sas analytics

SAS Analytics, Data analysis using SASSAS Analytics, Data analysis using SAS

Duration:60 hours

course fee :Rs 30,000/-

More detail visit www.iisastr.com

phone no:9312506496

Course content

1. Introduction to the SAS Language

1.1 Introduction

1.2 Basic Language: Rules and Syntax

1.3 Creating SAS Data Sets

1.4 The INPUT Statement

1.5 SAS Data Step Programming Statements Their Uses

1.6 Data Step Processing

1.7 More on INPUT Statement

1.7.1 Use of Pointer controls

1.7.2 The trailing@ line-hold specifier

1.7.3 The trailing@ @ line-hold specifier

1.7.4 Uses of RETAIN statement

1.7.5 The use of line pointer controls

1.8 Using SAS Procedures

2. More on SAS Programming and some Applications

2.1 More on the DATA and PROC STEPS

2.1.1 Reading data from files

2.1.2 Combing SAS data sets

2.1.3 Saving and retrieving permanent SAS data Sets

2.1.4 User- defined in formats and formats

2.1.5 Creating SAS data sets in procedure steps

2.2 SAS Procedures for Computing Statistics

2.2.1 The UNIVARIATE procedures

2.2.2 The FREQ procedure

2.3 Some Useful Base SAS Procedures

2.3.1 The PLOT procedures

2.3.2 The CHART procedures

2.3.3 The TABULATE procedure

3. Statistical Graphics Using SAS / GRAPH

3.1 INTRODUCTINS

3.2 An INTRODUCTINS to SAS / GRAPH

3.2.1 Useful SAS / GRAPH procedures

GPLOT procedure

GCHART procedure

3.2.2 Writing SAS/Graph programs

3.3 Quantile Plots

3.4 Empirical Quantile- Quantile Plots

3.5 Theoretical Quantile- Quantile Plots or probability Plots

3.6 Profile Plots of Means or Interaction Plots

3.7 Two Dimensional Scatter Plots and Scatter Plot Matrices

3.7.1 Two –Dimensional Scatter Plots

3.7.2 Scatter plots Matrices

3.8 Histograms Bar Charts and Pie Charts

3.9 Other SAS Procedures for High- resolutions Graphics

4. Statistical Analysis of Regression Models

1. An Introduction to Simple Linear Regression

4.1.1 Simple linear regression using PROC REG

4.1.2 Lack of fit test using PROC ANOVA

4.1.3 Diagnostics use of case statistics

4.1.4 Predictions of new y values using regressions

4.2 An Introduction to Multiple Regression Analysis

4.2.1 Multiple regression analysis using PROC REG

4.2.2 Case Statistics and residual analysis

4.2.3 Residual Plots

4.2.4 Examining relationships among regression variables

4.3 Types of Sums of Squares Computed in PROC REG and PROC GLM

4.3.1 Model comparison technique and extra sum of squares

4.3.2 Types of sums of squares in SAS

4.4 Subset selection using PROC REG for Model selection

4.4.1 Subset selection using PROC REG

4.4.2 Other options available in PROC REG for model selection

4.5 Inclusion of squared Terms Product terms in Regression Models

4.5.1 Including interaction terms in the model

4.5.2 Comparing slopes of regression lines using interaction

4.5.3 Analysis of models with higher-order terms with PROC REG

5. Analysis of Variance Model

5.1 Introduction

5.1.1 Treatment Structure

5.1.2 Experimental Designs

5.1.3 Linear Models

5.2 One-way Classification

5.2.1 Using PROC ANOVA to analyze one-way Classifications

5.2.2 Making preplanned (or a priori) comparisons using PROC GLM

5.2.3 Testing orthogonal polynomials using contrasts

5.3 One-Way Analysis of Covariance

5.3.1 Using PROC GLM to perform one-way covariance analysis

5.3.2 One-way covariance analysis: Testing for equal slopes

5.4 A two Factorial in a Completely Randomized Design

5.4.1 Analysis of a two-way factorial using PROC GLM

5.4.2 Residual Analysis of Interaction

5.5 Two-Way Factorial: Analysis of Interaction

5.6 Two-Way Factorial: Unequal Sample sizes

5.7 Two way Classification: Randomized Complete Block Design

5.7.1 Using PROC GLM to analyze a RCBD

5.7.2 Using PROC GLM to test for non additivity

6. Analysis of Variance: Random and Mixed Effects Models

6.1 Introduction

6.2 One-way Random Effects Model

6.2.1 Using PROC GLM to analyze one-way Random Effects Models

6.2.2 Using PROC MIXED to analyze one-way Random Effects Models

6.3 Two –way Crossed Random Effects Model

6.3.1 Using PROC GLM and PROC MIXED to analyze two –way Crossed Random Effects Model

6.3.2 Randomized complete block design: Blocking when treatment factors are random

6.4 Two-Way Nested Random Effects Model

6.4.1 Using PROC GLM to analyze two-way nested random effects models

6.4.2 Using PROC MIXED to analyze two-way Nested Random Effects Models

6.5 Two-way Mixed Effects Models

6.5.1 Two-way Mixed Effects Models: Randomized Complete Blocks Design

6.5.2 Two-way Mixed Effects Models: Crossed Classification

6.5.3 Two-way Mixed Effects Models: Nested Classification

6.6 Models with Random and Nested Effects for More Complex Experiments

6.6.1 Models for nested factorials

6.6.2 Models for split-plot experiments

6.6.3 Analysis of split-plot experiments using PROC GLM

6.6.4 Analysis of split-plot experiments using PROC MIXED

• Logistic Regression

• Factor Analysis(Principal component)

Fees: INR 11,000

SAS is one of the world’s most widely used statistical software. With our SAS training learn how to read databases,

conduct variable transformations and simple statistical analyses, and how to integrate SAS with other databases.

One of our most popular courses, ATI has trained in excess of 4000 students in SAS over the last 5 years

Introduction to Analytics

Introduction to SAS, GUI

Types of Libraries, Creating

Variable Attributes

o Name, Type, Format, Informat, Label

Introduction to Data steps and Proc steps

DATA Understanding

o Reading, Importing, Exporting and Copying Data

Conditional Statements (Where, If, If then Else)

Appending, Merging and Sorting Datasets

Proc steps like " Proc Means, Proc Freq, Proc Sort

Output Delivery System (ODS)

SAS Functions and Options

List Input, Delimiters, Reading missing Values, and non standard values

Do loops

Generating Data

o Execution

o Output Statements

o Nesting Do loops

o Do While and Do Until Statement

Arrays

o Dimensions

o Array elements and Range

o Proc report

Introduction to Data base, Relational Data base concepts

Proc SQL, Data integrity Constraints, Creating table and Inserting Values

Proc SQL codes to

o Retrieve & Summarize data

o Group, Sort & Filter

o Using Joins

o Indexes

Macros

o Defining and calling a macro

o Macro Parameters and Variables

o Global and Local Variables

Analyst

Progressive Digital Media GroupOctober 2011 – February 2013 (1 year 5 months) Hyderabad

Research:

To identify and monitor competitors and research market conditions by constantly tracking the changes in the industry. To analyze and incorporate customer preferences, demographics and buying habits, that influences the market dynamics. To undertake secondary research where data is collected from trade magazines, trade associations, statistical offices, company statements and trade departments, amongst other sources. Interpret findings and draw conclusions from preliminary research. To analyze the key market metrics through data sanity checks and verifies if it is in trend with the market. To initiate and complete the permission process for sourcing and attribution of information whenever necessary. To conduct cross-country comparison and also check if the data is in line. Authoring reports address client centric requirements.

Analytics:

Running descriptive statistics and statistical analysis including T-Test, ANOVA, Time Series Forecasting, Regression and Cluster Analysis by using SAS and SPSS Import and Export of Data, Variable creation, String and Date function, keep and Drop variables. Conditional execution (if then, Else if, Else, do loop, where conditions), Macro, Array, Sorting, Merging by using SAS and SPSS Comprehensive knowledge of Advanced Excel including conditional Formatting, Advance filtering, Cell Referencing, Text functions, What if Analysis, Vlookup, If statements, Data validation, Pivot Table, Solver, Charts, Macro, VBA, etc. Comprehensive knowledge of MS PowerPoint including building blocks of a presentation, themes and styles, tables, charts, graphs and smart art, animation Gained comprehensive knowledge of SQL including Basic structures SQL, basic commands, Grouping, Ordering, Union, Intersection, Different types of Joining (natural join, outer join) etc Sound understanding of strategic tools like Porter’s 5 forces, SWOT, PEST, BCG, GE, Value chain analysis, etc

Adeptness in Analytics using Traditional and Advanced Statistical applications in Banking, Insurance, Market Research, CPG/Retail, Hi-Technology.

• International Exposure:Interacting with Top Executive ManagementWorked with popular Marketing scientists around the Globe.Trained in R programming & Analytics in Minneapolis, MN, USA.Presenter/Co-Author in multiple International Conferences

• Traditional/Advanced Analytic Methods:Linear, Non Linear, Logistic, Probit, Multinomial Logit, Log Linear Regression, Pricing Analysis (with/out competitive context), Ranking Analysis/Preference scores, Text Perception, Image Perception/Advertising Research, Shapley Value/Game Theory, different Product Optimization Techniques which suits to real marketing decisions, Cannibalisation of Products, Random Forest, Decision Trees, CART, Key Driver Analysis, Derived Importance , Brand Association & Mapping techniques.

Analytics services and Product Development

• Technical Expertise:R, hadoop, mapreduce, SSRS, SPSS, SAS/SQL, SawTooth, Excel, Quantum, Quanvert.

Extensive knowledge in Programming, Data Analytics, Data Mining & Weighting using different programming tools

• Client Interaction:Interaction with Top Executive Management Global client interaction, Analysis findings, recommendations and preparing Executive summaries, explaining complex findings in layman terms

• Management & Training:Key driver in motivating team towards the success of OrganisationPeople ManagementBasic and Advanced Analytic Methods Trainer

http://www.linkedin.com/company/516464?goback=.fps_PBCK_ANUSHA+VALLURU_*1_*1_*1_*1_*1_*1_*2_*1_Y_*1_*1_*1_false_1_R_*1_*51_*1_*51_true_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2&trk=prof-exp-company-name

http://www.linkedin.com/search?search=&title=Analyst&sortCriteria=R&keepFacets=true&currentTitle=CP&goback=.fps_PBCK_ANUSHA+VALLURU_*1_*1_*1_*1_*1_*1_*2_*1_Y_*1_*1_*1_false_1_R_*1_*51_*1_*51_true_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2_*2&trk=prof-exp-title

R Programming TrainerCross Functional Trainer

SAS/BASE

HISTORY OF SAS --------------------------------------------------------------------------------------------1BASIC THEORY & RULES ETC...--------------------------------------------------------------------------1SAS WINDOWING ENVIRONMENT-----------------------------------------------------------------------2CREATION OF LIBRARIES-----------------------------------------------------------------------------------2SAS PROGRAMMING (BRIEFLY-----------------------------------------------------------------------------2 - DATASTEP - PROC STEPWAYS TO READ DATA (BRIEFLY) ----------------------------------------------------------------------2BACK END PROCESS------------------------------------------------------------------------------------------2INSTALLATION PROCESS ----------------------------------------------------------------------------------3DATASTEP

INFORMATS & FORMATS------------------------------------------------------------------------------------4DATA & OPTIONS---------------------------------------------------------------------------------------------4INFILE & OPTIONS--------------------------------------------------------------------------------------------5INPUT & OPTIONS--------------------------------------------------------------------------------------------6, 7DATALINES & OPTIONS-------------------------------------------------------------------------------------8DATES-------------------------------------------------------------------------------------------------------------8SUM STATEMENT----------------------------------------------------------------------------------------------9ATTRIB STATEMENT & INDIVIDUAL ATTRIBUTES--------------------------------------------------9RETAIN STATEMENT----------------------------------------------------------------------------------------9IF, IF/THEN/ELSE STATEMENT--------------------------------------------------------------------------10WHERE STATEMENT----------------------------------------------------------------------------------------10DO, DO ITERATIVE, DO UNTIL & DO WHILE -------------------------------------------------------11CONCATENATION & INTEREAVING---------------------------------------------------------------------12MERGE & UPDATE--------------------------------------------------------------------------------------------12 FUNCTIONS

- DATE FUNCTIONS-----------------------------------------------------------------------------------------13, 14 - CHARACTER FUNCTIONS -------------------------------------------------------------------------------15, 16 - NUMERIC FUNCTIONS------------------------------------------------------------------------------------17, 18

ARRAYS---------------------------------------------------------------------------------------------------------19, 20OTHERS MISSING CONCEPTS----------------------------------------------------------------------------21REVIEW OF DATASTEP------------------------------------------------------------------------------------22EXAM & DISCUSSION---------------------------------------------------------------------------------------23PROC STEPUTILITY PROCEDURES

- PROC IMPORT-----------------------------------------------------------------------------------------------24 - PROC EXPORT-----------------------------------------------------------------------------------------------24 - PROC CONTENTS-------------------------------------------------------------------------------------------24 - PROC APPEND-----------------------------------------------------------------------------------------------25 - PROC SORT--------------------------------------------------------------------------------------------------25 - PROC COPY--------------------------------------------------------------------------------------------------26 - PROC DATASETS-------------------------------------------------------------------------------------------26 - PROC COMPARE---------------------------------------------------------------------------------------------26 - PROC TRANSPOSE------------------------------------------------------------------------------------------27

- PROC FORMAT-----------------------------------------------------------------------------------------------27 - PROC SETINIT-----------------------------------------------------------------------------------------------27 - PROC PWENCODE -----------------------------------------------------------------------------------------28 - PROC OPTIONS --------------------------------------------------------------------------------------------28 - PROC RANK -------------------------------------------------------------------------------------------------28 - PROC CPORT------------------------------------------------------------------------------------------------29 - PROC CIMPORT---------------------------------------------------------------------------------------------29 - PROC -----------------------------------------------------------------------------------------

REPORTING PROCEDURES

- PROC PRINT-------------------------------------------------------------------------------------------------30 - PROC TABULATE------------------------------------------------------------------------------------------30 - PROC REPORT----------------------------------------------------------------------------------------------31 - _NULL_ REPORT-------------------------------------------------------------------------------------------32

SAS/GRAPHS & ODS CONCEPTS

- PROC GPLOT------------------------------------------------------------------------------------------------33 - PROC GCHART----------------------------------------------------------------------------------------------33 - ODS------------------------------------------------------------------------------------------------------------34SAS/STAT

- BASICS OF STATISTICS---------------------------------------------------------------------------------35

STATISTICAL PROCEDURES

- PROC MEANS -----------------------------------------------------------------------------------------------36 - PROC SUMMARY--------------------------------------------------------------------------------------------36 - PROC UNIVARIATE ---------------------------------------------------------------------------------------37 - PROC FREQ -------------------------------------------------------------------------------------------------37 - PROC CORR -------------------------------------------------------------------------------------------------38 - PROC REG----------------------------------------------------------------------------------------------------38 - PROC ANOVA-----------------------------------------------------------------------------------------------38 - T-TEST -------------------------------------------------------------------------------------------------------39 - Chi SQUARE -------------------------------------------------------------------------------------------------39 - HYPOTHESIS------------------------------------------------------------------------------------------------40 - OTHER STATISTICAL PROCEDURES ----------------------------------------------------------------41

REVIEW OF PROC STEP-------------------------------------------------------------------------------------42

EXAM & DISCUSSION ---------------------------------------------------------------------------------------43SAS/ACCESS

BASIC THEORY OF SAS/ACCESS ------------------------------------------------------------------------44

WAYS TO ACCESS DATA FROM DIFFERENT SOURCES LIKE NOTEPADS, EXCEL SHEETS, MS-ACCESS, ORACLE, DB2, SYBASE AND TERRADATA etc… - PROC IMPORT --------------------------------------------------------------------------------------------- () - INFILE STATEMENT-------------------------------------------------------------------------------------- () - SQL PASS THRU QUERY---------------------------------------------------------------------------------45 - LIBNAME STATEMEN -------------------------------------------------------------------------------------45 - PROC DBLOAD----------------------------------------------------------------------------------------------46

- PROC ACCESS-----------------------------------------------------------------------------------------------46

SQL (PROC SQL) ---------------------------------------------------------------------------------------47, 48, 49, 50, 51,REVIEW, EXAM & DISCUSSION --------------------------------------------------------------------------52 SAS/MACROS---------------------------------------------------------------------------------------------53, 54, 55, 56, 57REVIEW, EXAM & DISCUSSION---------------------------------------------------------------------------58

PERFORMANANCE TUNING---------------------------------------------------------------------------------59TESTING/DEBUGGING TECHNIQUES------------------------------------------------------------------- 60

PROJECT (REAL TIME) -----------------------------------------------------------------------------1MONTH

PRACTICECODING ON REAL TIME DATAINTERVIEW QUESTIONSRESUME PREPARATIONWRITTEN TESTSMOCK INTERVIEWSCONSULTIN

Fees: INR 16,500

The Advanced Analytics course introduces participants to fundamental concepts of statistics, and guides them all the

way to building predictive models using multiple linear and logistic regressions. All the topics are explained with the

help of hands-on practice with live case studies and data, enabling a deeper understanding of the underlying

concepts of analytics.

Introduction to analytics

o Need for analytics

o Analytics use in different industries

o Challenges in adoption of analytics

o Overview of Course Contents

Data understanding

o Data types (Nominal, Ordinal, Interval and Ratio)

Descriptive statistics

o Tabular & Graphical Method

o Summary statistics

Introduction to some statistical terminologies and inferences

o Population, Sample and Random variables

o Point and Interval Estimations

o Probability

o Discrete/Continuous Probability Distributions

Hypothesis Testing

o Importance of formulating and validating the hypothesis

o Formulation of hypothesis (Null and alternate)

o Testing association and differences

o Statistical significance and test statistic

o Level of significance

Z-Test, T-Test, Chi-Square test, ANOVA

Parametric & Non-Parametric test

Correlation & Regression

Linear Regression

o Case Study on Multiple Regression

Logistic Regression

o Case Study on Logistic Regression

Cluster Analysis

o Case Study on Cluster Analysis

Factor Analysis

o Case Study on Factor Analysis

programming for SAS 9

Item 1The following program is submitted.

data WORK.TEST;

input Name $ Age;

datalines;

John +35

;

run;

Which values are stored in the output data set?

A. Name Age

B. ---------------------

C. John 35

D. Name Age

E. ---------------------

F. John (missing value)

G. Name Age

H. ---------------------

I. (missing value) (missing value)

J. The DATA step fails execution due to data errors.correct_answer = "A"

Item 2Given the SAS data set WORK.ONE:

Id Char1

--- -----

182 M

190 N

250 O

720 P

and the SAS data set WORK.TWO:

Id Char2

--- -----

182 Q

623 R

720 S

The following program is submitted:

data WORK.BOTH;

merge WORK.ONE WORK.TWO;

by Id;

run;

What is the first observation in the SAS data set WORK.BOTH?

A. Id Char1 Char2

B. --- ----- -----

C. 182 M

D.

E. Id Char1 Char2

F. --- ----- -----

G. 182 Q

H.

I. Id Char1 Char2

J. --- ----- -----

K. 182 M Q

L.

M. Id Char1 Char2

N. --- ----- -----

O. 720 P S

P.correct_answer = "C"

Item 3Given the text file COLORS.TXT:

----+----1----+----2----+----

RED ORANGE YELLOW GREEN

BLUE INDIGO PURPLE VIOLET

CYAN WHITE FUCSIA BLACK

GRAY BROWN PINK MAGENTA

The following SAS program is submitted:

data WORK.COLORS;

infile 'COLORS.TXT';

input @1 Var1 $ @8 Var2 $ @;

input @1 Var3 $ @8 Var4 $ @;

run;

What will the data set WORK.COLORS contain?

A. Var1 Var2 Var3 Var4

B. ------ ------ ------ ------

C. RED ORANGE RED ORANGE

D. BLUE INDIGO BLUE INDIGO

E. CYAN WHITE CYAN WHITE

F. GRAY BROWN GRAY BROWN

G.

H. Var1 Var2 Var3 Var4

I. ------ ------ ------ ------

J. RED ORANGE BLUE INDIGO

K. CYAN WHITE GRAY BROWN

L.

M. Var1 Var2 Var3 Var4

N. ------ ------ ------ ------

O. RED ORANGE YELLOW GREEN

P. BLUE INDIGO PURPLE VIOLET

Q.

R. Var1 Var2 Var3 Var4

S. ------ ------ ------ ------

T. RED ORANGE YELLOW GREEN

U. BLUE INDIGO PURPLE VIOLET

V. CYAN WHITE FUCSIA BLACK

W. GRAY BROWN PINK MAGENTA

X.correct_answer = "A"

Item 4Given the SAS data set WORK.INPUT:

Var1 Var2

------ -------

A one

A two

B three

C four

A five


data WORK.ONE WORK.TWO;

set WORK.INPUT;

if Var1='A' then output WORK.ONE;

output;

run;

How many observations will be in data set WORK.ONE?

Enter your numeric answer. Do not add leading or trailing spaces to your answer.

correct_answer = "8"

Item 5The following SAS program is submitted:

data WORK.LOOP;

X = 0;

do Index = 1 to 5 by 2;

X = Index;

end;

run;

Upon completion of execution, what are the values of the variables X and Index in the SAS data set named WORK.LOOP?

A. X = 3, Index = 5B. X = 5, Index = 5C. X = 5, Index = 6D. X = 5, Index = 7

correct_answer = "D"


proc format;

value score 1 - 50 = 'Fail'

51 - 100 = 'Pass';

run;

Which one of the following PRINT procedure steps correctly applies the format?

A. proc print data = SASUSER.CLASS;

B. var test;

C. format test score;

D. run;

E.

F. proc print data = SASUSER.CLASS;

G. var test;

H. format test score.;

I. run;

J.

K. proc print data = SASUSER.CLASS format = score;

L. var test;

M. run;

N.

O. proc print data = SASUSER.CLASS format = score.;

P. var test;

Q. run;

R.correct_answer = "B"

Item 7This item will ask you to provide a line of missing code;

The SAS data set WORK.INPUT contains 10 observations, and includes the numeric variable Cost.

The following SAS program is submitted to accumulate the total value of Cost for the 10 observations:

data WORK.TOTAL;

set WORK.INPUT;

<insert code here>

Total=Total+Cost;

run;

Which statement correctly completes the program?

A. keep Total;

B. retain Total 0;

C. Total = 0;

D. If _N_= 1 then Total = 0;

correct_answer = "B"

Item 8This question will ask you to provide a line of missing code.

Given the following data set WORK.SALES:

SalesID SalesJan FebSales MarchAmt

------- -------- -------- --------

W6790 50 400 350

W7693 25 100 125

W1387 . 300 250


data WORK.QTR1;

set WORK.SALES;

array month{3} SalesJan FebSales MarchAmt;

<insert code here>

run;

Which statement should be inserted to produce the following output?

SalesID SalesJan FebSales MarchAmt Qtr1

------- -------- -------- -------- ----

W6790 50 400 350 800

W7693 25 100 125 250

W1387 . 300 250 550

A. Qtr1 = sum(of month{_ALL_});B. Qtr1 = month{1} + month{2} + month{3};C. Qtr1 = sum(of month{*});D. Qtr1 = sum(of month{3});

correct_answer = "C"

Item 9Given the following SAS error log

44 data WORK.OUTPUT;

45 set SASHELP.CLASS;

46 BMI=(Weight*703)/Height**2;

47 where bmi ge 20;

ERROR: Variable bmi is not on file SASHELP.CLASS.

48 run;

What change to the program will correct the error?

A. Replace the WHERE statement with an IF statementB. Change the ** in the BMI formula to a single *C. Change bmi to BMI in the WHERE statementD. Add a (Keep=BMI) option to the SET statement

correct_answer = "A"


data WORK.TEMP;

Char1='0123456789';

Char2=substr(Char1,3,4);

run;

What is the value of Char2?

A. 23B. 34C. 345D. 2345


SAS Advanced Programming for SAS 9

Item 1Given the following SAS data sets ONE and TWO:


proc sql;

select one.*, sales

from one right join two

on one.year = two.year;

quit;

Which one of the following reports is generated?

A.

B.

http://support.sas.com/certify/creds/samples.html#top

C.

D.


Item 2Given the following SAS data sets ONE and TWO:

The following SAS program is submitted creating the output table THREE:

data three;

merge one (in = in1) two (in = in2);

by num;

run;

Which one of the following SQL programs creates an equivalent SAS data set THREE?

A. proc sql;

B. create table three as

C. select *

D. from one full join two

E. where one.num = two.num;

F. quit;

G.

H. proc sql;

I. create table three as

J. select coalesce(one.num, two.num)

K. as NUM, char1, char2

L. from one full join two

M. where one.num = two.num;

N. quit;

O. proc sql;

P. create table three as

Q. select one.num, char1, char2

R. from one full join two

S. on one.num = two.num;

T. quit;

U. proc sql;

V. create table three as

W. select coalesce(one.num, two.num)

X. as NUM, char1, char2

Y. from one full join two

Z. on one.num = two.num;

AA. quit;



%let type = RANCH;

proc sql;

create view houses as

select *

from sasuser.houses

where style = "&type";

quit;

%let type = CONDO;

proc print data = houses;

run;

The report that is produced displays observations whose value of STYLE are all equal to RANCH.

Which one of the following functions on the WHERE clause resolves the current value of the macro variable TYPE?

A. GETB. SYMGETC. %SYMGETD. &RETRIEVE


Item 4The SAS data set SASDATA.SALES has a simple index on the variable DATE and a variable named REVENUE with no index.

In which one of the following SAS programs is the DATE index considered for use?

A. proc print data = sasdata.sales;

B. by date;

C. run;

D. proc print data = sasdata.sales;

E. where month(date) = 3;

F. run;

G. data march;

H. set sasdata.sales;

I. if '01mar2002'd < date < '31mar2002'd;

J. run;

K. data march;

L. set sasdata.sales;

M. where date < '31mar2002'd or revenue > 50000;

N. run;


Clinical Trials Programming Using SAS 9

Item 1What is the main focus of Good Clinical Practices (GCP)?

A. harmonized data collectionB. standard analysis practicesC. protection of subjectsD. standard monitoring practices


Item 2Vital Signs are a component of which SDTM class?

A. FindingsB. InterventionsC. EventsD. Special Purpose


Item 3Which option in the PROC EXPORT procedure overwrites an existing file?


A. NEWB. OVERWRITEC. REPLACED. KEEP


Item 4Given the following data set WORK.DEMO:

PTID Sex Age Height Weight

689574 M 15 80.0 115.5

423698 F 14 65.5 90.0

758964 F 12 60.3 87.0

653347 F 14 62.8 98.5

493847 M 14 63.5 102.5

500029 M 12 57.3 83.0

513842 F 12 59.8 84.5

515151 F 15 62.5 112.5

522396 M 13 62.5 84.0

534787 M 12 59.0 99.5

875642 F 11 51.3 50.5

879653 F 15 75.3 105.0

542369 F 12 56.3 77.0

698754 F 11 50.5 70.0

656423 M 16 72.0 150.0

785412 M 12 67.8 121.0

785698 M 16 72.0 110.0

763284 M 11 57.5 85.0

968743 M 14 60.5 85.0

457826 M 18 74.0 165.0


proc print data=WORK.DEMO(firstobs=5 obs=10);

where Sex='M';

run;

How many observations will be displayed?

A. 4B. 6C. 7D. 8


Item 5Given the following partial data set:

SUBJID SAF ITT OTH

101 1 . 1

103 1 1 1

106 1 1 1

107 1 . 1


proc format;

value stdypfmt

1="Safety"

2="Intent-to-Treat"

3="Other";

run;

data test;

set temp (keep=SUBJID ITT SAF OTH );

by subjid;

length STDYPOP $200;

array pop{*} SAF ITT OTH ;

do i=1 to 3;

if STDYPOP="" and pop{i}=1 then STDYPOP=put(i, stdypfmt.);

else if STDYPOP^="" and pop{i}=1 then STDYPOP = trim(STDYPOP)||"/"||put(i, stdypfmt.);

end;

run;

What is the value of STDYPOP for SUBJID=107?

correct_answer = "Safety/Other"


Given the data set WORK.STUDYDATA with the following variable list:

# Variable Type Len Label

2 DAY Char 8 Study Day

3 DIABP Num 8 Diastolic Blood Pressure

1 TRT Char 8 Treatment


proc means data=WORK.STUDYDATA noprint;

<insert code here>

class TRT DAY;

var DIABP;

output out=WORK.DIAOUT mean=meandp;

run;

WORK.DIAOUT should contain:

the mean diastolic blood pressure values for every day by treatment group the overall mean diastolic blood pressure for each treatment group

Which statement correctly completes the program to meet these requirements?A. where trt or trt*day;

B. types trt trt*day;

C. by trt day;

D. id trt day;



%let member1=Demog;

%let member2=Adverse;

%let Root=member;

%let Suffix=2;

%put &&&Root&Suffix;

What is written to the SAS log?

A. &member2

B. Adverse

C. &&&Root&Suffix

D. WARNING: Apparent symbolic reference ROOT2 not resolved.




proc format ;

value dayfmt 1='Sunday'

2='Monday'

3='Tuesday'

4='Wednesday'

5='Thursday'

6='Friday'

7='Saturday' ;

run ;

proc report data=diary ;

column subject day var1 var2 ;

<insert code here>

run ;

In the DIARY data set, the format DAYFMT is assigned to the variable DAY. Which statement will cause variable DAY to be printed in its unformatted order?

A. define day / order 'Day' ;

B. define day / order order=data 'Day' ;

C. define day / order noprint 'Day' ;

D. define day / order order=internal 'Day' ;


Item 9You are using SAS software to create reports that will be output in a Rich Text Format so that it may be read by Microsoft Word. The report will span multiple pages and you want to display a '(Continued)' text at the end of each page when a table spans multiple pages.

Which statement can you add to the SAS program to ensure the inclusion of the '(Continued)' text?

A. ods rtf file='report.rtf';

B. ods tagsets.rtf file='report.rtf';

C. ods tagsets.rtf file='report.rtf' break='Continued';

D. ods file open='report.rtf' type=rtf break='(Continued)';


Item 10What is the primary purpose of programming validation?

A. Ensure that the output from both the original program and the validation program match.B. Efficiently ensure any logic errors are discovered early in the programming process.C. Justify the means used to accomplish the outcome of a program and ensure its accurate

representation of the original data.D. Document all specifications pertaining to programmed output and ensure all were reviewed

during the programming process.correct_answer = "C"

Predictive Modeling Using SAS Enterprise Miner 7

Item 1

Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:


1. Set the Clustering method to Average.2. Run the Cluster node.

Use this project to answer the next two questions:

What is the Importance statistic for MTGBal (Mortgage Balance)?A. 0.32959B. 0.42541C. 0.42667D. 1.000000

correct_answer = "C" You must change the clustering method to average and run the cluster node first. Select view results and look in the output window and view the Variable Importance results.

What is the Cubic Clustering Criterion statistic for this clustering?A. 5.00B. 14.69C. 5862.76D. 67409.93

correct_answer = "B" Run the diagram flow and view the results. From the results window, select View -> Summary Statistics -> CCC Plot and mouse over where the data point and the line intersect. This will display the CCC statistic.

Item 21. Create a project named Insurance, with a diagram named Explore.2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\

workshop\Practice.3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has

insurance, 0= does not have insurance).4. Set the measurement level for the Target variable, Ins, to Binary.5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.6. All other variables should be set to Interval or Binary.7. Make sure that the default sampling method is random and that the seed is 12345.

Use this project to answer the next <b.seven< b="" style="color: rgb(51, 51, 51); font-family: Arial, Helvetica, Verdana, sans-serif; font-size: small; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 16px; orphans: auto; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;">questions. (Note: only 2 of 7 questions are displayed for this example)

The variable Branch has how many levels?A. 8B. 12C. 19D. 47

correct_answer = "C" This information can be obtained by viewing the PROC FREQ output.

What is the mean credit card balance (CCBal) of the customers with a variable annuity?

A. $0.00B. $8,711.65C. $9,586.55D. $11,142.45

correct_answer = "D" You can use a Stat Explore Node and view the output for the Descriptive Statistics for CCBal by level of the target variable.

SAS Platform Administration for SAS 9

Item 1The location of the repository manager physical files can be found in:

A. SAS Management Console.B. the metadata server's omaconfig.xml file.C. the foundation repository.D. the metadata server's sasv9.cfg file.


Item 2Every SAS platform implementation includes:

A. a foundation repository and a repository manager.B. a foundation repository and a custom repository.C. a custom repository and a repository manager.D. multiple project repositories.


Item 3Which procedure allows a platform administrator to update table metadata?

A. METAUPDATE_RULEB. METASELECTC. METATABLED. METALIB


Item 4Which statement regarding pre-assigned libraries is true?

A. Pre-assigned libraries reduce the initialization time for a workspace server.B. Pre-assigned libraries always connect to an RDBMS at server initialization.C. Pre-assigned libraries always connect to a base SAS library at server initialization.D. Pre-assigned libraries do not have to be identical across all SAS client applications.



Item 5A platform administrator needs to retrieve from the metadata a complete LIBNAME statement including the user ID and password.

To complete this task, the platform administrator must be connected to SAS Management Console with what type of user access in the metadata?

A. Access to the credentials associated with libraries created with the METALIB procedure.B. Access to credentials established by the LIBNAME engine.C. Access to credentials associated with users in the outbound login.D. Access to credentials for the authentication domain associated with the database server.


Item 6By default, which groups have WriteMetadata on the Foundation repository?

A. PUBLICB. SASUSERSC. ADMINISTRATORS ONLYD. SAS SYSTEM SERVICES ONLY


Item 7Given the following authorization settings for Library Sales2:

Library Sales2's parent folder has an explicit grant of RM for Mary. Library Sales2 has an explicit denial of RM for PUBLIC.

Which statement is true?A. Mary can see Library Sales2.B. Mary can see data flagged as PUBLIC in Library Sales2.C. Mary cannot see Library Sales2.D. Mary can see Library Sales2, but not any data flagged as PUBLIC.


Item 8Which statement is FALSE regarding the WriteMemberMetadata (WMM) permission?

A. By default, it mirrors the WriteMetadata permission.B. It only applies to folders.C. If WriteMetadata is granted, then you should not deny WMM.D. WMM is inherited from one folder to another folder.


Item 9Content has been exported from a SAS 9.1.3 environment into a SAS 9.2 development environment. After the export, the platform administrator attempts to promote an object from the SAS 9.2 development environment into a production environment.

What will be the result of this promotion attempt?

A. The promotion will not be allowed because objects from SAS 9.1.3 cannot be promoted to SAS 9.2.B. The promotion will not be allowed because objects in a development environment cannot be promoted

to a production environment.C. The promotion will be allowed assuming the object type is allowed for promotion.D. The promotion will not be allowed because objects exported from a previous environment cannot be

promoted.correct_answer = "C"

SAS Data Integration Developer for SAS 9

Item 1Which of the following servers is NOT a part of the platform for SAS Business Analytics server tier?

A. SAS Metadata ServerB. SAS Workspace ServerC. SAS/CONNECT ServerD. SAS Content Server


Item 2Which products are needed on the local host in order to access data from an MS Access Database using an ODBC Data Source name?

A. SAS/ACCESS interface to DSNB. SAS/ACCESS interface to MDBC. SAS/ACCESS interface to PC FilesD. SAS/ACCESS interface to ODBC


Item 3Which statement is true regarding external files?

A. External file objects are accessed with SAS INFILE and FILE statements.B. External files contain only one record per line.C. External files can be used as input but not as outputs in SAS Data Integration Studio jobs.D. SAS can only work with Blank, Comma, Semicolon and Tab as delimiters in external files.



Item 4Within SAS Data Integration Studio's SQL Join transformation, the option to turn on debug is located in which Properties pane?

A. Select PropertiesB. Create PropertiesC. SQL Join PropertiesD. Job Properties


Item 5Which SAS Data Integration Studio reports, generated as external files, can be stored as document objects within metadata?

A. only job reportsB. only table reportsC. both job reports and table reportsD. No reports can be stored as document objects.


Item 6You want to create a job to extract only the rows that contain information about female employees from a table that contains information about both male and female employees. The new table should have observations in ascending order of age. Refer to the job flow diagram in the exhibit. Where would you set the options to filter and sort the data?

A. Where tab and Group By tabB. Where tab and Order By tabC. Where tab and Parameters tabD. Group By tab and Parameters tab


Item 7Within SAS Data Integration Studio's Table Loader transformation, which load style choice does NOT exist?

A. Delete whereB. Append to ExistingC. Replace

D. Update/Insertcorrect_answer = "A"

Item 8In SAS Data Integration Studio, a business key can be defined in the properties of which transformation?

A. Data ValidationB. SQL JoinC. LookupD. SCD Type 2 Loader


SAS BI Content Developer for SAS 9

Item 1When opening a registered SAS data file into a Microsoft Excel Worksheet, a user has the option to sort the data.

Which application performs the sort and where does the sort occur?

A. SAS performs the sort on the server.B. SAS performs the sort on the local machine.C. Excel performs the sort on the server.D. Excel performs the sort on the local machine.


Item 2When can you add a stored process as a data source to an information map?

A. anytimeB. when at least one table is selected as a data sourceC. when at least one OLAP cube is selected as a data sourceD. once an application server has been selected


Item 3Refer to the exhibit.

A SAS.IdentityGroups filter has been created in SAS Information Map Studio. There is a data item called


"Group" that contains different metadata groups.

If the "Group" filter is applied to the map, how will it affect the data?

A. All rows will be returned for any group that the user is a member of.B. Only rows that belong to the first group are returned.C. All rows will be returned for PUBLIC group only.D. All rows matching the group identity login are returned.


Item 4A SAS data set is used as a data source for a SAS BI Dashboard data model.

Which type of code do you write to query the data?

A. DATA StepB. PROC SQLC. a SQL/JDBC queryD. MDX


Item 5Refer to the exhibit.

What causes this error message when executing a stored process?

A. Stored process code cannot be a .TXT file.B. The stored process server is not running.C. The file that contains the stored process code is not in the specified location.D. An administrator deleted the stored process from the metadata.


Item 6In a stored process, when using a range prompt named DateRange, which macro variables would you use in your SAS code?

A. DateRange_START and DateRange_FINISHB. DateRange_BEGIN and DateRange_END

C. DateRange_MIN and DateRange_MAXD. DateRange0 and DateRange1


Item 7Upon initial install, all of the capabilities in the 'Web Report Studio: Report Creation' role are also included in which role?

A. Web Report Studio: Report ViewingB. Web Report Studio: AdvancedC. Web Report Studio: Content ManagementD. Web Report Studio: Administration


Item 8A content developer would like to create a group of cascading prompts to use in multiple reports without recreating the prompts for each report.

What features of the prompt framework must the developer use?

A. Cannot create shared cascading prompts for use in multiple reports.B. Dynamic Prompts and Shared PromptsC. Cascading Prompts and Standard GroupsD. Cascading Prompts, Standard Groups, and Shared Prompts


Item 9A SAS Information Map with a SAS OLAP Cube as a data source can be built from which of the following?

A. multiple SAS OLAP CubesB. a SAS OLAP Cube and a stored processC. one table joined with one SAS OLAP CubeD. one SAS OLAP Cube only


Item 10Which statement is true regarding connection profiles used with the SAS platform applications?

A. Each SAS platform application must have its own connection profile.B. Connection profiles are stored on the server machine.C. Connection profiles are stored on the machine where the SAS application is installed.D. All SAS platform applications share one connection profile.



SAS Statistical Business Analyst Using SAS 9

Item 1A financial analyst wants to know whether assets in portfolio A are more risky (have higher variance) than those in portfolio B. The analyst computes the annual returns (or percent changes) for assets within each of the two groups and obtains the following output from the GLM procedure:

Which conclusion is supported by the output?

A. Assets in portfolio A are significantly more risky than assets in portfolio B.B. Assets in portfolio B are significantly more risky than assets in portfolio A.C. The portfolios differ significantly with respect to risk.D. The portfolios do not differ significantly with respect to risk.


Item 2An analyst has determined that there exists a significant effect due to region. The analyst needs to make pairwise comparisons of all eight regions and wants to control the experimentwise error rate.

Which GLM procedure statement would provide the correct output?

A. lsmeans Region / pdiff=all adjust=dunnett;

B. lsmeans Region / pdiff=all adjust=tukey;

C. lsmeans Region / pdiff=all adjust=lsd;

D. lsmeans Region / pdiff=all adjust=none;


Item 3A linear model has the following characteristics:

a dependent variable (y)

one continuous predictor variables (x1) including a quadratic term (x12) one categorical predictor variable (c1 with 3 levels) one interaction term (c1 by x1)

Which SAS program fits this model?A. proc glm data=SASUSER.MLR;

B. class c1;

C. model y = c1 x1 x1sq c1byx1 /solution;

D. run;

E. proc reg data=SASUSER.MLR;

F. model y = c1 x1 x1sq c1byx1 /solution;

G. run;

H. proc glm data=SASUSER.MLR;

I. class c1;

J. model y = c1 x1 x1*x1 c1*x1 /solution;

K. run;

L. proc reg data=SASUSER.MLR;

M. model y = c1 x1 x1*x1 c1*x1;

N. run;


Item 4Refer to the REG procedure output:

What is the most important predictor of the response variable?

A. interceptB. overheadC. scrapD. training


Item 5Which statement is an assumption of logistic regression?

A. The sample size is greater than 100.B. The logit is a linear function of the predictors.C. The predictor variables are not correlated.D. The errors are normally distributed.


Item 6When selecting variables or effects using SELECTION=BACKWARD in the LOGISTIC procedure, the business analyst's model selection terminated at Step 3.

What happened between Step 1 and Step 2?

A. DF increased.B. AIC increased.C. Pr > Chisq increased.D. - 2 Log L increased.


Item 7The LOGISTIC procedure will be used to perform a regression analysis on a data set with a total of 10,000 records. A single input variable contains 30% missing records.

How many total records will be used by PROC LOGISTIC for the regression analysis?

Enter your numeric answer in the space below. Do not add leading or trailing spaces to your answer.

Click the calculator button to display a calculator if needed.

correct_answer = "7000"

Item 8An analyst is screening for irrelevant variables by estimating strength of association between each input and the target variable. The analyst is using Spearman correlation and Hoeffding's D statistics in the CORR procedure.

What would likely cause some inputs to have a large Hoeffding and a near zero Spearman statistic?

A. nonmonotonic association between the variablesB. linear association between the variablesC. monotonic association between the variablesD. no association between the variables


Item 9An analyst builds a logistic regression model which is 75% accurate at predicting the event of interest on the training data set. The analyst presents this accuracy rate to upper management as a measure of model assessment.

What is the problem with presenting this measure of accuracy for model assessment?

A. This accuracy rate is redundant with the misclassification rate.B. It is pessimistically biased since it is calculated from the data set used to train the model.C. This accuracy rate is redundant with the average squared error.D. It is optimistically biased since it is calculated from the data used to train the model.


Item 10Refer to the exhibit:

For the ROC curve shown, what is the meaning of the area under the curve?

A. percent concordant plus percent tiedB. percent concordant plus (.5 * percent tied)C. percent concordant plus (.5 * percent discordant)D. percent discordant plus percent tied

correct_answer = "B"</b.seven<>

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