Good time to pass A00-240 SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam today, we have released new A00-240 study guide with valid exam questions and answers to help you complete the Statistical Business Analyst exam. Valid Statistical Business Analyst Certification Exam A00-240 Study Guide from Killtest was written by Killtest great team, who spent a lot time and energy to complete all real A00-240 exam questions and also, they verified all the answers. Passing A00-240 exam is guaranteed by Killtest team after reading Valid Statistical Business Analyst Certification Exam A00-240 Study Guide.

A00-240 Statistical Business Analyst Exam Issued By SAS For SAS professionals

We know, A00-240 Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam is issued by SAS. Today, SAS is a leader in business analytics, data warehousing and data mining, which has gone on to develop a solid customer base in the banking and pharmaceutical industries as well as in academia and at numerous agencies at all levels of government. 

Currently, there are 7 categories with 28 credentials in SAS Global Certification Program, all certifications covered below are based on SAS 9.4:

● Foundation Tools

● Advanced Analytics

● Business Intelligence and Analytics

● Data Management

● Administration

● JMP

● Partners

SAS Foundation Tools Certifications

SAS Foundation Tools Certifications aim at SAS professionals whose workdays revolve around writing and managing SAS programs. SAS currently offers four Foundation Tools certifications:

SAS Certified Professional: Advanced Programming Using SAS 9.4

SAS Certified Clinical Trials Programmer Using SAS 9

SAS Certified Specialist: Base Programming Using SAS 9.4

SAS Certified Associate: Programming Fundamentals Using SAS 9.4

SAS Advanced Analytics Certifications

SAS Advanced Analytics Certifications are designed for SAS professionals who gather, manipulate and analyze big data using SAS tools, run reports and make business recommendations based on complex models. There are 8 Advanced Analytics certifications:

SAS Certified Data Scientist Using SAS 9

SAS Certified Advanced Analytics Professional Using SAS 9

SAS Certified Predictive Modeler Using SAS Enterprise Miner 14

SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling

AI and Machine Learning Professional

SAS Certified Specialist: Machine Learning Using SAS Viya 3.4

SAS Certified Specialist: Forecasting and Optimization Using SAS Viya 3.4

Natural Language & Computer Vision Specialist

SAS Business Intelligence and Analytics Certifications

SAS Business Intelligence and Analytics certifications are designed for IT professionals who create interfaces and reports for SAS 9 or who use SAS Visual Analytics routinely. There are 3 SAS Business Intelligence and Analytics certifications:

SAS Certified BI Content Developer for SAS 9

SAS Certified Visual Modeler Using SAS Visual Statistics 7.4

Visual Business Analyst

SAS Data Management Certifications

Professionals whose workdays (or career aspirations) revolve more around managing data and platforms rather than deep statistics, analysis and modeling will gravitate to data management credentials. Currently, there are 4 Data Management certifications:

SAS Certified Big Data Professional Using SAS 9

SAS Certified Data Integration Developer for SAS 9

SAS Certified Data Quality Steward for SAS 9

Data Curation for SAS Data Scientists

SAS Administration Certifications

SAS Administration Certifications are designed for professionals responsible for supporting the SAS Business Analytics platform from installation through day-to-day maintenance. It has a single credential, the SAS Certified Platform Administrator for SAS 9. Candidates must know how to set up folders, manage user accounts, monitor system performance, apply security techniques, perform backups and complete other administrative tasks.

SAS JMP Certifications

SAS JMP is data analysis and visualization software that allows users to explore, mine and share data analyses in a graphical format. There are 3 exams in this category:

JMP Certified Specialist: JMP Scripting Using JMP 14

JMP Design and Analysis of Experiments Using JMP 14

JMP Statistical Thinking for Industrial Problem Solving

SAS Partners Certifications

SAS offers credential programs for certified SAS resellers, VARs, and consultants though its partner program. There are 5 partner credentials available to SAS partners:

SAS Certified Deployment Specialist for Visual Analytics 7.3

SAS Certified Technical Specialist for Visual Analytics 7.4

SAS Certified Architecture and Design Specialist for SAS Grid Manager 9.4

SAS Certified Deployment and Implementation Specialist for SAS Grid Manager 9.4

SAS Certified Platform Upgrade Specialist for SAS 9.4

A00-240 SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling exam is one of SAS Advanced Analytics Certifications. It is designed for SAS professionals who use SAS/STAT software to conduct and interpret complex statistical data analysis.

SAS Certification A00-240 Exam Is Administered By SAS and Pearson VUE

Completing Statistical Business Analyst Certification requires you to pass A00-240 SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam. A00-240 exam contains 60 scored multiple-choice and short-answer questions. Candidates must achieve score of 68 percent correct to pass. SAS Certification A00-240 exam is administered by SAS and Pearson VUE, it needs to be completed in 2 hours.

More, A00-240 exam tests your skills in five sections:

A00-240 Study Guide Is Valid For Statistical Business Analyst Exam

Understanding A00-240 exam outline and details is the key to prepare for A00-240 exam, and choosing A00-240 study guide is great for passing SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam. A00-240 study guide is valid for your Statistical Business Analyst exam, you can check A00-240 free demo questions from Killtest first.

In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

A. Training: 50% Validation: 0% Testing: 50%

B. Training: 100% Validation: 0% Testing: 0%

C. Training: 0% Validation: 100% Testing: 0%

D. Training: 50% Validation: 50% Testing: 0%

Answer: D

A confusion matrix is created for data that were oversampled due to a rare target.

What values are not affected by this oversampling?

A. Sensitivity and PV+

B. Specificity and PV

C. PV+ and PV

D. Sensitivity and Specificity

Answer: D

An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.

What is the purpose of the training data set?

A. To provide an unbiased measure of assessment for the final model.

B. To compare models and select and fine-tune the final model.

C. To reduce total sample size to make computations more efficient.

D. To build the predictive models.

Answer: A

When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for handling the mean imputation?

A. The sample means from the validation data set are applied to the training and test data sets.

B. The sample means from the training data set are applied to the validation and test data sets.

C. The sample means from the test data set are applied to the training and validation data sets.

D. The sample means from each partition of the data are applied to their own partition.

Answer: B

An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.

Which statement and option combination will generate these statistics?

A. Score data=valid1 out=roc;

B. Score data=valid1 outroc=roc;

C. mode1 resp(event= '1') = gender region/outroc=roc;

D. mode1 resp(event"1") = gender region/ out=roc;

Answer: B

In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)

A. Simple random sampling without replacement

B. Simple random sampling with replacement

C. Stratified random sampling without replacement

D. Sequential random sampling with replacement

Answer: A,C

The total modeling data has been split into training, validation, and test data.

What is the best data to use for model assessment?

A. Training data

B. Total data

C. Test data

D. Validation data

Answer: D

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. It violates assumptions of the model.

B. It requires extra computational effort and time.

C. It omits the training (and test) data sets from the benefits of the cleansing methods.

D. There is no ability to compare the effectiveness of different cleansing methods.

Answer: D

A company has branch offices in eight regions. Customers within each region are classified as either "High Value" or "Medium Value" and are coded using the variable name VALUE. In the last year, the total amount of purchases per customer is used as the response variable.

Suppose there is a significant interaction between REGION and VALUE.

What can you conclude?

A. More high value customers are found in some regions than others.

B. The difference between average purchases for medium and high value customers depends on the region.

C. Regions with higher average purchases have more high value customers.

D. Regions with higher average purchases have more medium value customers.

Answer: B

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. test

B. adjust

C. var

D. hovtest

Answer: D