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You have developed a linear regression model to predict home prices based on various features such as square footage, number of bedrooms, and location. Which of the following summary statistics would best allow you to assess the overall fit of your linear regression model?
Answer: B
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You have developed a linear regression model to predict home prices based on various features such as square footage, number of bedrooms, and location. Which of the following summary statistics would best allow you to assess the overall fit of your linear regression model?
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Question 5
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A data scientist is working on a predictive modeling project with a target variable that follows a multinomial distribution because the target variable represents multiple unordered categories. Which procedure should they use to model this type of distribution while maintaining computational efficiency?
Answer: D
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A data scientist is working on a predictive modeling project with a target variable that follows a multinomial distribution because the target variable represents multiple unordered categories. Which procedure should they use to model this type of distribution while maintaining computational efficiency?