A00-240 practice tests

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SASInstitute A00-240 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prepare Inputs for Predictive Modeling	20%	- Manipulate data using DATA step - Screen variables with CORR procedure and empirical logit plots - Identify data preparation challenges - Transform categorical variables
Topic 2: Logistic Regression	25%	- Interpret odds ratios and model coefficients - Build models using PROC LOGISTIC - Score new datasets with LOGISTIC and PLM - Select and optimize input variables
Topic 3: Measure and Evaluate Model Performance	25%	- Create and interpret ROC, lift, and gains charts - Use confusion matrices and classification metrics - Determine optimal decision cut-off values - Validate models with training/validation data - Apply honest assessment principles
Topic 4: Analysis of Variance (ANOVA)	10%	- Assess ANOVA assumptions - Use PROC GLM for ANOVA - Analyze factor interactions - Perform post-hoc tests
Topic 5: Linear Regression	20%	- Interpret REG, GLM, and PLM procedure output - Perform model selection with GLMSELECT - Conduct residual and diagnostic analysis - Fit multiple linear regression models

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q38-Q43):

NEW QUESTION # 38
An analyst knows that the categorical predictor, storeId, is an important predictor of the target.
However, store_Id has too many levels to be a feasible predictor in the model. The analyst wants to
combine stores and treat them as members of the same class level.
What are the two most effective ways to address the problem? (Choose two.)

A. Cluster by using Greenacre's method to combine stores that are similar.
B. Eliminate store_id as a predictor in the model because it has too many levels to be feasible.
C. Use subject matter expertise to combine stores that are similar.
D. Randomly combine the stores into five groups to keep the stochastic variation among the observations
intact.

Answer: A,C

NEW QUESTION # 39
Refer to the REG procedure output:

How many observations are used in the analysis? Enter your numeric answer in the space below.

Answer:

Explanation:
100

NEW QUESTION # 40
Refer to the lift chart:

What does the reference line at lift = 1 corresponds to?

A. The predicted lift for the best 50% of validation data cases
B. The predicted lift if the entire population is scored as event cases
C. The predicted lift if 50% of the population are randomly scored as event cases
D. The predicted lift if none of the population are scored as event cases

Answer: B

NEW QUESTION # 41
A predictive model uses a data set that has several variables with missing values.
What two problems can arise with this model? (Choose two.)

A. The model will likely be overfit.
B. Complete case analysis means that fewer observations will be used in the model building process.
C. There will be a high rate of collinearity among input variables.
D. New cases with missing values on input variables cannot be scored without extra data processing.

Answer: B,D

Explanation:
Explanation/Reference:

NEW QUESTION # 42
Which statistic is based on the maximum vertical distance between the primary event EDF and the secondary event EDF?

A. SBC
B. Brier Score
C. Max EDF
D. KS

Answer: D

NEW QUESTION # 43
......

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