SAS Global Certification program
SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
Designed for SAS professionals who use SAS/STAT software to conduct and interpret complex statistical data analysisSuccessful candidates should have experience in
Required ExamCandidates who earn this credential will have earned a passing score on the SAS Statistical Business Analysis Using SAS 9: Regression and Modeling exam. This exam is administered by SAS and Pearson VUE.
- 60 scored multiple-choice and short-answer questions (must achieve score of 68% correct to pass)
- In addition to the 60 scored items, there may be up to 5 unscored items.
- 2 hours to complete exam
- Use exam ID A00-240; required when registering with Pearson VUE.
Exam topics include:
ANOVA - 10%
Verify the assumptions of ANOVA
- Explain the central limit theorem and when it must be applied
- Examine the distribution of continuous variables (histogram, box-whisker, Q-Q plots)
- Describe the effect of skewness on the normal distribution
- Define H0, H1, Type I/II error, statistical power, p-value
- Describe the effect of sample size on p-value and power
- Interpret the results of hypothesis testing
- Interpret histograms and normal probability charts
- Draw conclusions about your data from histogram, box-whisker, and Q-Q plots
- Identify the kinds of problems may be present in the data: (biased sample, outliers, extreme values)
- For a given experiment, verify that the observations are independent
- For a given experiment, verify the errors are normally distributed
- Use the UNIVARIATE procedure to examine residuals
- For a given experiment, verify all groups have equal response variance
- Use the HOVTEST option of MEANS statement in PROC GLM to asses response variance
Analyze differences between population means using the GLM and TTEST procedures
- Use the GLM Procedure to perform ANOVA
- CLASS statement
- MODEL statement
- MEANS statement
- OUTPUT statement
- Evaluate the null hypothesis using the output of the GLM procedure
- Interpret the statistical output of the GLM procedure (variance derived from MSE, F value, p-value R**2, Levene's test)
- Interpret the graphical output of the GLM procedure
- Use the TTEST Procedure to compare means
Perform ANOVA post hoc test to evaluate treatment effect
- Use the LSMEANS statement in the GLM or PLM procedure to perform pairwise comparisons
- Use PDIFF option of LSMEANS statement
- Use ADJUST option of the LSMEANS statement (TUKEY and DUNNETT)
- Interpret diffograms to evaluate pairwise comparisons
- Interpret control plots to evaluate pairwise comparisons
- Compare/Contrast use of pairwise T-Tests, Tukey and Dunnett comparison methods
Detect and analyze interactions between factors
- Use the GLM procedure to produce reports that will help determine the significance of the interaction between factors. MODEL statement
- LSMEANS with SLICE=option (Also using PROC PLM)
- ODS SELECT
- Interpret the output of the GLM procedure to identify interaction between factors: p-value
- F Value
- R Squared
- TYPE I SS
- TYPE III SS
Fit a multiple linear regression model using the REG and GLM procedures
- Use the REG procedure to fit a multiple linear regression model
- Use the GLM procedure to fit a multiple linear regression model
Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models
- Interpret REG or GLM procedure output for a multiple linear regression model: convert models to algebraic expressions
- Convert models to algebraic expressions
- Identify missing degrees of freedom
- Identify variance due to model/error, and total variance
- Calculate a missing F value
- Identify variable with largest impact to model
- For output from two models, identify which model is better
- Identify how much of the variation in the dependent variable is explained by the model
- Conclusions that can be drawn from REG, GLM, or PLM output: (about H0, model quality, graphics)
Use the REG or GLMSELECT procedure to perform model selection
- Use the SELECTION option of the model statement in the GLMSELECT procedure
- Compare the different model selection methods (STEPWISE, FORWARD, BACKWARD)
- Enable ODS graphics to display graphs from the REG or GLMSELECT procedure
- Identify best models by examining the graphical output (fit criterion from the REG or GLMSELECT procedure)
- Assign names to models in the REG procedure (multiple model statements)
Assess the validity of a given regression model through the use of diagnostic and residual analysis
- Explain the assumptions for linear regression
- From a set of residuals plots, asses which assumption about the error terms has been violated
- Use REG procedure MODEL statement options to identify influential observations (Student Residuals, Cook's D, DFFITS, DFBETAS)
- Explain options for handling influential observations
- Identify collinearity problems by examining REG procedure output
- Use MODEL statement options to diagnose collinearity problems (VIF, COLLIN, COLLINOINT)
Perform logistic regression with the LOGISTIC procedure
- Identify experiments that require analysis via logistic regression
- Identify logistic regression assumptions
- logistic regression concepts (log odds, logit transformation, sigmoidal relationship between p and X)
- Use the LOGISTIC procedure to fit a binary logistic regression model (MODEL and CLASS statements)
Optimize model performance through input selection
- Use the LOGISTIC procedure to fit a multiple logistic regression model
- LOGISTIC procedure SELECTION=SCORE option
- Perform Model Selection (STEPWISE, FORWARD, BACKWARD) within the LOGISTIC procedure
Interpret the output of the LOGISTIC procedure
- Interpret the output from the LOGISTIC procedure for binary logistic regression models: Model Convergence section
- Testing Global Null Hypothesis table
- Type 3 Analysis of Effects table
- Analysis of Maximum Likelihood Estimates table
- Association of Predicted Probabilities and Observed Responses
Score new data sets using the LOGISTIC and PLM procedures
- Use the SCORE statement in the PLM procedure to score new cases
- Use the CODE statement in PROC LOGISITIC to score new data
- Describe when you would use the SCORE statement vs the CODE statement in PROC LOGISTIC
- Use the INMODEL/OUTMODEL options in PROC LOGISTIC
- Explain how to score new data when you have developed a model from a biased sample
Identify the potential challenges when preparing input data for a model
- Identify problems that missing values can cause in creating predictive models and scoring new data sets
- Identify limitations of Complete Case Analysis
- Explain problems caused by categorical variables with numerous levels
- Discuss the problem of redundant variables
- Discuss the problem of irrelevant and redundant variables
- Discuss the non-linearities and the problems they create in predictive models
- Discuss outliers and the problems they create in predictive models
- Describe quasi-complete separation
- Discuss the effect of interactions
- Determine when it is necessary to oversample data
Use the DATA step to manipulate data with loops, arrays, conditional statements and functions
- Use ARRAYs to create missing indicators
- Use ARRAYS, LOOP, IF, and explicit OUTPUT statements
Improve the predictive power of categorical inputs
- Reduce the number of levels of a categorical variable
- Explain thresholding
- Explain Greenacre's method
- Cluster the levels of a categorical variable via Greenacre's method using the CLUSTER procedure
- METHOD=WARD option
- FREQ, VAR, ID statement
- Use of ODS output to create an output data set
- Convert categorical variables to continuous using smooth weight of evidence
Screen variables for irrelevance and non-linear association using the CORR procedure
- Explain how Hoeffding's D and Spearman statistics can be used to find irrelevant variables and non-linear associations
- Produce Spearman and Hoeffding's D statistic using the CORR procedure (VAR, WITH statement)
- Interpret a scatter plot of Hoeffding's D and Spearman statistic to identify irrelevant variables and non-linear associations
Screen variables for non-linearity using empirical logit plots
- Use the RANK procedure to bin continuous input variables (GROUPS=, OUT= option; VAR, RANK statements)
- Interpret RANK procedure output
- Use the MEANS procedure to calculate the sum and means for the target cases and total events (NWAY option; CLASS, VAR, OUTPUT statements)
- Create empirical logit plots with the GPLOT procedure
- Interpret empirical logit plots
Apply the principles of honest assessment to model performance measurement
- Explain techniques to honestly assess classifier performance
- Explain overfitting
- Explain differences between validation and test data
- Identify the impact of performing data preparation before data is split
Assess classifier performance using the confusion matrix
- Explain the confusion matrix
- Define: Accuracy, Error Rate, Sensitivity, Specificity, PV+, PV-
- Explain the effect of oversampling on the confusion matrix
- Adjust the confusion matrix for oversampling
Model selection and validation using training and validation data
- Divide data into training and validation data sets using the SURVEYSELECT procedure
- Discuss the subset selection methods available in PROC LOGISTIC
- Discuss methods to determine interactions (forward selection, with bar and @ notation)
- Create interaction plot with the results from PROC LOGISTIC
- Select the model with fit statistics (BIC, AIC, KS, Brier score)
Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
- Explain and interpret charts (ROC, Lift, Gains)
- Create a ROC curve (OUTROC option of the SCORE statement in the LOGISTIC procedure)
- Use the ROC and ROCCONTRAST statements to create an overlay plot of ROC curves for two or more models
- Explain the concept of depth as it relates to the gains chart
Establish effective decision cut-off values for scoring
- Illustrate a decision rule that maximizes the expected profit
- Explain the profit matrix and how to use it to estimate the profit per scored customer
- Calculate decision cutoffs using Bayes rule, given a profit matrix
- Determine optimum cutoff values from profit plots
- Given a profit matrix, and model results, determine the model with the highest average profit
Note: All 22 main objectives will be tested on every exam. The 126 expanded objectives are provided for additional explanation and define the entire domain that could be tested.
Best Value! Save 37%.
Statistical Business Analyst Certification Package
Available in U.S. and Canada
Statistical Business Analyst Certification
- View the sample questions for this exam.
- Practice your skills with the SAS Certification Practice Exam: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling (PE-240P)
- Access SAS software through the SAS University Edition.
More information:Contact the SAS Global Certification Program at firstname.lastname@example.org or 800-727-0025.
Registration Options:Visit Pearson VUE to register online. Candidates may not register directly at a Pearson VUE testing facility. A minimum of 24 hours is required for registration for returning candidates. First-time candidates require additional time.
Visit www.pearsonvue.com/sas. Follow these easy steps once on the site:
- Attention first-time users:
You must "create" a new Web account within Pearson VUE before you can schedule a SAS exam. This can take up to two business days based on information provided to produce your username and password needed for exam registration. You will not have a SAS Candidate ID until after you have scheduled a SAS exam. It will be automatically assigned to you and sent via email.
- Returning users:
If you have previously taken a SAS exam with Pearson VUE and created a Web account, you can use the "Sign In" to register for an exam. If you do not remember your sign-in information, there are links within Pearson VUE to help obtain this information.
Testing LocationsLocations for testing can be found at www.pearsonvue.com/sas under "Find a test location." During registration, you will chose a location to take your exam.
SAS offers monthly exam sessions in Cary, NC and at some US conferences. For a SAS-sponsored US exam session, visit SAS-sponsored Testing Events in the US. For SAS-sponsored testing outside the US, please contact your local SAS office.
Exam PricingWithin North America and India, the fees associated with an exam offered through Pearson VUE is $180 USD.
Certification exam prices are subject to change. In some countries, different pricing and additional taxes may apply. Please visit www.pearsonvue.com/sas for exam pricing in your country.
- To cancel or reschedule your test appointment, visit www.pearsonvue.com/sas and select 'Cancel a Test' or 'Reschedule a Test.' Tests must be canceled more than 24 hours before the scheduled exam appointment time. Canceling with less than 24 hours' notice will forfeit your exam fee.
- Customers who do not appear for a scheduled exam forfeit the full exam fee. If the exam fee was paid with a voucher, the voucher number will be invalidated and unavailable for future use.
Retake PolicyCandidates may attempt each certification exam up to five times in a 12-month period, waiting a minimum of 14 days between attempts. Exam charges are incurred for each exam attempt. Exams that do not comply with this retake policy will be considered invalid and will not be eligible for refund and/or a certification credential. Once a passing score is achieved on a specific exam, no further attempts are allowed on that exam.
Candidate AgreementCandidates are encouraged to review the SAS Institute Inc. Global Certification Program Candidate Agreement prior to their exam day.
Arriving at the test center: Candidates should plan to arrive 15 minutes before their scheduled exam time. Candidates arriving more than 15 minutes late are not guaranteed exam availability or a refund.
Reference materials: To maintain the security of the test environment, candidates are not permitted to bring reference materials of any kind into the testing center.
Personal items: The only items allowed in the testing area are your identification. Please leave any backpacks, laptops, briefcases and other personal items at home. If you have personal items that cannot be left behind (such as purses), the testing center may have lockers available for use. No cameras, cell phones, audio players, or other electronic devices are allowed during exam sessions. Please refer to Pearson VUE Candidate Rules Agreement for more information.
All notes will be collected at the end of testing and no material may be removed from the testing event.
Score ReportYou will receive an immediate pass/fail score upon completion of your exam attempt at your testing facility. The score report will display the percentage of items in each section that you answered correctly for your exam. Please note: These section scores are calculated on a per section basis and cannot be used in determining your total score. They are provided to you for descriptive purposes only.
Welcome E-mail and CertificateIf you pass your exam and meet all requirements for this credential, you will receive an e-mail from SAS with instructions providing access to your certificate and logo through the Certification Records Management System. This e-mail will be sent to the e-mail address you provided to Pearson VUE at exam registration. Some individual firewalls may send this e-mail to your junk folder. Please allow at least one week from your exam date to receive your e-mail.
Within Certification Records Management system, your certificate can be accessed on the left navigation bar under "Printable Documents." To print your certificate, your pop-up blocker should be disabled before clicking the "Print Now" button. Click on "Print Now" and your certificate will open in a new window where you can download and/or print.
Certain credentials require more than one exam to earn the credential. We encourage you to visit credentials and exams for more information.
Public Registry of Certified ProfessionalsA Public Registry of SAS Certified Professionals is maintained within the SAS Certification Records Management system. If you do not wish for your name to appear in the Public Registry of SAS Certified Professionals, you can choose to be excluded by updating your personal information in the SAS Certification Records Management system.
Once you earn your credential, you'll enjoy these perks:
- digital badge to share your success
- 20% off SAS training and books