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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Format: Multiple choices, multiple answers , short answers
Length of Examination: 120 minutes
Language: Czech, simplified Chinese, traditional Chinese, Dutch, English (UK), English (US), French, German, Indonesian, Italian, Japanese, Korean, Polish, Portuguese, Portuguese (Brazil), Russian, Slovak, Spanish, Spanish (Latin America), Thai, Turkish, and Vietnamese
Number of Questions: 60 multiple-choice and short-answer questions(In addition to the 60 scored items, there may be up to five unscored items)
Passing score: 68% (Must achieve score of 68 percent correct to pass)

SASInstitute A00-240 Certification is a valuable credential for professionals who work in the field of business analytics. By passing A00-240 exam, individuals can demonstrate their proficiency in SAS statistical software and their ability to perform statistical analysis using regression and modeling techniques.

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The SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential is aimed at professionals who work in data analysis, business intelligence, and statistical modeling. SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification exam covers a range of topics such as data preparation, linear regression, logistic regression, and time series analysis.

SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q49-Q54):

NEW QUESTION # 49
Refer to the following exhibit:

What is a correct interpretation of this graph?

A. The association between the binary predictor and the log-odds is quadratic.
B. The association between the continuous predictor and the binary response is quadratic.
C. The association between the continuous predictor and the log-odds is quadratic.
D. The association between the continuous predictor and the continuous response is quadratic.

Answer: C

NEW QUESTION # 50
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. New cases with missing values on input variables cannot be scored without extra data processing.
B. The model will likely be overfit.
C. There will be a high rate of collinearity among input variables.
D. Complete case analysis means that fewer observations will be used in the model building process.

Answer: A,D

NEW QUESTION # 51
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 # 52
Which SAS program will detect collinearity in a multiple regression application?

A. Option B
B. Option A
C. Option D
D. Option C

Answer: A

NEW QUESTION # 53
Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4).

A. Option B
B. Option A
C. Option D
D. Option C

Answer: A

NEW QUESTION # 54
......

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