There is difference between how SAS handles IF and WHERE
conditions. The 'WHERE' condition is applied on data before
they enter Program Data Vector (PDV) and in case of 'IF' it
is applied after data comes out from PDV. Now, if you have
created a variable in the same data step using 
Where : the created variable will not be applied condition.
IF: the created variable will be subjected to the condition
applied.

Make sure you apply the following rules when determining 
which approach to take when subsetting your data set using 
the DATA step. If your subset condition does not meet the 
requirements below, then the WHERE and IF statements should 
produce identical results. For cases such as this, use the 
WHERE statement since it is more efficient. Note that 
having both WHERE and IF statements within the same DATA 
step has a cumulative effect.
•	Can use WHERE statement when only specifying data 
set variables 
•	Use IF statement when specifying automatic 
variables or new variables created within DATA step 
•	Use IF statement when specifying FIRST.BY or LAST. 
BY variables 
•	Use IF statement when specifying data set options 
such as OBS = , POINT = or FIRSTOBS = 
•	In general, use IF statement when merging data sets 
to apply subset condition after merging data set 
•	Use WHERE statement when specifying indexes

WHERE Statement can be only be used with variables in the 
existing dataset where as IF statement can also be used raw 
data as well

Hi Saggy Desai,

I think you can get Genuine SAS Dumps from: sasiexam@gmail.com

Regards
Bharath

SAS rename is used for variable renaming while lables is 
used to define/alter the lables of the vaiables

The resultant dataset depends on the input datasets.
In case of one to one and one to many  both work 
similarly,i.e. the resultant dataset is same.
But differs in case of many to many and non matching 
datasets:
many to many:
ex:                         (merge on x)  (proc sql)
X  Y              X    Z      X  Y  Z     X  Y  Z     
-----             ------      -------     -------
1  A              1    F      1  A  F     1  A  F
1  C              1    R ---> 1  C  R     1  A  R 
2  B              2    G      2  B  G     1  C  F 
                                          1  C  R
                                          2  B  G  


NON MATCHING DATA:

ex:                         (merge on x)  (proc sql)
X  Y              X    Z      X  Y  Z     X  Y  Z     
-----             ------      -------     -------
1  A              1    F      1  A  F     1  A  F
2  B              3    T ---> 2  B  .     3  C  T
3  C              4    G      3  C  T     
                              4  .  G

Hi Akshara
 
 
You can get latest SAS Certi Dumps from: sasi.vats@gmail.com
 
I took few dumps from him and scored 100 %, he always 
maintains latest dumps
 
 
Regards
Jeevan

hey aksara,
contact this mail id for getting sas related latest info:

certification 
openings
career

Hi Shiva

Yes Shiva, i got A00-211 & A00-212 Dumps from Sasi Vats, 
I got above 96 % Score, 
thanks a tonns to Sasi Vats once again

Thanks
Reshma

Regression is used to model Interval target variables where 
as logistic regression is used to model Categorical 
varaibles. 

Regression Assumptions: Input variables are linearly 
related to target variable and that input variables and  
residuals are normally distributed, and independent with a 
mean of 0 and constant variance.

Logistic Regression: There are no distributional 
requirements for inputs in Logistic regression

Regression Modelling is also called linear modelling as the 
input variables and residuals normally distributed.
the formula generally used here is 
Y = m1x1+m2x2+m3x3+m4x4+c

Where as the logistic modelling is a non linear modelling 
in which input variables and residuals randomly distributed.
The dependent variable has a value of either 1 or 0
the formula we use here is
Y=         1
   --------------------
    1  +  e^-(m1x1+m2x2+m3x3+m4x4)

proc ttest data=a;
paired var1 var2;
run;

I tried the above code.But it worked after I gave * or : 
between var1 and var2.

proc ttest data=a;
paired var1:var2;
run;

using DSD

by using : oprator

by using double trailing operator @@

we can pass the paramters at run time.
here is an example which passes three parameters( 3 dates) 
to a program calles pgm_name:

>sas  pgm_name -sysparm "01aug95 05aug94 10jan60"

Proc Sql;
Select * from <dataset name>
where _n_ in (100,150,180,190);
quit;

Proc Sql;
Select *,monotonic ()as c from <datasetname>
group by a having c in (100,150,180,190);
quit;

Before saying answer is not correct, please try this
Data f;
 do i=1 to 200;
 output;
 end; 
run;

Proc Sql;
Select *,monotonic ()as c from f
group by i having c in (100,150,180,190);
quit;

Proc print;
run;

* Setup test data;
data test;
do i=1 to 200;
j=ranuni(i);
output;
end;
run;

Proc Sql;
Select *,monotonic ()as c from test
having c in (100,150,180,190);
quit;

PROC SQL;
SELECT*,
MONOTONIC() AS COUNT
FROM TEST
HAVING COUNT IN(100,150,180,190);
QUIT;

Hi.

I don t know any specific reason why yu dont wan to use 
proc format. It would be better if you use that as there 
would be probably some more wines in the market where u can 
apply this format of red wine....
Anyways I think you can try this.
* the content in brackets have to come from your program

proc sql;
update [dataset_name];
set [wine_name_field] = "Red Wine" where [wine_name_field]
="Malambo Shiraz Malbec 750ML(0388)";
exit;

let me know in case u require something else.

above answer is correct. Just need to correct syntax 
errors. Following is the corrected code,

proc sql;
update [dataset_name]
set [wine_name_field] = "Red Wine" where [wine_name_field]
="Malambo Shiraz Malbec 750ML(0388)";
quit;

You can use HASH lookup for this. Performnace will depend 
on the data size.

Actually sas stores dates as numbers

eg:: given date  12-07-2009


in sas :: we can store like this `12-07-2009`d

we can store date values using date format 
(ex:date9.,ddmmyyyy10.)

We can read the date value with the help of date informats.
Say we have the date 09/13/2008.
Now if we want SAS to read this date, we will use the date 
informat in the input statement like
"input date mmddyy10."
SAS will store this date in the numerical form as the 
number of days passed from 1st january, 1960.

e.g the date is '05/09/2007'

we can use the input function to convert this string into SAS date i.e.
date='05/09/2007'
sasdate=input(date,mmddyy10.);

Also, we can use mdy function.For this first use substr function.

m=substr(date,4,2);
d=substr(date,1,2);
y=substr(date,7,4);
sasdate=mdy(m,d,y);

If you don't know in advance how the date will be 
formatted, you can use the ANYDTDTE. informat. This will 
extract a SAS date from most date/date-time formats. 
(Warning: ANYDTDTE doesn't fully support day-month-year 
ordering, even if you have this set as your system 
preference, but it still copes with most DMY-formatted 
dates.)

For example if we have a date="14/12/2008".

you have to input it first and the format it like
date1=input(date,ddmmyy10.);
format date1 ddmmyy10.;
run;

data temp;
date='17/12/2009';
m=substr(date,4,2);
d=substr(date,1,2);
y=substr(date,7,4);
d1=mdy(m,d,y);
format d1 mmddyy10.;
run;

Proc tabulates out puts the aggregate values in table

whereas

Proc print used to print the data of a dataset into an out
put window

The PRINT procedure: prints the observations in a SAS data 
set, using all or some of the variables. You can create a 
variety of reports ranging from a simple listing to a 
highly customized report .

The Tabulate procedure : used to print tabular type of 
Reports
and we can find descriptive statistics.

proc print is used to print the observations in the output
proc tabulate is used to print the observations in table 
form
as rows and colums

proc print produces list report output. Proc Tabulate print 
crosstabulation report output.