Statistics with SAS
Technology Short Courses: Fall 2007
(Oct 29, 2007)
Kentaka Aruga
Object of the course
• Performing simple descriptive statistics (proc mean,
proc freq, and proc corr)
• Performing basic test statistics
(Chi-square test, T-test, F-test)
• Basic commands for regression analysis and how
to export the result into a table
(proc reg)
Section 1 Preparation
Getting data and importing data
Getting data
• Download the SAS command that will be used in this practice
from
http://www.uri.edu/its/research/sasstat.txt
• Download the data file that will be used in this course from
http://www.uri.edu/its/research/auto.xls
http://www.uri.edu/its/research/vote.txt
• Save the files under ‘C:/’ drive of your windows computer.
Importing Excel file to SAS
• Open SAS program and copy and paste the
following commands from the file you have just
downloaded “sasstat.txt”:
libname car ‘c:/’;
proc import out= car.auto
datafile=“c:/auto.xls”
dbms=excel2000 replace;
sheet=“auto”;
getnames=yes;
run;
Then highlight the command line and execute the
command.
Proc import
• Look at the ‘trunk’ column
• Do you see an empty column?
• SAS determines the data type based on
the most common data type in the first 8
rows. ‘trunk’ column has mixed
data.(since the first eight columns are all
zero, the remaining columns become all
zero)
Proc import
• Add the following statement
mixed = yes;
• Now the command line should look like
proc import out= car.auto
datafile=“c:/auto.xls”
dbms=excel2000 replace;
sheet=“auto”;
getnames=yes;
mixed = yes;
run;
• Execute this command
Section 2
Performing simple descriptive
statistics (proc mean, proc freq,
and proc corr)
How to perform simple descriptive
statistics (Review from SAS basics
course)
• How would you see the number of obvs, mean,
std, min, and max of all numeric variables in SAS?
Ans.
proc means data=car.auto;
run;
• How do you analyze frequency of the variables?
Ans.
proc freq data=car.auto;
run;
Proc means
• By default “proc means” provides the number of obvs, mean, std,
min, and max of all numeric variables
proc means data=car.auto;
run;
• Specifying a certain variable
– var variable name ;
Q. How would you execute the mean procedure for
the variables “price”, “mpg,” and “weight” ?
• Creating an output table
– output out= file name
Q. How would you get the output for the mean
procedure for the variables “price”, “mpg,”
and “weight”?
Proc means (Answers)
proc means data=car.auto;
output out=car.means;
var price mpg weight;
run;
Proc freq
• By default this procedure creates frequency tables for all
variables
proc freq data=car.auto;
run;
• Specifying a certain variable
– tables variable name
Q. How would you execute the FREQ procedure for the
variable “foreign”?
• Creating an output table
– /out = file name
Q. How would you get the output for the FREQ procedure for
the variable “foreign”?
Proc freq (Answers)
proc freq data=car.auto;
tables foreign /out=car.frn;
run;
Proc freq: Creating a two-way table
• How would you create a two-way
table using the FREQ procedure for the
variables “rep78” and “foreign”?
Ans.
proc freq data=sasuser.auto;
tables rep78*foreign;
run;
Proc freq: two-way table
Total % (= 8/13)
Row % (= 8/9)
Column % (= 8/10)
Proc corr
• The CORR procedure generates ‘Simple Statistics’
based on non missing values, and ‘Pearson
Correlation Coefficient’, an index that quantifies the
linear relationship between a pair of variables
• Insignificant p-value indicates the lack of linear
relationship between the two variables.
Proc corr
• Finding correlations between a pair of
variables
1) All variables
proc corr data=car.auto;
run;
2) Three specific variables
proc corr data=car.auto;
var price mpg weight;
run;
Section 3
Performing basic test statistics
(Chi-square test, T-test, F-test)
Chi-square test of independence
• What is the Chi-square test of independence?
Ans. It tests whether the variable in the row and column
are independent or related
• What is the null hypothesis?
Ans. The variables in the row and column are
independent: there is no relationship between row and
column frequencies
• The command for SAS to test this is provided in the
option of “proc freq”. Simply use chisq.
• To display the expected cell frequency for each cell use
the option “expected.”
Chi-square test of independence:
exercise
There are 34 students in the classroom and there was a
vote on whether they wanted to have a turtle in their
classroom as a pet. The data file “vote.txt” contains the
result of the vote (Yes=y, No=n), and gender of the
students (male=m, female=f).
• Q1 Import the file “vote.txt” into SAS and name the
variables “answers” and “gender.”
• Q2 Using the option “chisq,” test whether or not the
answers to the vote and gender are associated with
each other.
Answers
Q1
data vote;
infile 'c:/vote.txt';
input answers $ gender $;
run;
Q2
proc freq data=vote;
tables answers*gender /expected chisq;
run;
Results
Expect Freq 
Row total (15)  Column total (16)
Table total (34)
What does the result tell you?
• The null hypothesis that
the two variables are
independent is rejected
at even 1% significance
level.
This is lower than 0.01
• The two variables
“answers” and “gender”
are associated with
each other (They are
dependent).
Proc ttest
•
This procedure is used to test the hypothesis of
equality of means for two normal populations
from which independent samples have been
obtained.
–
Three cases in SAS
• One-sample t-test
•
•
– Computes the sample mean of the variable and
compares it with a given number.
Two-sample t-test
– Compares the mean of the first sample minus the
mean of the second sample to a given number.
Pair observations t-test
– Compares the mean of the differences in the
observations to a given number.
Assumptions of “proc ttest”
• The observations are random samples drawn from normally
distributed populations. This can be tested using the
UNIVARIATE procedure
– If the normality assumptions are not satisfied: use NPAR1WAY
procedure.
• Two populations of a group comparison must be
independent.
– If not independent, you should question the validity of a paired
comparison.
• The default null hypothesis is set as equal to zero. To
change this you can use H0=‘number’.” e.g. h0=10
• The default confidence level is 5%. To change this you can
use alpha=‘confidence level’.” e.g. alpha=0.01
Source: http://www.okstate.edu/sas/v8/saspdf/stat/chap67.pdf
Proc ttest: exercise
• How would you perform a t-test on mpg
variable classified by foreign variable?
Hint: use “class” and “var” statement
• What will the null hypothesis be in this
case?
Proc ttest (Cont’d)
• The command
proc ttest data=car.auto;
class foreign;
var mpg;
run;
– CLASS statement: contains a variable that distinguishes
the groups being compared.
– VAR statement: specifies the response variable to be used
in calculations.
• The null hypothesis
H 0 : domestic  foreign  0
• The alternative hypothesis
H1 : domestic  foreign  0
See here
High high
p-value
• The first table shows the basic statistics
• The second table is the t-test for equal mean. Before using this
table you need to look at the third table to determine if the
assumption of equal variances is reasonable
• The third table is a test of equal variances
• In this example the null hypothesis of equal variance is not
rejected.
• Thus you need to look at the “equal variance” in the second table.
The second table suggests there is not a difference in means
across domestic and foreign car.
Section 4
Basic commands for regression analysis and
how to export the result into a table
(proc reg)
Regression analysis
• Regression analysis : finding a reasonable
mathematical model of the relationship
between a response variable (y) and a set
of explanatory variables (x1, x2,…. xP)
• General model
y   0  1 x1   2 x2 
  p xp  
Proc reg
• General command
proc reg data = file name
model DV = IV ;
run;
DV: dependent variable IV: independent variable
• This procedure also does the following testing:
– F-test:
Tests the null hypothesis that none of the independent
variables has any effect
– T-test
Tests for each IV the null hypothesis that the independent
variable has no effect toward the dependent variable.
Proc reg: exercise
• Let ‘price’ be a response variable (dependent
variable (DV)), and ‘mpg’ and ‘length’ be explanatory
variables (independent variables (IV))
Q1 What will be the commands?
Q2 What null hypotheses will be tested?
Q3 Will the model be significant?
Proc reg: answers
Q1 proc reg data = car.auto;
model price = mpg length;
run;
Q2 F-test H 0 : price  0  
H1 : price  0  1mpg  2length  
T-test H 0 : i  0
H1 :  i  0
Proc reg
Q3
Proc reg: Confidence and
prediction interval
• Constructing 95% confidence and
prediction interval by adding two options,
‘clm’ and ‘cli’
• How would you add these options in the
case of previous model?
proc reg data=car.auto;
model price = mpg length / clm cli;
run;
Proc reg: creating an output table
• Add “outest = file name” after the “proc reg”
command
proc reg data=car.auto
outest=car.est1;
model price = mpg length /clm cli;
run;
quit;
• In order to see the output data file “car.est1” you
need to add the statement “quit” in the end.
• You can drop the categories you do not want to see by
using the “keep” or “drop” statement
e.g.
data car.est2 (keep=intercept mpg length);
set car.est1;
run;
data car.est3 (drop=price _model_ _depvar_ _type_
_RMSE_);
set car.est1;
run;
Proc reg: creating an output table
• To see other outputs go to “Help” and type in
“REG” and go into “The REG procedure.”
Click “Syntax”
Click Here
Exporting the output data to Excel
• General commands
proc export data = Name of the SAS data file you
are exporting
outfile = “The name of the drive or the pass to the
folder of your computer”
dbms = excel2000 replace;
run;
• How would you export the file “car.est2” into an Excel
file?
Ans. proc export data = car.est2
outfile = “c:/est.xls"
dbms = excel2000 replace;
run;
Useful supports: other useful sites
• Online SAS manuals
http://www.uri.edu/sasdoc
This will automatically link you to
http://support.sas.com/documentation/onlinedoc/
sas9doc.html
• Statbookstore: useful site for finding program
examples
http://www.geocities.com/statbookstore/
For further Questions:
kentaka@mail.uri.edu