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Haas MFE SAS Workshop Lecture 1: Introduction to SAS

Haas MFE SAS Workshop Lecture 1: Introduction to SAS. Peng Liu http://faculty.haas.berkeley.edu/peliu/computing. Haas School of Business, Berkeley, MFE 2006. What is SAS?. Stands for “Statistical Analysis System”, Pronounced “sass”, not spelled out as three letters.

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Haas MFE SAS Workshop Lecture 1: Introduction to SAS

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  1. Haas MFE SAS WorkshopLecture 1: Introduction to SAS Peng Liuhttp://faculty.haas.berkeley.edu/peliu/computing Haas School of Business, Berkeley, MFE 2006

  2. What is SAS? • Stands for “Statistical Analysis System”, • Pronounced “sass”, not spelled out as three letters. • Developed in the early 1970s at North Carolina State University • SAS Institute Inc. was formed in 1976 • Now the most widely used statistical software in both industry and academic circles Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 2

  3. Overview of SAS Products • Base SAS - data management and basic procedures • SAS/STAT - statistical analysis • SAS/GRAPH - presentation quality graphics • SAS/OR - Operations research • SAS/ETS - Econometrics and Time Series Analysis • SAS/IML - Interactive Matrix Language • SAS/SQL – Structural query language Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 3

  4. Getting Started • SAS PRIMER for Financial Engineers: • Lecture1: SAS Introduction • Lecture2: SAS Data management • Lecture3: SAS Financial modeling • Lecture4: Advanced SAS techniques • Learning by doing, let’s look at real SAS program using actual financial data. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 4

  5. WHY SAS? Top reasons for financial engineers to use SAS? • Reliable • Handel large datasets • Powerful procedures • Quant interviews Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 5

  6. A Task • You have obtained a valuable dataset, you want to look at the data, have a sense what those data represent. • Download the data MortgageLoan.xls from computing webpage. Or open from P:\PodiumPC\2006MFE • Often the data is too large that excel cannot contain. • We want to use a software to read-in, look-it-up, summarize, regression, visualize, report… • A demonstration - you will do it yourself later. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 6

  7. INPUT DATA Options nodate nonumber ls=80; DATA LOAN1; INFILE'R:\bulk\SAS\MFE\loan.txt' DELIMITER=','; INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; RUN; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 7

  8. Informative messages are written to the SAS log - make sure you read it! 1 DATA LOAN1; 2 INFILE 'R:\bulk\SAS\MFE\loan.txt' DELIMITER=','; 3 INPUT ID Origination mmddyy10. Term Rate Balance 4 Appraisal LTV FICO_orig City $ State $2. ; 5 RUN; NOTE: The infile 'R:\bulk\SAS\MFE\loan.txt' is: File Name=R:\bulk\SAS\MFE\loan.txt, RECFM=V,LRECL=256 NOTE: 100 records were read from the infile 'R:\bulk\SAS\MFE\loan.txt'. The minimum record length was 56. The maximum record length was 69. NOTE: The data set WORK.LOAN1 has 100 observations and 10 variables. NOTE: DATA statement used (Total process time): real time 0.04 seconds cpu time 0.01 seconds Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 8

  9. DATA STEP Options nodate nonumber ls=80; DATA LOAN1; INFILE 'R:\bulk\SAS\MFE\loan.txt' DELIMITER=','; INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; RUN; /* DATA STEP */ DATA LOAN2; SET LOAN1; LTV1 = 100*(BALANCE/APPRAISAL); LTV2 = ROUND(LTV1,0.1); IF LTV-LTV2 NE 0THEN ERROR=1; ELSE ERROR=0; RUN; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 9

  10. PROC STEP Options nodate nonumber ls=80; DATA LOAN1; INFILE 'R:\bulk\SAS\MFE\loan.txt' DELIMITER=','; INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; RUN; /* DATA STEP */ DATA LOAN2; SET LOAN1; LTV1 = 100*(BALANCE/APPRAISAL); LTV2 = ROUND(LTV1,0.1); IF LTV-LTV2 NE 0 THEN ERROR=1; ELSE ERROR=0; RUN; PROCPRINTDATA=LOAN2; VAR ID TERM RATE LTV LTV2 ERROR; TITLE'SAMPLE RECORDS FROM LOAN LEVEL DATA’ ; RUN; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 10

  11. PROC MEANS DATA LOAN1; INFILE 'R:\bulk\SAS\MFE\loan.txt' DELIMITER=','; INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; RUN; /* DATA STEP */ DATA LOAN2; SET LOAN1; LTV1 = 100*(BALANCE/APPRAISAL); LTV2 = ROUND(LTV1,0.1); IF LTV-LTV2 NE 0 THEN ERROR=1; ELSE ERROR=0; RUN; PROCPRINT DATA=LOAN2; VAR ID TERM RATE LTV LTV2 ERROR; TITLE 'SAMPLE RECORDS FROM LOAN LEVEL DATA SET'; RUN;PROCMEANS DATA=LOAN1; VAR APPRAISAL FICO_ORIG; RUN; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 11

  12. SAS program structure /* DATA STEP */ DATA LOAN2; SET LOAN1; LTV1 = 100*(BALANCE/APPRAISAL); LTV2 = ROUND(LTV1,0.1); IF LTV-LTV2 NE 0THEN ERROR=1; ELSE ERROR=0; /* PROCEDURE STEP */ PROCMEANS DATA=LOAN1; VAR APPRAISAL FICO_ORIG; RUN; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 12

  13. Output 1 SAMPLE RECORDS FROM LOAN LEVEL DATA Obs ID Term Rate LTV LTV2 ERROR 1 240248 180 6.375 71.2 71.2 0 2 522967 360 6.625 60.9 60.9 0 3 826556 360 7.125 65.5 65.5 0 4 885563 360 7.000 80.0 80.0 0 5 4243480 360 7.750 79.9 79.9 0 …………. 23 5869916 360 7.250 55.4 55.4 0 24 5871655 360 8.250 80.0 80.0 0 25 5875033 360 8.500 80.0 80.0 0 26 5889419 360 8.250 57.9 57.9 0 27 5903222 360 7.750 48.4 48.4 0 28 5909103 360 7.750 75.2 75.2 0 29 5934371 360 7.625 50.0 50.0 0 30 5943458 360 7.625 80.0 80.0 0 Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 13

  14. Output 2 SAMPLE RECORDS FROM LOAN LEVEL DATA The MEANS Procedure Variable N Mean Std Dev Minimum Maximum Appraisal 100 691833.28 364426.29 220000.00 2351000.00 FICO_orig 100 731.5700000 52.9597245 564.0000000 805.0000000 Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 14

  15. What you need to run SAS • SAS software for Windows/Unix/Mac OS • Available through Haas on Bear and on the Terminal Server • One year licenses are available to UC Berkeley students for $30 http://softdist.berkeley.edu/ • Current version for windows 9.1.3 • SAS dataset(s) • Can be created from external files in many formats, can be directly input in data step. • SAS program(s) • Data step(s), Proc step(s), or both Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 15

  16. SAS Datasets • Structure: Rows-obs.; Columns-var. • Dataset names must be 32 characters or less, constructed of letters, digits and the underscore • Good idea not to start names with an underscore, special system variables are named that way. • Missing values are handled consistently in SAS, and are represented by a period (.) • A SAS dataset contains not only data bu also the information on varialbe type, label, etc. • Temporary v.s. Permanent dataset Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 16

  17. SAS programs-Basic Structure 1 • SAS is composed of a series of SAS statement. Each SAS statement must end in a semicolon (;) • All SAS programs for windows must end with statement: RUN; • There are two main components in most SAS programs – (the SAS programmer is always doing one of the two things) • The DATA steps and the PROCedure steps. • You can combine as many data and proc steps in whatever order you want. • Data steps begin with the word data and procedure steps begin with the word proc. • The data steps allow you to read raw/sas/other data, manipulate data by concatenating, merging and subsetting data. The data step is used to prepare your data for use by one or more SAS procedures • The procedure steps perform analysis on the data, and produce statistical and graphical output. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 17

  18. SAS programs-Basic Structure 2 • Add comments using asterisk * …; or /* …*/ • The RUN; command signals to SAS that the previous commands can be executed. • There are global options (like linesize and pagesize) as well as options specific to datasets and procedures. • Variable names must be 32 characters or less, constructed of letters, digits and the underscore character. There are virtually no reserved keywords in SAS; it's very good at figuring things out by context. • SAS is not case sensitive, except inside of quotation mark ‘ ’ or “ ” . • The placement of the SAS statements does not effect SAS processing. Create your own programming style! Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 18

  19. Running PC SAS • Open SAS program (clicking SAS icon) • Load or type your SAS program in the Program Editor window(Enhanced Editor) • Run/Submit: F8=RUN; • Check log for error (F6=Log) • Check output/Graphic windows for results/graph(F7=output) • Revise code (F5 PGM) • CTRL+E = Clear screen Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 19

  20. PROCIMPORT OUT= WORK.loan DATAFILE ="R:\bulk\SAS\MFE\MortgageLoan.xls" DBMS=EXCEL REPLACE; SHEET="Loan$"; GETNAMES=YES; RUN; PROCEXPORT DATA= WORK.Loan2 OUTFILE ="R:\bulk\SAS\MFE\loan2.xls" DBMS=EXCEL REPLACE; SHEET="loan"; RUN; Importing/Exporting data Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 20

  21. Two-level name: libref.dsname Syntax: LIBNAME LIBREF ‘PATH’; LIBREF is the library reference name you provided. PATH is the physical directory on your computer. Example-creating a permanent SAS data LIBNAME MFE 'R:\bulk\SAS\MFE\'; DATA MFE.LOAN; SET LOAN; RUN; Example-reading an external SAS dataset DATA LOAN; SET MFE.LOAN; LTV1 = 100*(BALANCE/APPRAISAL); RUN; Create a permanent dataset Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 21

  22. Fixed Format 1234567890123456789012345 024024807/19/20021806.375 052296708/14/20023606.625 082655602/18/20023607.125 088556305/06/20023607 424348007/10/20013607.75 429657109/11/20013607.125 Data loan; Infile 'R:\bulk\SAS\MFE\loan.txt'; Input id 1-7 month 8-9 day 11-12 year 14-17 city $ 32-42 state $50-51; Run; /*using fileref*/ Filename xxx 'R:\bulk\SAS\MFE\loan.txt'; Data loan; Infile xxx; Input id 1-7 month 8-9 day 11-12 year 14-17 city $ 32-42 state $50-51; Run; Read Raw Data 1 Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 22

  23. List Format 0240248 07/19/2002 180 6.375 0522967 08/14/2002 360 6.625 0826556 02/18/2002 360 7.125 0885563 05/06/2002 360 7 4243480 07/10/2001 360 7.75 4296571 09/11/2001 . 7.125 Filename xxx 'R:\bulk\SAS\MFE\loan.txt'; Data loan; Infile xxx; Input id origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig city & $ State $2. ; Run; /* note: 1.May need to specify length for cha. Var.to avoid default truncation at length=8. 2.Make sure mising/blank field is replaced by period. */ Read Raw Data 2 Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 23

  24. Delimited Format 0240248,07/19/2002,180,6.375 0522967,08/14/2002,360,6.625 0826556,02/18/2002,360,7.125 0885563,05/06/2002,360,7 4243480,07/10/2001,360,7.75 4296571,09/11/2001,360,7.125 filename xxx 'R:\bulk\SAS\MFE\loan.txt' ; DATA LOAN1; INFILE xxx DELIMITER=','; INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; RUN; Read Raw Data 3 Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 24

  25. Modifiers for List Input • The colon (:) modifier for list input tells SAS to use a format for input, but to stop when the next whitespace is found. • Data like: 17,244 2,500,300 600 12,003 14,120 2,300 4,232 25 could be read using an input statement like input x1 : comma. x2 : comma. x3 : comma. x4 : comma. ; • The ampersand (&) modifier tells SAS to use two whitespace characters to signal the end of a character variable, allowing embedded blanks to be read using list input. Thus, the statements: • input city & $ state $ 2.; could be used to read data such as SAN JOSE,CA BATON ROUG,LA UPPER SADD,NJ Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 25

  26. Other Modifiers for the Input Statement • + number advance number columns. • # number advance to line number. • / advance to next line. • trailing @ hold the line to allow further input statements in this iteration of the data step on the same data. • trailing @@ hold the line to allow continued reading from the line on subsequent iterations of the data step. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 26

  27. Variable Lists • SAS provides several different types of variable lists, which can be used in all procedures, and in some data step statements. • Numbered List - When a set of variables have the same prefix, and the rest of the name is a consecutive set of numbers, you can use a single dash (-) to refer to an entire range: x1 - x3 for x1, x2, x3; x01 - x03 for x01, x02, x03 • Colon list - When a set of variables all begin with the same sequence of characters you can place a colon after the sequence to include them all. If variables a, b, xheight, and xwidth have been defined, then x: for xwidth, xheight. • Special Lists - Three keywords refer to a list with the obvious meaning: _numeric_ , _character_, _all_ In a data step, special lists will only refer to variables which were already defined when the list is encountered. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 27

  28. Variable Lists (cont'd) • Name range list - When you refer to a list of variables in the order in which they were defined in the SAS data set, you can use a double dash (--) to refer to the range: • If the input statement INPUT ID Origination mmddyy10. Term Rate Balance Appraisal LTV FICO_orig City $ State $2. ; was used to create a data set, then LTV -- state refers to LTV FICO_orig city state • If you only want character or numeric variables in the name range, insert the appropriate keyword between the dashes: • id _character_ state refers to city and state • In general, variables are defined in the order they appear in the data step. If you're not sure about the order, you can check using proc contents. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 28

  29. Display SAS Dataset • Proc content data=loan; run; • The short option limits the output to just a list of variable names. • The position option orders the variables by their position in the data set, instead of the default alphabetical order. This can be useful when working with double dashed lists. • The directory option provides a list of all the data sets in the library that the specified data set comes from, along with the usual output for the specified data set. • procprint DATA = loan2 (firstobs=60 obs=100); VAR id origination rate ltv fico_orig city; run; • Useful statement in proc print:ID state; SUM error; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 29

  30. SAS Functions: Mathematical Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 30

  31. SAS Functions: Statistical Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 31

  32. Round(arg, amount) Int(arg) Ceil(arg) Floor(arg) Rannor(seed) Ranuni(seed) Ranbin(seed,n,p) Runtbl(seed,p1,p2,… pn) SAS Functions: other numerical Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 32

  33. Operators in SAS • Arithmetic operators: * Multiplication + addition / division - subtraction ** exponentiation • Comparison Operators: = or eq equal to ^= or ne not equal to > or gt greater than >= or ge greater than or equal to < or lt less than <= or le less than or equal to • Boolean Operators: & or and and | or or or ^ or not negation • Other Operators: ><minimum;<>maximum; || char. concatenation • The in operator lets you test for equality to any of several constant • values. x in (1,2,3) is the same as x=1 | x=2 | x=3. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 33

  34. Using Statistical Summary Functions You can use variable lists in all the statistical summary functions by preceding the list with the word “of”; for example: xm = mean(of x1-x10); vmean = mean(of thisvar -- thatvar); Without the of, the single dash is interpreted in its usual way, that is as a minus sign or the unary minus operator; thus xm = mean(of x1-x10); is the same as xm = mean(x1,x2,x3,x4,x5,x6,x7,x8,x9,x10); but xm1 = mean(x1-x10); calculates the mean of x1 minus x10, and xm2 = mean(x1--x10); calculates the mean of x1 plus x10. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 34

  35. SAS Functions: Character 1 • compress(target,<chars-to-remove>) expr = "one, two: three:"; new = compress(expr,",:"); results in new equal to one two three With no second argument compress removes blanks. • index(source,string) - finds position of string in source where = "university of california"; i = index(where,"cal"); results in i equal to 15 • indexc(source,string) - finds position of any character in string in source where = "berkeley, ca"; i = indexc(where,"abc"); results in i equal to 1, since b is in position 1. index and indexc return 0 if there is no match. • left(string) - returns a left-justied character variable • length(string) - returns number of characters in a string length returns 1 if string is missing, 12 if string is uninitialized • repeat(string,n) - repeats a character value n times • reverse(string) - reverses the characters in a character variable Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 35

  36. SAS Functions: Character 2 • right(string) - returns a right-justied character variable • both = right(one) || left(two); insures no blanks between the two concatenated variables. • trim(string) - returns string with leading blanks removed • upcase(string) - converts lowercase to uppercase lowcase(string)- converts uppercase to lowercase • scan(string,n,<delims>) - returns the nth word" in string field = "smith, joe"; first = scan(field,2," ,"); results in first equal to joe If you omit delims, SAS uses most non-alphanumeric characters • substr(string,position,<n>) - returns pieces of a variable field = "smith, joe"; last = substr(field,1,index(field,",") - 1); results in last equal to smith • translate(string,to,from) - changes from chars to to chars word = "eXceLLent"; new = translate(word,"xl","XL"); results in new equal to excellent • verify(source,string) - return position of first char. in source which is not in string check = verify(val,"0123456789."); results in check equal to 0 if val is a character string containing only numbers and periods. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 36

  37. Data Type Conversion-Problem • SAS only has three data types: Numeric, Character and Date/time. When you accidentally mix variable types, SAS tries to fix your program by converting them. • Log File - “Note: Numeric Values have been converted to Character!” Cannot ignore this! • For example: 110 can be numeric or character, when you use numerical function on character variables or vice versa. SAS tries to convert to appropriate data type first, then perform function calculations. • How to Fix? A practical way is to use INPUT/PUT functions. • Close cousin of input/put statements, but different! Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 37

  38. Character to Numeric new=INPUT (old, informat); Informat must be the type you are converting to – numeric Rate_num=input (rate_char,5.2); Demo- loan5 Numeric to Character new=PUT (old, format); Informat must be the type you are converting from – numeric Rate_char=put (rate, 5.2); Data Type Conversion-FIX Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 38

  39. SAS Date and Time - values • There are three types of date and time values which SAS can handle, shown with their internal representation in parentheses: • Time values (number of seconds since midnight) • Date values (number of days since January 1, 1970) • Datetime values (number of seconds since January 1, 1970) • You can specify a date and/or time as a constant in a SAS program by surrounding the value in quotes, and following it with a t, a d or a dt. The following examples show the correct format to use: 3PM => '3:00p't or '15:00't or '15:00:00't January 4, 1937 => '4jan37'd 9:15AM November 3, 1995 =>'3nov95:9:15'dt or '3nov95:9:15:00'dt Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 39

  40. SAS Date and Time - Formats • SAS provides three basic informats for reading dates which are recorded as all numbers, with or without separators: • ddmmyyw. - day, month, year (021102, 6-3-2002, 4/7/2000) • mmddyyw. - month, day, year (110202, 3-6-2002, 7/4/2000) • yymmddw. - year, month, day (021102, 2002-3-6, 2000/7/4) • These informats will correctly recognize any of the followingseparators: blank : - . /, as well as no separator. • For output, the ddmmyyXw., mmddyyXw. and yymmddXw. formats are available, example using format statement • where “X" species the separator as follows: B - blank C - colon(:) D - dash(-) N - no separator P - period(.) S - slash(/) Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 40

  41. SAS Date and Time - Functions • datepart - Extract date from datetime value dateonly = datepart(present); • day,month year - Extract part of a date value day = day(date); • dhms - Construct value from date, hour, minute and second present_time=dhms(dateonly,10,00,00); • mdy - Construct date from month, day and year date = mdy(mon,day,1996); • time - Returns the current time of day now = time(); • today - Returns the current date datenow = today(); • intck - Returns the number of intervals between two values days=intck('day', origination, today()); • intnx - Increments a value by a number of intervals expiration=intnx('month', origination, term); format expiration yymmdds10.; Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 41

  42. Titles and Footnotes • SAS allows up to ten lines of text at the top (titles) and bottom (footnotes) of each page of output, specified with title and footnote statements. The form of these statements is title<n> text; or footnote<n> text; where n, if specified, can range from 1 to 10, and text must be surrounded by double or single quotes. • If text is omitted, the title or footnote is deleted; otherwise it remains in effect until it is redefined. Thus, to have no titles, use: title; • By default SAS includes the date and page number on the top of each piece of output. These can be suppressed with the nodate and nopage system options. Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 42

  43. System Options • Syntax option opt; • Check out all options: procoptions; • Frequently used options: • Display: • Date/nodate • Number/nonumber • Center/nocenter • Linesize=64-256 eg: ls=80; • Pagesize=20-200 eg: ps=100; • Label/nolabel Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 43

  44. Dataset Options • Syntax: DATA dsname (opt); • Example: data loan_CA (where=(state='CA') drop=id); set loan; run; • Frequently used options • (Drop|keep=var-list) • (Rename=(old=new…)) • (Where=(logical expressions)) • (label=‘dataset description’) • (Obs/firstobs=n) (used only with set or data option of a proc) Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 44

  45. Resources: Introductory Books • http://www.sas.com/apps/pubscat/welcome.jsp • The Little SAS Book: a primer (3rd) is popular for beginners • Mastering the SAS System, 2nd Edition, by Jay A. Jae, Van Nostrand Reinhold • Quick Start to Data Analysis with SAS, by Frank C. DiIorio and Kenneth A. Hardy, Duxbury Press. • How SAS works: a comprehensive introduction to the SAS System, by P.A. Herzberg, Springer-Verlag • Applied statistics and the SAS programming language, by R.P. Cody, North-Holland, New York • SAS Institute produces several introductory guides; most are at a very elementary level. Among them are: • Introducing the SAS System, Version 6, First Edition • SAS Language and Procedures: Introduction, Version 6, First Edition • SAS Introductory Guide for Personal Computers, Release 6.03 • SAS Applications Programming: A Gentle Introduction Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 45

  46. Online Resources (sample) • Online help Sample Programs, distributed with SAS on all platforms. • SAS Institute Home Page: http://www.sas.com • SAS Institute Technical Support: • http://www.sas.com/service/techsup/find answer.html • Others: • http://www.math.yorku.ca/SCS/StatResource.html#SAS • http://www.indiana.edu/~statmath/stat/sas/win/ • http://www.ats.ucla.edu/stat/sas/ • http://statcomp.ats.ucla.edu/sas/ Haas School of Business, Berkeley, MFE 2006Peng Liu AND Alexander Vedrashko 46

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