This page summarizes the SAS material required for this class.

Readings:

The following chapters refer to the text "Applied Statistics and the SAS Programming Language, Cody & Smith." You may want to review these chapters if you have the text.

• Chapter 1: pp1 - 15
• Chapter 2: pp22 - 34, pp42 - 44
• Chapter 5: pp115 - 133
• Chapter 6: pp138 - 148
• Chapter 7: pp150 - 163
• Chapter 12: pp280 - 288
• Chapter 17: pp353 - 355

The following chapters refer to the text "SAS System for Elementary Statistical Analysis, Schlotzhauer & Littell." You may want to review these chapters if you have the text.

• Chapter 2: pp27 - 33
• Chapter 3: pp37 - 53
• Chapter 4: pp80 - 86 (PROC UNIVARIATE)
• Chapter 4: pp86 - 87 (PROC MEANS)
• Chapter 7: pp185 - 214
• Chapter 9: pp286 - 311

The textbook readings above may not cover all the material required. The material below is a summary of textbook readings plus additional required topics. Remember to pay particular attention to the rules summarized in the Basic Rules section below. Here is a simple SAS program and its output. At a minimum, you should be very comfortable with programs of this complexity.

Review:

• Basic Rules:
  • All SAS programs consist of a sequence of statements organized into "steps". There are only two kinds of steps:
    • DATA step:
    • PROC step:
      Note:Once a dataset has been created, it can be processed by any subsequent "DATA" or "PROC" step.
  • A SAS program can contain any number of "DATA" and "PROC" steps.
  • All SAS statements start with a keyword (DATA, INPUT, PROC, etc.).
  • All SAS statements end with a semicolon ";".
  • SAS statements can be entered in free-format. That is, they can begin in any column; there may be multiple statements per line; you may split a statement over several lines (as long as no word is split.).
  • Uppercase and lowercase are equivalent, except inside quote marks (lang = 'c'; is not the same as lang = 'C';).
  • Naming Convention:
  1. 32 characters in length (Note: v6.12 users: 8 characters in length)
  2. begin with A-Z or _(i.e. underscore)
  3. cannot contain blanks or special symbols (e.g., &, %, $, #, etc.)
  • SAS Types:
  1. Character variables (followed by $)
  2. Numeric variables
  Note:Missing data: represented by '.' for numeric variables; by ' ' (i.e. space) for character variables.

• General statements:

These are statements that do not belong to a particular DATA or PROC step. They have a global effect.

• footnote statement
• title statement
• options statement

• DATA step statements:

SAS carries out all statements in the DATA step in order for each input observation .

1. The "DATA" statement identifies the start of a DATA step and names the dataset to be created.

	DATA <dataset_name>;
    

2. The "INFILE" statement identifies an external file from which data will be read (see Guide 5 for an example).

	INFILE <file_name>;
    

3. The SET statement copies data from an existing dataset.

	DATA <dataset_name>;
	SET <dataset_name>;
    

4. The "DATALINES" statement is used if you choose to embed data in your program instead of reading it from an external file.

	DATALINES;
    

5. The "INPUT" statement defines variables, their type, and specifies how data is to be read:

	 INPUT <variable_name [type] [position]>;

         Example:
	 i)   INPUT MFG @@; 
	 ii)  INPUT MFG $ TYPE $ SEEK TRANSFER;
	 iii) INPUT MFG $ 1-8 TYPE $ 11-12 SEEK 13-16 TRANSFER 17-19;
    

6. Variables may be given descriptive names (see Guide 3 for an example):

   	 LABEL <variable_name='label'>...;
   
            Example:
   	 i)  LABEL MFG='Manufacturer'; 
   	 ii) LABEL MFG='Manufacturer'  
   	   	      SEEK='Seek Time'; 
   

7. Assignment statements create new variables (see Guide 6 for an example). The usual arithmetic operations are available:

	Symbol Operation             Example

	**     Exponentiation        Z=X**2;
	*      Multiplication        Z=X*Y;
	/      Division              Z=X/Y;
	+      Addition              Z=X+Y;
	-      Subtraction           Z=X-Y;
    

Also, the following math functions are available:
1. Exponential, i.e. e^x where e¹=2.71828183:

	EXP(<variable_name>)
    

2. Natural logarithm, i.e. log_e(x):

	LOG(<variable_name>)
    

3. Square root:

	SQRT(<variable_name>)
    

4. Absolute value, i.e. |x|:

	ABS(<variable_name>)


The example below creates additional variables using some of these functions:

	DATA CDROM;
	INPUT MFG $ TYPE $ SEEK TRANSFER;
	IF SEEK < 15 THEN CLASS='FAST';
	ELSE CLASS='SLOW';
	* CREATE SQRT & LOG TRANSFORMS; 
	LOGTRAN = LOG10(TRANSFER)
	ROOTTRAN= SQRT(TRANSFER);
	DATALINES;
	NEC 12X 7.3 105
	SONY 6X 23.1 830
	... (more data lines)

8. The "DROP" and "KEEP" statements are used to remove variables and all associated values from a dataset :

	DROP <variable_name>...;

removes named variables from the dataset and keeps unnamed variables.

	KEEP <variable_name>...;

keeps named variables and drops unnamed variables from the dataset.
9. The "IF" statement is used for conditional processing. Note that expression is a boolean expression that evaluates to T or F and so statement T is executed if it evaluates to T and statement F if it evaluates to F.
   :

	IF <expression> THEN <statement T>;
	ELSE <statement F>;

Note: The ELSE statement is optional but, if present, must immediately follow the associated IF statement. The IF ... THEN part comprises a single statement:

	i)  IF SEEK < 15 THEN CLASS = 'FAST';
	    ELSE CLASS = 'SLOW';
	ii) CLASS='SLOW';
	    IF SEEK < 15 THEN CLASS = 'FAST';

SAS comparison operators are shown below. You can use either the symbol or the two-letter abbreviation.

	Symbol     Abbrev

	<, <=      LT, LE  
	>, >=      GT, GE  
	=, ^=      EQ, NE  

SAS also provides logical operators for more complex boolean expressions. Either the symbol or word may be used.

	Symbol  Connective

	 &        AND  
	 |        OR  
 	 ^        NOT  

A special form of the "IF" statement is used for subsetting a dataset, that is selecting/excluding particular observations.

	DATA CDROM;
	INPUT MFG $ TYPE $ SEEK TRANSFER;
	IF SEEK < 15;

The statement IF SEEK < 15; is equivalent to:

i)  IF SEEK < 15 THEN OUTPUT;
ii) IF SEEK >=15 THEN DELETE;
    

The example below excludes those observations where seek is 15 or more:

	DATA CDROM;
	INPUT MFG $ TYPE $ SEEK TRANSFER;
	IF SEEK < 15;
	DATALINES;
	NEC 12X 7.3 105
	SONY 6X 23.1 830
	SONY 4X 40.1 330
	CANON 6X 13.5 530
	SONY 12X 5.5 1000

The dataset CDROM will therefore contain observations 1, 4 and 5 only:


	NEC 12X 7.3 105
	CANON 6X 13.5 530
	SONY 12X 5.5 1000

10. Comments:

Two types of comments:

	i)	* ... ;
	ii)	/* ... */
	
	DATA CDROM;
	* Read in variables;
	INPUT MFG $ TYPE $ TRANSFER SEEK;
	/*  ignore next statement
	SEEKMIN = SEEK/60000;
	*/
  



• PROC step statements:

SAS procedures execute predefined procedures which may be either statistical or utility procedures. The data structure processed is the most recently created dataset unless otherwise specified in a "DATA=" option.

	PROC <procedure_name> [option];
	[procedure_statement];
    


"option" typically depends on the procedure but some, such as the "DATA=" option, may be used with all procedures:

	 DATA=<dataset_name>


Note that "procedure_statement" typically depends on the procedure but some may be used with all procedures:

	 VAR <variable_name>;


Indicates which variables are to be analyzed. If this statement is omitted, the default is to include all variables of the appropriate type.



	 BY <variable_name>;


Used primarily with the SORT procedure in which case it cannot be omitted.



	 ID <variable_name>;


Specifies the name of a variable to be used as an observation IDentifier.



	 LABEL <variable_name='label'>;


Assigns a descriptive label to a variable.



	 WHERE <expression>;  


Selects only those observations for which the expression is true.



You should be familiar with the following procedures:

1. Correlations among a set of variables:

	PROC CORR [options];
	  [VAR <variable_name>;  
            WITH <variable_name>;]
    

2. Means, standard deviations, and other univariate statistics (N; MEAN; STD; MIN; MAX; SUM; VAR):

	PROC MEANS [options];
	  [VAR <variable_name>...;]
    

3. Univariate statistics. That is means, standard deviations, median etc. Also provides options to generate a p-value for a normality test and to produce the box plot, stem & leaf and normal plots:

	PROC UNIVARIATE [options];
	  [VAR <variable_name>...;]
    

4. Print a SAS data set:

	PROC PRINT [options];
	  [VAR <variable_name>...;]
    

5. Sort a SAS data set according to one or more variables:

	PROC SORT [options];
	  BY <variable_name>...;
  

6. Plot y against x. May be used to create a scatter plot or a residual plot

	PROC PLOT [options];
 	  PLOT <dep_var_name>*<indep_var_name>='*' [options];

  

7. Produce coefficients of the simple linear regression equation.

	PROC REG [options];
 	  MODEL <dep_var_name>=<indep_var_name>;

  

If residuals are needed then the optional output statement must be included. The dataset specified in the out= option will be created and will include the contents of the original dataset processed in addition to the variable specified in the r= option which will include the residuals.

	PROC REG [options];
 	  MODEL <dep_var_name>=<indep_var_name> [/ option];
 	  OUPUT OUT=<dataset> r=<var_name>;
  

See guide 5 (output) for an example. Also, see this income/gpa sample program.