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How to study the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
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Topics of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Dumps will include the following topics:
1. ANOVA - 10%
- Perform ANOVA post hoc test to evaluate treatment effect
- Analyze differences between population means using the GLM and TTEST procedures
- Detect and analyze interactions between factors
- Verify the assumptions of ANOVA
2. Linear Regression - 20%
- Use the REG or GLMSELECT procedure to perform model selection
- Fit a multiple linear regression model using the REG and GLM procedures
- Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models
- Assess the validity of a given regression model through the use of diagnostic and residual analysis
3. Logistic Regression - 25%
- Perform logistic regression with the LOGISTIC procedure
- Optimize model performance through input selection
- Score new data sets using the LOGISTIC and PLM procedures
- Interpret the output of the LOGISTIC procedure
4. Prepare Inputs for Predictive Model Performance - 20%
- Improve the predictive power of categorical inputs
- Use the DATA step to manipulate data with loops, arrays, conditional statements and functions
- Screen variables for non-linearity using empirical logit plots
- Screen variables for irrelevance and non-linear association using the CORR procedure
- Identify the potential challenges when preparing input data for a model
5. Measure Model Performance - 25%
- Establish effective decision cut-off values for scoring
- Apply the principles of honest assessment to model performance measurement
- Assess classifier performance using the confusion matrix
- Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
- Model selection and validation using training and validation data
NEW QUESTION 60
A marketing campaign will send brochures describing an expensive product to a set of customers. The cost for mailing and production per customer is $50. The company makes $500 revenue for
each sale.
What is the profit matrix for a typical person in the population?
- A. Option D
- B. Option C
- C. Option A
- D. Option B
Answer: B
NEW QUESTION 61
Refer to the exhibit:
Based upon the comparative ROC plot for two competing models, which is the champion model and why?
- A. Candidate 1, because it is closer to the diagonal reference curve
- B. Candidate 2, because it shows less over fit than Candidate 1
- C. Candidate 1, because the area outside the curve is greater
- D. Candidate 2, because the area under the curve is greater
Answer: D
NEW QUESTION 62
Refer to the exhibit.
Based on the control plot, which conclusion is justified regarding the means of the response?
- A. No groups are significantly different from each other.
- B. Only XL and 2XL are not significantly different from each other.
- C. 2XL is significantly different from all other groups.
- D. All groups are significantly different from each other.
Answer: B
NEW QUESTION 63
Which SAS program will divide the original data set into 60% training and 40% validation data sets,
stratified by county?
- A. Option D
- B. Option C
- C. Option A
- D. Option B
Answer: B
NEW QUESTION 64
Which SAS program will detect collinearity in a multiple regression application?
- A. Option C
- B. Option D
- C. Option A
- D. Option B
Answer: D
NEW QUESTION 65
A marketing manager attempts to determine those customers most likely to purchase additional products as the result of a nation-wide marketing campaign.
The manager possesses a historical dataset (CAMPAIGN) of a similar campaign from last year.
It has the following characteristics:
* Target variable Respond (0, 1)
* Continuous predictor Income
* Categorical predictor Homeowner(Y, N)
Which SAS program performs this analysis?
- A. Option C
- B. Option D
- C. Option A
- D. Option B
Answer: C
NEW QUESTION 66
This question will ask you to provide a missing option.
Given the following SAS program:
What option must be added to the program to obtain a data set containing Spearman statistics?
OUTCORR=estimates
- A.
- B. OUTPUT=estimates
- C. OUT=estimates
- D. OUTS=estimates
Answer: A
Explanation:
Explanation/Reference:
NEW QUESTION 67
Which statistic, calculated from a validation sample, can help decide which model to use for prediction of a binary target variable?
- A. Mallow's Cp
- B. Average Squared Error
- C. Chi Square
- D. Adjusted R Square
Answer: B
NEW QUESTION 68
The total modeling data has been split into training, validation, and test data.
What is the best data to use for model assessment?
- A. Validation data
- B. Total data
- C. Training data
- D. Test data
Answer: A
NEW QUESTION 69
Refer to the REG procedure output:
Click on the calculator button to display a calculator if needed.
- A. 0.1372
- B. 0.4115
- C. 0.5884
- D. 0.6994
Answer: B
NEW QUESTION 70
Refer to the exhibit:
SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each subset are given.
Based on the exhibit, which statement is true?
- A. The R-Square champion model is the most parsimonious.
- B. The SBC champion model is more parsimonious than the AIC champion.
- C. Adjusted R-Square and R-Square agree on the champion model.
- D. The AIC champion model is more parsimonious than the SBC champion.
Answer: B
NEW QUESTION 71
What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?
- A. There is no ability to compare the effectiveness of different cleansing methods.
- B. It violates assumptions of the model.
- C. It omits the training (and test) data sets from the benefits of the cleansing methods.
- D. It requires extra computational effort and time.
Answer: A
NEW QUESTION 72
Refer to the exhibit.
Given alpha=0.02, which conclusion is justified regarding percentage of body fat, comparing small (S), medium (M), and large (L) wrist sizes?
- A. Large wrist size is significantly different than small wrist size.
- B. There is no significant difference due to wrist size.
- C. Medium wrist size is significantly different than small wrist size.
- D. Large wrist size is significantly different than medium wrist size.
Answer: A
NEW QUESTION 73
A researcher is planning a logistic regression to model the probability of disease occurrence. The researcher determines the rate of disease occurrence in the population is 1%.
For which of the following would this study be a candidate?
- A. multicollinearity
- B. oversampling
- C. over fitting
- D. simple random sample
Answer: C
NEW QUESTION 74
Refer to the REG procedure output: The Intercept estimate is interpreted as:
- A. The predicted value of the response when all the predictors are at their current values.
- B. The predicted value of the response when all predictors = 0.
- C. The predicted value of the response when all predictors are at their minimum values.
- D. The predicted value of the response when all predictors are at their means.
Answer: B
NEW QUESTION 75
This question will ask you to provide missing code segments.
A logistic regression model was fit on a data set where 40% of the outcomes were events (TARGET=1)
and 60% were non-events (TARGET=0). The analyst knows that the population where the model will be
deployed has 5% events and 95% non-events. The analyst also knows that the company's profit margin for
correctly targeted events is nine times higher than the company's loss for incorrectly targeted non-event.
Given the following SAS program:
What X and Y values should be added to the program to correctly score the data?
- A. X=.10.Y=05
- B. X=.05, Y=.40
- C. X=.05, Y=10
- D. X=40, Y=10
Answer: C
NEW QUESTION 76
Suppose training data are oversampled in the event group to make the number of events and non-events roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than 0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).
The following SAS program was used.
What does this program calculate?
- A. Sensitivity
- B. Depth
- C. Specificity
- D. Positive predictive value
Answer: A
NEW QUESTION 77
What is the default method in the LOGISTIC procedure to handle observations with missing data?
- A. Only cases with variables that are fully populated are used.
- B. Parameters are estimated accounting for the missing values.
- C. Missing values are imputed.
- D. Parameter estimates are made on all available data.
Answer: A
NEW QUESTION 78
Given the following LOGISTIC procedure:
What is the difference between the datasets OUTFILEJ and OUTFILE_2?
- A. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored
logits. - B. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored
probabilities - C. OUTFILE_1 contains the final parameter estimates while OUTFILE_2 contains the newly scored
probabilities. - D. OUTFILEJ contains the final parameter estimates and Wald Chi-Square values while OUTFILE_2
contains the newly scored probabilities.
Answer: C
NEW QUESTION 79
This question will ask you to provide a missing option.
Complete the following syntax to test the homogeneity of variance assumption in the GLM procedure:
means Region / <insert option here> =levene ;
- A. hovtest
- B. adjust
- C. var
- D. test
Answer: A
Explanation:
Explanation
NEW QUESTION 80
Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4).
- A. Option C
- B. Option D
- C. Option A
- D. Option B
Answer: D
NEW QUESTION 81
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