getting started with sas base and sas enterprise guide · 3 introducing sas enterprise guide...

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N U I T, NEWCASTLE UNIVERSITY

Getting Started With SAS Base and SAS Enterprise Guide

A Training Manual for Beginners

Dr. S. T. Kometa

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Table of Contents

Introducing SAS Enterprise Guide (SAS-EG): A Typical Session …………………………..….3

SAS Enterprise Guide and the SAS System …………………………………………………..…..4

Introduction to SAS Enterprise Guide ………………………………………………………..…..4

Analysis Capabilities …………………………………………………………………………..…...5

Data Exploration, Analysis, and Reporting by Example ……………………………….……….5

Example …………………………………………………………………………..…………………5

Exercise One: Importing Data and Creating Notes………...……………………………………..7

Exercise Two: ……..………………………………………………………………………………...7

Exercise Three: Combining Reports into a Single Document..………………………………....10

Getting Started with the SAS System Point and Click Approach .......…………….…………...12

Getting Started with the SAS System Programming Approach ..........………………………...18

Basic Statistical Procedures through Programming ……………………………………………23

Learning outcomes (Aims and objectives of this workshop)

This course gives a quick overview of the essentials of SAS. After completing this course you

should:

be able to create an SAS data file from scratch

be able to carry out some simple analyses on the data file

be able to present some of the data graphically

open an Excel file in SAS

be able to use SAS Enterprise Guide

be able to interpret the output from the analyses

be able to use SAS with a degree of confidence

Important Notice: Please follow this instruction and change one default setting before you

continue. From the menu bar select Tools-> Options -> Tasks. Under “Default footnote text for

task output:” change the last argument to TIMEAMPM20.

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Introducing SAS Enterprise Guide (SAS-EG): A Typical Session

A typical SAS-EG session involve starting SAS-EG, opening an SAS data file, requesting an

analysis or build a chart and then leaving SAS-EG.

Starting SAS-EG

On Remote Application Service (RAS)

Type the following url in the address field of your internet browser: https://ras.ncl.ac.uk/. Log in

normally using your logon name and password. Single click on the Statistical Software folder.

Single click on SAS Enterprise Guide. Close the Welcome dialogue box.

On Common Desktop

Choose Start -> Programs -> Statistical Software. The available statistical software will be

displayed, choose SAS, and select SAS Enterprise Guide. Close the Welcome dialogue box.

Opening An SAS Data File (Set)

Click File -> Open -> Data…. Under the text area for File name: type

\\campus\software\dept\sas and click on Open. Select fall94 and click Open.

Running An Analysis

1. Select Describe -> Summary Statistics….

2. With Data selected in the Selection pane, control-click to select the variables sat, hsgpa,

and ptest in the Variables pane.

3. Drag these variables to the Task pane and drop them in as Analysis variables.

4. Select Status in the Variables pane and drag it to the Task pane to assign it as a

Classification variable.

5. Select Statistics in the Selection pane.

6. In the Basic statistics pane change the Maximum decimal places from Best fit to 2.

7. Select Percentiles in the Selection pane and select Median in the Percentile statistics pane.

8. Select Run to generate the descriptive statistics and plots.

Building A Chart

1. Select Graph -> Bar Chart….

2. With Bar Chart selected in the Selection pane, select Stacked Vertical Bar.

3. Select Data in the Selection pane.

4. In the Columns to assign pane, select College and drag it to the Column to Chart role in

the Task roles pane.

5. In the Columns to assign pane, select Status and drag it to the Stack role in the Task roles

pane.

6. Select Layout in the Selection pane. Deselect 2D by clicking on it.

7. In the Shape panel, select Cylinder from the drop-down menu.

8. Select Run.

Leaving SAS-EG

Click File -> Exit. Save Changes to Project? Select No.

https://ras.ncl.ac.uk/

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SAS Enterprise Guide and the SAS System

When you use SAS Enterprise Guide, you are also using SAS software behind the scenes. As you

access data and build tasks, SAS Enterprise Guide generates SAS code. You can use all the features

of SAS Enterprise Guide without knowing how to program in SAS. When you run a task, the

generated code is sent to SAS for processing and the results are returned to SAS Enterprise Guide.

Introduction to SAS Enterprise Guide

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Analysis Capabilities

An Overview of Statistical Tasks

To better understand the full capabilities of SAS Enterprise Guide, go through the menu bar and

examine all the available menus. Your attention is draw to the following menus:

Describe

Analyze

ANOVA

Regression

Multivariate

Survival Analysis

Capability Analysis

Control Charts

Time Series

Graph

Exit Enterprise Guide.

Data Exploration, Analysis, and Reporting by Example

Objectives

Explore the Enterprise Guide environment.

Conduct data exploration and analysis.

Generate a simple report.

Example

Information was collected on students attending your university in academic year 1994. You want

to create some reports and graphs to summarize student characteristics.

The data set contains 18 pieces of information on 200 students. The data is already in SAS format.

Study the data file carefully to better understand it. The variables in the data set are shown below:

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Exercise One: Importing Excel Data and Creating Notes

Follow these instructions to import the data set:

1. Open Enterprise Guide by single-click on the icon.

2. When you open Enterprise Guide, you will see a window asking whether you want to open

an existing project or create a new project, SAS program, or data. Select New Project.

3. Next, import the data. To open the Microsoft Excel file, select File -> Import Data. In File

name: type \\campus\software\dept\spss and click Open.

4. Select Employee data and then select Open.

5. Follow the online instructions by selecting Next, Next, Next and Finish.

A new SAS data table is created from the Excel worksheet.

Exercise Two: Data Exploration using Charts, Summary Statistics and Correlation

1. Select File ->Open ->Data…. In File name: type \\campus\software\dept\sas and click

Open.

2. Select the file fall94, and then select Open. Note that this begins a new flow in the Process

Flow diagram, which we will work with from this point forward.

3. To add some text in the project describing the data, select File ->New ->Note. You can then

type information into the note. For example “Data file containing 18 pieces of information

on 200 students”.

4. Save the work done so far by selecting File -> Save Project As….

5. Save the project within a folder (directory) on your H: Drive (My Documents). If you like,

you can create a new folder for this tutorial within the folder My SAS Files.

6. Name the project Students, and then select Save.

Data Exploration

You have been asked to generate a report on the data from academic year 1994. In particular, the

administration is interested in comparing students by their status. Begin by creating some graphs

and descriptive statistics that look at the college the students are enrolled in and some of their

current and previous academic measures. Begin by creating some bar charts that show the status of

the students within each of the colleges. Follow these steps:

1. Select Tasks -> Graph -> Bar Chart….

2. With Bar Chart selected in the Selection pane, select Stacked Vertical Bar.


4. In the Columns to assign pane, select College and drag it to the Column to Chart role in

the Task roles pane.

5. In the Columns to assign pane, select Status and drag it to the Stack role in the Task roles

pane.

6. Select Layout in the Selection pane. Deselect 2D by clicking on it.

7. In the Shape panel, select Cylinder from the drop-down menu.

8. Select Run.

Examine the bar chart. What information can you get from it?

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Recall that the definitions of the values of these variables were listed at the beginning of this

document on page 6.

If you point your cursor at the different parts of the bar chart, the information on that section is

displayed.

If you examine the Process Flow and Project Tree, you will notice the additions of the dialog that

created the bar chart and the output to each of these. In the Project window, you also can see and

have access to the Log window for this task.

The office requesting the information would like some descriptive statistics about the students' high

school grade point averages, pretest scores, and sat scores. They would like this information

separately for each type of student (freshman, returning, continuing, and transfer students). To

generate the requested descriptive statistics, follow these steps:

1. Select Tasks -> Describe -> Summary Statistics….

2. With Data selected in the Selection pane, control-click to select the variables sat, hsgpa,

and ptest in the Variables to assign pane.

3. Drag these variables to the Task roles pane and drop them in as Analysis variables.

4. Select Status in the Variables pane and drag it to the Task roles pane to assign it as a

Classification variable.

5. Select Statistics in the Selection pane.

6. In the Basic statistics pane change the Maximum decimal places from Best fit to 2.

7. Select Percentiles in the Selection pane and select Median in the Percentile statistics pane.

8. Select Run to generate the descriptive statistics and plots.

Now examine the output. What information can you draw from the output?

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You are interested in examining the relationship between these three measures of student

performance prior to attending the university and the student performance at the university as

measured by their cumulative grade point average at the end of the Fall term (cumgpae). One

statistical measure that can be used is the correlation statistic. Follow these steps:

1. Select Tasks or Analyze -> Multivariate -> Correlations….

2. With Data selected in the Selection pane, control-click to select the variables sat, cumgpae,

hsgpa, and ptest in the Variables to assign pane.

3. Drag those selections to the Task Roles pane and drop them in as Analysis variables.

4. Select Options in the Selection pane and note that the Pearson correlation will be computed

by default.

5. Select Results in the Selection pane and click to select Create a scatter plot for each

correlation pair.

6. Select Run.

Examine the output, what conclusion(s) can you draw from the output?

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Now attempt to produce two dimension scatter plot using any two of the variables you used to

produce the correlation.

In addition to two-dimensional scatter plots, you can also produce three-dimensional scatter plots.

To illustrate this, generate a 3D scatter plot with the variables cumgpae, hsgpa, and ptest. This will

allow you to explore the relationship between all three of the variables at the same time. Follow

these steps:

1. Select Task -> Graph -> Scatter Plot….

2. With Scatter Plot selected in the Selection pane, select 3D Scatter Plot in the Scatter Plot

pane.


4. Assign hsgpa as the Horizontal variable, ptest as the Vertical variable, and cumgpae as

the Depth variable.

5. Select 3D Scatter in the Selection pane.

6. Change the Symbol type to Sphere using the drop down arrow. Note that you do have the

capability to control most aspects of the graph including such things as the axes and titles.

7. Select Run and examine the chart.

You can export a graph like this to a Word or PowerPoint presentation.

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Exercise Three: Combine Reports into a Single Document

You might want to include some of these results in a report. Your results can be sent to several

different types of files, several of which would be useful for creating a report. You can also pick

and choose output to include in a document using the Document Builder in Enterprise Guide.

Follow these steps:

1. Select File -> New -> Report.

2. Select any part of the output (results) that you want to include in your report from the left

pane. Drop it in any of the squares in the right pane. Click OK.

The document has been added to the project and the process flow as Report. Save the document

outside of Enterprise Guide. Follow these steps:

1. Right-click on Report in the project tree or the process flow and select Export -> Export

Report….

2. Select Local Computer to export the document to.

3. Choose a location on your computer to save the document, rename it.

4. Choose the report format that you want e.g. html. Click Save.

At this point, you can open the html file that has been created in an application such as Microsoft

Word and add comments and conclusions. This file can then be saved and submitted electronically.

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Getting Started with the SAS System

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Point and Click Approach

You are advised to use this document alongside the program.

Starting SAS

To start SAS click on Start -> Programs -> Statistical Software -> The SAS System -> The SAS

System for Windows.

The SAS software has five main windows: Explorer, Results, Editor (Program), Log and Output

Windows. Windows may overlay one another. See Fig.1 below.

Fig. 1 The SAS Windows

Explorer window

Use this window for file management tasks such as moving, copying and deleting files. In this

window, you can also create new libraries and SAS files. You can display the Explorer window

with or without a tree view of its contents. That is, View -> Show Tree. You can also use the

Toggle Tree on the toolbar to do this. See Fig. 2.

Log Window

Editor Window

Toolbar

Pull down Menu bar

Window bar Editor is the active window

Status bar Cursor Position indicator Message Line

Output Window under the Log and Editor windows

Results Window under the Explorer window

Explorer Window

Command line area. Click on tick to submit command

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Fig. 2 The Explorer Window

Program Editor Window

In this window, you can enter, edit, and submit SAS programs. You can use more than one Editor

window. The main features of this window include:

colour coding and syntax checking of SAS language

expandable and collapsible sections, click on the (+) to expand and (-) to collapse

multi-level undo and redo. See Fig. 3 for details.

Fig. 3 Program Editor Window

Normal View of the

Explorer Window

Toolbar for the

Explorer Window.

Unavailable tools

are grayed.

Help

Explorer

Programming Window

New Library

New Toggle Tree Toggle Details

Tree View of the Explorer

Window

Help

Break

Clear All

Submit

SAS Explorer New Library

Undo

Paste

New

Open

Save

Print

Print Preview

Toolbar for the

Editor Window.

Unavailable tools

are grayed.

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Log window

This window display important information about your SAS session and programs you submit.

Always examine the log window before you look at your output.

Fig. 4 Log Window

Output Window

You can browse output from SAS programs that you submit in this window. By default, the

window is positioned behind the Editor and Log windows. The window automatically moves to the

front for your first output in your SAS session. For subsequent output in the same session, you will

need to select the output button to see the output.

Results Window

This window helps you to navigate and manage output from SAS programs that you submit. You

can view, save and print individual items of output. By default, the Results window is positioned

behind the Explorer window and it is empty until you submit a program that creates output. Then it

moves to the front of your display.

The output and results window are shown together in Fig. 5 below.

Toolbar for the

Log Window.

Unavailable tools

are grayed. Very

similar to the

Editor toolbar.

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Fig. 5 Output and Results Windows

Using SAS window features

The active window determines what items are available on the main menu bar. In other words, each

window has its own menu selections that reflect the actions you can perform in the window. For

example, click the Explorer window and then select View. Examine the options available. Click

the Editor window and select View again. Examine the options available and notice that it offers

different selections.

Note:

you can minimize the Log, Editor and Output windows

right-click in any window to see the pop-up menus

toolbar displays icons for many of the actions you perform most often in a particular

window. Select the various Windows and examine how the toolbar changes.

Move your mouse to a tool and hold it there for a moment to see the name of the tool.

Getting Help in the SAS System

Help is available for all products in the SAS System. To appreciate the extensive help provided by

the SAS System, try the following:

Select Help. Take your time and examine this, particularly the following:

Output area.

It shows the actual

output.

Results area.

It shows table

of contents of the

output

Output

Window Results

Window

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Using This Widow

SAS Help and Documentation

Getting Started with the SAS Software

Learning SAS Programming

SAS on the Web

Make the Explorer window active, then select Help -> Using This Window. Take a few

moments and examine the task-oriented help available.

SAS Products

Base SAS, Enterprise Miner, SAS Enterprise Guide, SAS/ACCESS, SAS/AF, SAS/ASSIST,

SAS/CALC, SAS/CONNECT, SAS/EIS, SAS/ETS, SAS/FSP, SAS/GIS, SAS/GRAPH, SAS/IML,

SAS/INSIGHT, SAS/IntrNet, SAS/LAB, SAS/MDDB, SAS/OR, SAS/QC, SAS/SHARE,

SAS/SPECTRAVIEW/ SAS/STAT, SAS/TOOLKIT, SAS/TUTOR, SAS/Warehouse

Administrator.

Programming Language

The SAS Software is also a very powerful programming language.

Exploring Files in SAS

In the SAS System, you can explore and manage both SAS files and other files. In the Explorer

window, you can view and manage SAS files, which are stored in libraries. A library is simply a

link to the physical location of a file such as a directory or folder. If you delete the library the file

still exist in the directory or folder.

Make the Explorer window active and double-click on Libraries. All the active libraries

(directories) are listed. Double-click the Sashelp library. All members (files and directories) are

listed. Move back up to the top level, i.e. View -> Up One Level, or just click on its icon.

SAS allows you to explore files in your operating environment via View -> My Favorite Folders.

Working with SAS files: Details and Sort

To see detail information about any file double-click on its library and then click the detail tool or

View -> Details. In the Explorer window, you can sort files by any column. Just click the heading

of the column to sort the files. For example, click on the Type column to sort the files by file type.

Click it again to reverse the order. Go back to the original order by View -> Refresh.

File properties

The SAS System allows you to view detail properties on a file. Just right-click on the file you are

interested in the Explorer window and select Properties from the pop-up menu. The General

Properties window will be displayed. To see other properties, click the tab at the top of this

window. Try this using any file in the sashelp library.

To open a file just double-click its icon in the Explorer window. The file will be opened using the

Viewtable window. Try this again using any file in the sashelp library.

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Working with SAS Libraries

Creating a new library

There is already a folder in your H Drive (Documents) called My SAS Files. Check to confirm that

this folder is there. We need to create a new library in SAS and link it to this folder (My SAS Files).

All the SAS files that we create in this workshop will be stored in the folder (My SAS Files).

To create a new library follow these instructions:

Make the Explorer window active and double-click Libraries.

Select File -> New.

In the New Library window, type a name for the new library, e.g. MyNewLib. Leave the

default engine selected.

Select Enabled at Startup.

Click Browse and go H Drive (Documents) and select My SAS Files.

Click OK to create the library. MyNewLib appears in the active Libraries list.

Copying a table (file or data set)

Make sure that the Explorer window is active, then select View -> Show Tree. The window

will now have two panes, left and right.

Double-click the Sashelp library located in the left pane. Its content will be displayed in the

right pane. Scroll down and look for Prdsale table.

Click on Prdsale, drag and drop it on MyNewLib on the left pane.

Open MyNewLib and confirm that the table was copied successfully.

Note: You can change the name of a table quite easily. Right-click the name of the table and select

Rename from the pop-up menu. Re-name Prdsale as Myproductsales. Click OK.

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Programming Approach

The SAS Language Introduction

The SAS software has a very powerful programming language. There are many things that you can

do through programming that you can't do through the point and click approach. In fact, the power

of SAS still lies in the programming language. This document introduces some of the basic ideas in

SAS programming.

Some basic ideas about SAS and its programming language

SAS programs: A SAS program is simply a sequence of statements executed in order. This can be

simple or complex in nature.

SAS statements: Every SAS statement ends with a semicolon (;). Some SAS statements have

optional parts or sections.

Layout of SAS programs:

SAS statements can be in upper or lowercase

Statement can continue on the next line as long as you don’t split words in two

More than one statement can be on the same line

Statements can start in any column

Comments: Including comments in your program makes it easy to read and understand. There are

two ways to include comments in your SAS programs:

One starts with an asterisk (*) and ends with a semicolon (;).

The other starts with slash asterisk (/*) and ends with asterisk slash (*/).

That is, your comment goes between these characters. SAS ignores comments during the execution

of your program.

SAS Data Sets You write SAS programs to create, manipulate or analyse data sets. It is therefore important to

understand what a SAS data set is. The following applies to SAS data sets:

Variables and observations: In SAS terminology, data set consists of variables and observations.

In terms of relational databases, SAS data sets are also called tables, observations are called rows,

and variables are called columns.

Data types: There are just two data types in SAS: Numeric and Character. The dollar sign ($) is

used to denote character variables.

Missing data: Missing numeric data values are represented by periods (.), while missing character

values are represented by blanks.

Size of SAS data sets: SAS can handle up to 32,767 variables in a single data set. The number of

observations is limited by your computer’s capacity.

Rules for SAS names: When naming your variables and data sets bear the following rules in mind:

names must be 32 characters or fewer in length

names must start with a letter or underscore ( _ )

names can contain only letters, numerals, or underscores ( _ ). No % $ ! * & # @, please.

names can contain upper- and lowercase letters.

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Information on SAS data set such as the name, date created, version of SAS used, are stored as part

of the data set. Information on the variables such as type, name, length, format and informat are also

stored.

The Two Parts of a SAS Program

A SAS program is made up of two parts a data step and a procedure (proc) step. This can be simple

or complex. Examine the simple program below:

DATA firstdata;

quantity=10;

price=50;

Totalcost=quantity*price;

PROC PRINT DATA=firstdata;

RUN;

Data steps:

begin with DATA statements

read and modify data

create a SAS data set

The data step has built-in loops that execute line by line and observation by observation.

Proc steps:

begin with PROC statements

perform specific analysis or function

produce results or report

Choosing a Mode for Submitting SAS Programs

A SAS program does nothing until you submit or execute it. Once you have completed your

program, there are several ways to submit or execute the program:

SAS Windowing environment: Also known as interactive SAS. Run -> Submit. This is the

recommended method.

Non-interactive mode: The command is: system prompt> SAS filename.sas.

Batch or background mode: Common with mainframe computers.

Interactive line mode: Not recommended.

Windows and Commands in the SAS Windowing Environment

There are five basic SAS windows:

Results

Explorer

Program Editor

Log

Output

You may have up to three ways to issue commands:

Menus

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The tool bar

SAS command bar (command line)

Submitting a Program in the SAS Windowing Environment

First, make sure that your program is in the Program Editor window. Use any of the following to

submit your program:

Use the Submit icon on the toolbar

Make the Program Editor window active and type SUBMIT in the command line and then

press the tick with your mouse pointer

Make the Program Editor window active and select SUBMIT from the RUN pull-down

menu

Use the method you feel most comfortable with. Once you execute or submit a SAS program

messages will be generated. If your program does not have any errors output will be generated if

any.

Viewing the SAS Log and Output: You can now examine the SAS Log and the output from your

program if any.

Reading the SAS Log

SAS writes messages in to the log window each time you submit a program. Always examine the

log first before you examine your output if any. There is plenty of important information in the log.

You may also find warnings and other type of notes, which sometimes indicate errors and other

times just provide useful information.

Viewing and Printing the SAS Output

How you view or print your output depends on how you submit your programs. If you submit your

program in the SAS windowing environment, then your output will go to the Output window by

default. Listing of the different parts of your output will also be displayed in the Result window.

Printing or saving the contents of the Output window should be easy. Note that you can print or

save all or just parts of your output.

Using SAS System Options

System options are parameters you can change that affect the SAS System. The SAS System makes

many assumptions about how you want it to work. System options give you a way to change some

of these assumptions.

You can see a list of system options and their current values by opening the SAS System Options

window (i.e. Tools -> Options -> System) or by using the OPTIONS procedure in the Editor

Window (i.e. PROC OPTIONS; RUN;). In the SAS windowing environment, you can change

system options by:

SAS System Options window

OPTIONS statement

The OPTIONS statement is one of the special SAS statements which does not belong to either a

PROC or a DATA step.

Standard and Non-standard Numeric data

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Standard numeric data contain only numbers, decimal points, minus signs, and E for scientific

notation. Numbers with commas and pound signs are example of non-standard data. To read non-

standard data you use SAS informats. To print out non-standard data you use SAS formats.

Examples will be highlighted as we proceed through this document.

Practice 1

Type in the simple program on page 19 into the Editor window and submit it (via Run ->

Submit). The program starts with DATA and ends with a semicolon after RUN. Examine the Log

and Output Window.

GETTING YOUR DATA INTO THE SAS SYSTEM

SAS Data Libraries

This is used to store and manage data in SAS files. A SAS data library is a collection of one or

more SAS files that is recognized by the SAS System. Each file belongs to a particular library. A

library reference (libref) is the name you associate with the SAS data library. Each SAS data library

is assigned a libref. You reference files in the library by using the corresponding libref followed by

the name of the file.

Temporary and Permanent Data Sets The SAS System creates two types of data sets:

1. Temporary data set - A temporary SAS data set exists only for the duration of the current

SAS session and it is lost forever when you exit the SAS System. The default libref for

temporary data set is work. In other words, the SAS System automatically assigns the libref

work to the data set name you specify. When working with files in this library, you can

specify the libref or ignore it, SAS does not mind.

2. Permanent data set - A permanent SAS data set exists after the end of the current session and

until you deletes it. In creating or working with a permanent SAS data set you must specify

the libref and the data set name.

Both types of SAS data sets have two-level names in the form of libref.data-set-name. The sample

data sets found in SAS are permanent SAS data sets. For example, some data sets are kept in the

sashelp library. You can create your own library to store your SAS data sets permanently or use any

of the libraries available in SAS.

Methods of Getting Your Data into the SAS System

Entering data directly into SAS data sets

Creating SAS data sets from raw data files

Converting other software’s data files into SAS data sets

Reading other software’s data files directly

Telling SAS Where to Find Your Raw Data Internal Raw Data: Use the DATALINES or CARDS statement to tell SAS that raw data follows.

The following example illustrates this. Type and submit this little program. Examine the log

window and then the output window.

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Practice 2

DATA seconddata;

INPUT name $ weight height;

CARDS;

James 65 1.65

John 70 1.50

Lisa 60 1.70

;

PROC PRINT DATA=seconddata;

RUN;

The DATA statement tells SAS to create a temporary data set called seconddata. The INPUT

statement tells SAS to create three variables, the first is character (name) and the other two are

numeric (weight and height). If a variable name comes before $ then it is a character variable

otherwise numeric. The semicolon after the data indicates end of data line. The PROC PRINT

statement prints out the output on the screen not on paper.

External Raw Data Files: You can read raw data to create a SAS data set using the INFILE

statement, e.g. the following data in text format could be read into the SAS system using the

program below. As an exercise, use NotePad to type in the raw data. Save it as firsttrial in the

Temp directory in drive C. The data values are separated by space. Do not type in the first line.

Practice 3

Raw data firsttrial.txt

Lucky 2.3 1.9 . 3.0

Spot 4.6 2.5 3.1 .5

Tubs 7.1 . . 3.8

Hop 4.5 3.2 1.9 2.6

Noisy 3.8 1.3 1.8

1.5

Winner 5.7 . . .

Now type the following program in SAS Program Editor window to read the raw data file and

create a SAS data set.

Program to read raw data

* Create a temporary SAS data set named data1;

* Read the data file firsttrail.txt using list input;

DATA data1;

INFILE 'c:\Temp\firsttrial.txt';

INPUT ToadName $ Weight Jump1 Jump2 Jump3;

* Print the data to make sure that the file was read correctly;

PROC PRINT DATA = data1;

TITLE 'SAS Data Set Toads';

RUN;

The Input statement tells SAS what variables to read in the order given.

When dealing with long records, include the LRECL=option in the INFILE statement, e.g. Infile

'c:\stk\Training\sas\parks.txt' LRECL=2000; This ensure that data are not truncated.

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Importing Data

You can also import data directly into SAS. Follow these instructions.

Make sure that the Explorer window is your active window then select File -> Import

Data….We want to import an Excel file.

On the displayed dialogue box, click on the dropdown arrow and select Microsoft Excel

Workbook on PC Files Server.

Click Next and select Browse…

Under File name: type \\campus\software\dept\spss. Then click Open and select Employee

data.

Click Open again. Notice that the full path of the file appears next to Workbook:. So if you

knew the full path of your file you could have type it in.

Click OK. Then click Next and select Mynewlib from the library dropdown menu.

Under Member type the name of your file e.g. myfirstimport.

Click Next and click Finish. Check the Log window to make sure that the file was imported

successfully. Open and examine the file.

WORKING WITH YOUR DATA

Once you have successfully included your data in the SAS software, there is a lot that you can do

with it. This section of the document gives you examples of some of the things that you can do. You

can create new variables from existing ones, use SAS functions on variables, request various types

of statistics, build a model, etc.

Basic Statistical Procedures

Examining the Distribution of Data with PROC UNIVARIATE

This is a good procedure to help you explore your data before you do any formal statistical testing.

Type this simple programme into the data editor and submit it:

proc univariate data=stk.employeedata plot normal;

var salary salbegin;

run;

The normal option produces tests of normality while the plot option produces three plots of your

data (stem-and-leaf, box plot and normal probability plot).

Examine the output. What conclusion can you draw?

Hint: Skewness indicates how symmetric the distribution is while Kurtosis indicates how flat or

peaked the distribution is. The normal distribution has values of zero for both Skewness and

Kurtosis. If the mean (average) is very different from the median this indicates that the data is not

normal.

Producing Statistics with PROC MEANS

Proc means produce the descriptive statistics that you produce with proc Univariate. Univariate

prints out all these statistics by default. But if you know you want only a few of these statistics then

proc Means is better. Type this simple programme into the data editor and submit it:

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proc means data=stk.employeedata n mean median std mode;


run;

Testing Categorical Data with PROC FREQ

Produces many statistics for categorical data. The best known of which is chi-square. Type this

simple programme into the data editor and submit it:

proc format;

value $gender 'm'='male'

'f'='Female';

value group 1='Clerical'

2='Custodial'

3='Manager';

proc freq data=stk.employeedata;

format gender $gender. jobcat group.;

tables gender jobcat gender*jobcat / chisq measures;

run;


Examining Correlations with PROC CORR

A correlation coefficient measures the relationship between two variables. Before producing the

correlation coefficient between two interval variables, it is advisable to produce a scatter plot first.


proc gplot data=stk.employeedata;

plot salary*salbegin = gender;

run;

proc corr data=stk.employeedata;


run;


Using PROC ANOVA for One-Way Analysis of Variance

The ANOVA procedure is one of several in the SAS System that perform analysis of variance.

PROC ANOVA is specifically designed for balanced data – data were there are equal numbers of

observations (cases or subjects) in each classification. If your data is not balance use the GLM

procedure (see next example). To do this example you need to first import the data file from

\\campus\software\dept\spss. The file is an SPSS file and is called ‘number of words recalled’. So

you must tell SAS that you want to import an SPSS file in the Import Window (File -> Import

Data…). Import the file into your library Mynewlib and give it a member name words. Type this

simple programme into the data editor and submit it:

proc anova data=stk.words;

class group;

model score=group;

means group / scheffe;

run;

quit; *the quite statement is necessary because proc anova will still be running;

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Using PROC GLM

Use this when your data is unbalance. Type this simple programme into the data editor and submit

it:

proc glm data=stk.employeedata;

class jobcat;

model salary=jobcat;

means jobcat / scheffe;

run;

quit;


Using PROC T TEST

You can use this procedure for group means comparison, one-sample comparison or paired sample

comparison. It is assumed that the data is normally distributed.

Group Means Comparison (Independent samples)


ods graphics on;

proc ttest data=stk.employeedata;

class gender;

var salary;

run;

ods graphics off;


One-Sample Comparison

Is it true that the average salary of people working in this company is $30,000? Type this simple

programme into the data editor and submit it:

ods graphics on;

proc ttest data=stk.employeedata h0=30000;

var salary;

run;

ods graphics off;


Paired Sample Comparison

Some common examples of paired samples are:

pre- and post-test scores for a student receiving tutoring

fuel efficiency readings of two fuel types observed on the same automobile

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sunburn scores for two sunblock lotions, one applied to the individual’s right arm, one to the

left arm

political attitude scores of husbands and wives


ods graphics on;

proc ttest data=stk.employeedata;

paired Salary*Salbegin;

run;

ods graphics off;


Nonparametric Analysis

Most formal statistical analysis assumes that your data is normally distributed. If your data fails this

assumption you must use nonparametric analysis. We have seen that salary is not normally

distributed. Type this simple programme into the data editor and submit it:

Independent samples

ods graphics on;

proc npar1way data=stk.employeedata wilcoxon median;

class gender;

var salary;

run;

ods graphics off;


Using PROC REG

You use proc reg to build linear regression model. Type this simple programme into the data editor

and submit it:

ods graphics on;

proc reg data=stk.employeedata;

model salary=salbegin prevexp;

run;

ods graphics off;

Adding to programme. proc format;

value $gender 'm'='male'

'f'='Female';

value group 1='Clerical'

2='Custodial'

3='Manager';

proc means data=mynewlib.employeedata n mean median std mode;

format gender $gender. jobcat group.;

class gender jobcat;


run;