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[BEST & NEW] Base SAS Interview Questions and Answers

Last updated on 24th Dec 2022, Blog, Interview Question

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1. Distinction between INPUT and INFILE?

Ans:

In contrast to the INPUT statement, which is used to define your variables, the INFILE statement is used to locate an external file.

  • FILENAME take a look at ‘C:\DEEP\File1.xls’;
  • DATA READING;
  • INFILE TEST;
  • LENGTH NAME $25;
  • INPUT ID NAME$ SEX;
  • RUN;

Note : The variable name, followed by $ (dollar sign), identifies the variable sort as character. within the example shown on top of, ID and SEX area unit numeric variables and Name a personality variable.

2. Distinction between Informat and Format?

Ans:

Informats browse the information whereas Formats write the information. Informat is to inform SAS that variety ought to be browsed in a very specific format. For example: The informant mmddyy6. Tells SAS to browse the number121713as the date Dec seventeen, 2013. Format is to inform SAS the way to print the variables.

3. Distinction between Missover and Truncover?

Ans:

    MissoverTruncover
    When the MISSOVER possibility is employed on the INFILE statement, the INPUT statement doesn’t jump to consecutive lines once reading a brief line. Instead, MISSOVER set variables to missing. It assigns the information worth to the variable though the worth is shorter than the length that’s expected by the INPUT statement.

The subsequent is AN example of AN external file that contains data:

  • 1
  • 22
  • 333
  • 4444

This information step uses the numeric in format four. to browse one field in every record of information and to assign values to the variable ID.

  • data reading;
  • infile ‘external-file’ missover;
  • input ID4.;
  • run;
  • proc print data=reading;
  • run;

The output is shown below :

    ObsID
    1 .
    2 .
    3 .
    four 4444
  • Truncover
  • data reading;
  • infile ‘external-file’ trun cover;
  • input ID4.;
  • run;
  • proc print data=reading;
  • run;

The output is shown below :

    ObsID
    1 1
    2 22
    3 333
    four 4444

4. Describe the Purpose of double trailing@@ in Input Statement ?

Ans:

The double trailing sign (@@)tells SAS instead of advancing to a brand new record, hold the present input record for the execution of consecutive INPUT statements.

  • DATA Reading;
  • Input Name $ Score @@;
  • cards;
  • Sam twenty five David thirty Ram thirty five
  • Deeps twenty Daniel forty seven Pars eighty four
  • ;
  • RUN;

The output is shown below :Double Trailing

5. The way to embrace or exclude specific variables in a very information set?

Ans:

The DROP statement specifies the names of the variables that you just wish to get rid of from the information set.

  • data readin1;
  • set reading;
  • drop score;
  • run;

The KEEP statement specifies the names of the variables that you just wish to retain from the information set.

  • data readin1;
  • set reading;
  • keep var1;
  • run;

The main distinction between DROP/ KEEP statement and DROP=/ KEEP=data set possibility is that you just can’t use DROP/KEEP statements in procedures.

  • data readin1 (drop=score);
  • set reading;
  • run;
  • data readin1 (keep=var1);
  • set reading;
  • run;

6. The way to print observations five through ten from an information set?

Ans:

The FIRSTOBS= and OBS=data set choices would tell SAS to print observations five through ten from the information set READING.

  • proc print information = reading (firstobs=5 obs=10);
  • run;

7.What area unit the default statistics that PROC suggests that produce?

Ans:

PROC suggests that turn out the “default” statistics of N, MIN, MAX, MEAN and STD DEV.

8. Name and describe functions that you just have used for information cleaning?

Ans:

SAS Character Functions.

9.Difference between operate and PROC.

Ans:

  • The MEAN operation is a mean of the worth of many variables in one observation.
  • The average that’s calculated mistreatment PROC suggests is that the total of all of the values of a variable divided by the quantity of observations within the variable.
  • In alternative words,The MEAN operation can total across the row and a procedure can total down a column.

10. Variations between WHERE and IF statement?

Ans:

    WHERE IF
    WHERE statements are often utilized in procedures to set information . IF statements can’t be utilized in procedures.
    WHERE are often used as an information set possibility . IF can’t be used as an information set possibility.
    The WHERE statement is a lot more economical than the IF statement. It tells SAS to not browse all observations from the information set.
    WHERE statements are often accustomed to explore for all similar character values that sound alike as. IF statements can’t be used.
    WHERE statements can’t be used once reading information mistreatment INPUT statements. IF statements are often used.
    Multiple IF statements are often accustomed execute multiple conditional statements. When it’s needed to use freshly created variables, useIF statement because it doesn’t need variables to exist within the READING information set.

11.What is Program information Vector (PDV)?

Ans:

PDV could be a logical space within the memory.

12. What’s information _NULL_?

Ans:

The DATA _NULL_ is principally accustomed to producing macro variables. It may be accustomed to write output while not making a dataset.The idea of “null” here is that we’ve an information step that really doesn’t produce an information set.

13. What’s the distinction between ‘+’ operator and total function?

Ans:

SUM operator returns the total of non-missing arguments whereas “+” operator returns a missing price if any of the arguments are unit missing.

Suppose we’ve a knowledge set containing 3 variables – X, Y and Z. all of them have missing values. we tend to want to reckon the total of all the variables.

14.Why has no price been deleted once the NODUP choice is used?

Ans:

Although ID three has 2 identical records (See observation five and 7), the NODUP choice has not removed them. it’s as a result of they’re not next to at least one another within the dataset and SAS solely appears at one record back.

To fix this issue, type on all the variables within the dataset READING.

To type by all the variables while not having to list all of them within the program, you’ll be able to use the keywork.

  • ‘_ALL_’in the BY statement (see below).
  • PROC type DATA=reading NODUP;
  • BY _all_;
  • RUN;
  • The output is shown below :
  • SAS NODUP Output

15. Distinction between NODUP and NODUPKEY Options?

Ans:

The NODUPKEY choice removes duplicate observations wherever price of a variable listed in BY statement is perennial whereas NODUP choice removes duplicate observations wherever values altogether the variables are unit perennial (identical observations).

16. What area unit _numeric_ and _character_ and what do they do?

Ans:

    1. 1. _NUMERIC_ specifies all numeric variables that are already outlined within the current knowledge step.
    2. 2. _CHARACTER_ specifies all character variables that are presently outlined within the current knowledge step.
    3. 3. Unmitigated specifies all variables that are presently outlined within the current knowledge step.

Example : To incorporate all the numeric variables in PROC suggests that.

  • proc means;
  • var _numeric_;
  • run;

17. A way to type in down order?

Ans:

Use the down keyword in PROC type code. The instance below shows the utilization of the down keyword.

  • PROC type DATA=auto;
  • BY down engine ;
  • RUN ;

18. Below what circumstances would you code a pick construct rather than IF statements?

Ans:

When you have a protracted series of reciprocally exclusive conditions and also the comparison is numeric, employing a choose cluster is slightly more economical than victimization IF-THEN or IF-THEN-ELSE statements as a result of electronic equipment time is reduced.

The syntax for choose once is as follows :

  • SELECT (condition);
  • WHEN (1) x=x;
  • WHEN (2) x=x*2;
  • OTHERWISE x=x-1;
  • END;
  • Example :
  • SELECT (str);
  • WHEN (‘Sun’) wage=wage*1.5;
  • WHEN (‘Sat’) wage=wage*1.3;
  • OTHERWISE DO;
  • wage=wage+1;
  • bonus=0;
  • END;
  • END;

19. A way to convert a numeric variable to a personality variable?

Ans:

You must produce a differently-named variable victimization the place operates.

The example below shows the utilization of the place.

  • charvar=put(num var, 7.) ;

20. The way to convert a personality variable to a numeric variable?

Ans:

You must produce a differently-named variable mistreatment the INPUT function.

The example below shows the employment of the INPUT perform.

  • number=input(charvar,4.0);

21. What’s the distinction between volt-ampere A1 – A3 and volt-ampere A1 — A3?

Ans:

Single Dash : It is employed to specify consecutively numbered variables. A1-A3 implies A1, A2 and A3.

Double-dash : It is employed to specify variables supporting the order of the variables as they seem within the file,regardless of the name of the variable. A1–A3 implies all the variables from A1 to A3 within the order they seem within the knowledge set.

Example :The order of variables in an exceedingly knowledge set : ID Name A1 A2 C1 A3.

So mistreatment A1-A3 would returnA1 A2 A3. A1–A3 would returnA1 A2 C1 A3.

22. Distinction between PROC means that and PROC SUMMARY?

Ans:

    PROC means thatPROC SUMMARY
    Proc means that by default produces written output within the OUTPUT window whereas Proc outline doesn’t. Inclusion of the PRINT possibility on the Proc outline statement can output results to the output window. Omitting the volt-ampere statement in PROC means that analyses all the numeric variables whereasOmitting the variable statement in PROC outline produces an easy count of observation.

23. A way to do Matched Merge and output solely consisting of observations from each file?

Ans:

Use IN=variable in MERGE statements. It’s used for matched merges to trace and choose that observations within the knowledge set from the merge statement can lead to a replacement knowledge set.

  • data reading;
  • merge file1(in=infile1)file2(in=infile2);
  • by id;
  • if infile1 ne infile2;
  • run;

24. A way to do Matched Merge and output consisting of observations from solely file1?

Ans:

  • knowledge reading;
  • merge file1(in=infile1)file2(in=infile2);
  • by id;
  • if infile1;
  • run;

25. However, do I produce a knowledge set with observations=100, mean zero and variance 1?

Ans:

  • data reading;
  • do i=1 to 100;
  • temp=0 + rannor(1) * 1;
  • output;
  • end;
  • run;
  • proc suggests that data=reading mean std dev;
  • var temp;
  • run;

26. A way to label values and use it in PROC FREQ?

Ans:

Use PROC FORMAT to line up a format.

  • proc format;
  • value score zero – 100=‘100-‘
  • 101 – 200=‘101+’
  • other=‘others’
  • ;
  • proc freq data=reading;
  • tables outdata;
  • format outdata score. ;
  • run;

27. A way to use arrays to rearrange a group of variables?

Ans:

Recode the set of questions: Q1,Q2,Q3…Q20 within the same way: if the variable features a price of vi rearrange it to SAS missing.

  • data reading;
  • set outdata;
  • array Q(20) Q1-Q20;
  • do i=1 to 20;
  • if Q(i)=6 then Q(i)=.;
  • end;
  • run;

28. A way to use arrays to rearrange all the numeric variables?

Ans:

Use _numeric_ and dim functions within the array.

  • data reading;
  • set outdata;
  • array Q(*) _numeric_;
  • do i=1 to dim(Q);
  • if Q(i)=6 then Q(i)=.;
  • end;
  • run;

Note : DIM returns a complete count of the amount of parts in the array dimension letter of the alphabet.

29. A way to calculate mean for a variable by group?

Ans:

Suppose Q1 may be a numeric variable and Age a grouping variable. you want to cypher the mean for Q1 by Age.

  • PROC suggests that DATA=READING;
  • VAR Q1;
  • CLASS AGE;
  • RUN;

30. A way to generate cross tabulation?

Ans:

  • Use PROC FREQ code.
  • PROC FREQ DATA=auto;
  • TABLES A*B ;
  • RUN;
  • SAS can turn out a table of A by B.

31. A way to generate elaborate outline statistics?

Ans:

  • Use PROC UNIVARIATE code.
  • PROC UNIVARIATE DATA=READING;
  • CLASS Age;
  • VAR Q1;
  • RUN;

Note : Q1 may be a numeric variable and Age a grouping variable.

32. A way to count missing values for numeric variables?

Ans:

Use PROC suggests that with NMISSoption.

33. A way to count missing values for all variables?

Ans:

  • proc format;
  • value $missfmt ‘ ‘=’Missing’ other=’Not Missing’;
  • value miss fmt .=’Missing’ other=’Not Missing’;
  • run;
  • proc freq data=one;
  • format _CHAR_ $missfmt.;
  • tables _CHAR_ / missing missprint no cum no percent;
  • format _NUMERIC_ missfmt.;
  • tables _NUMERIC_ / missing missprint no cum no percent;
  • run;

34. Describe the ways that during which you’ll produce macro variables

Ans:

There area unit five ways that to make macro variables:

  • %Let.
  • Iterative you are doing statement.
  • Call Symput.
  • Proc SQl into clause.
  • Macro Parameters.

35. Use of decision SYMPUT

Ans:

CALL SYMPUT puts the worth from a dataset into a macro variable.

  • proc suggests that data=test;
  • var x;
  • output out=testmean mean=x bar;
  • run;
  • data _null_;
  • set testmean;
  • call symput(“xbarmac”,xbar);
  • run;
  • %put mean of x is & bar mac;

36. What area unit SYMGET and SYMPUT?

Ans:

SYMPUT puts the worth from a dataset into a macro variable whereas SYMGET gets the value from the macro variable to the dataset.

37. That date advances a date, time or datetime price by a given interval?

Ans:

The INTNX performs a date, time, or datetime price by a given interval, and returns a date, time, or datetime price. Ex: INTNX(interval,start-from,number-of-increments,alignment).

38. A way to count the amount of intervals between 2 given SAS dates?

Ans:

INTCK(interval,start-of-period,end-of-period) is an associate degree interval that counts the amount of intervals between 2 offered SAS dates, Time and/or datetime.

39. Distinction between SCAN and SUBSTR?

Ans:

SCAN extracts words among a worth that’s marked by delimiters. SUBSTR extracts a little of the worth by stating the precise location. It’s best used once we apprehend the precise position of the substring to extract from a personality price.

40. The subsequent knowledge step executes:

Ans:

  • Data strings;
  • Text1=“MICKEY MOUSE & DONALD DUCK”;
  • Text=scan(text1,2,’&’);
  • Run;

41. For what purpose would you utilize the RETAIN statement?

Ans:

A RETAIN statement tells SAS to not set variables to missing once going from this iteration of the information step to ensuing. Instead, SAS retains the values.

42. Once grouping is in result, will the wherever clause be employed in PROC SQL to set data?

Ans:

No. so as to set knowledge once grouping is in result, the HAVING clause should be used. The variable per the clause should contain outline statistics.

PROC SQL created simple.

43. A way to use IF THEN ELSE in PROC SQL?

Ans:

  • PROC SQL;
  • SELECT WEIGHT,
  • CASE
  • WHEN WEIGHT BETWEEN zero AND fifty THEN ’LOW’
  • WHEN WEIGHT BETWEEN fifty one AND seventy THEN ’MEDIUM’
  • WHEN WEIGHT BETWEEN seventy one AND one hundred THEN ’HIGH’
  • ELSE ’VERY HIGH’
  • END AS NEW WEIGHT FROM HEALTH;
  • QUIT;

44. A way to take away duplicates mistreatment PROC SQL?

Ans:

  • Proc SQL no print;
  • Create Table entomb.Merged one as
  • Select distinct * from entomb.reading ;
  • Quit;

45. A way to count distinct values by a grouping variable?

Ans:

You can use PROC SQL with COUNT(DISTINCT variable_name) to see the amount of distinctive values for a column.

46. A way to merge 2 information sets victimization PROC SQL?

Ans:

PROC SQL Merging.

47. Distinction between past and %SYSEVALF.

Ans:

%EVAL cannot perform arithmetic calculations with operands that have the floating purpose values. it’s once the %SYSEVALF operation comes into image.

  • %let last=%eval (4.5+3.2);
  • %let last2=%sysevalf(4.5+3.2);
  • %put 2;

48. A way to rectify SAS Macros.

Ans:

There area unit some system choices that may be wont to rectify SAS Macros:

MPRINT, MLOGIC, SYMBOLGEN.

49. That is a lot of faster- information Step / Proc SQL.

Ans:

The SQL procedure performed higher with the smaller datasets (less than approx. one hundred MB) whereas the information step performed higher with the larger ones (more than approx. 100 MB).

It is as a result of the information step that handles every record consecutively thus it ne’er uses plenty of memory, however, it takes time to method one at a time. Thus with a smaller dataset, the information step goes to require longer causing every record through.

With the SQL procedure, everything is loaded up into memory quickly. By doing this, the SQL procedure will method tiny datasets rather quickly since everything is on the market in memory. Conversely, once you move to larger datasets, your memory will get stalled, which then results in the SQL procedure being a bit slower compared to the information step which can ne’er take up an excessive amount of memory area.

50. A way to save log in Associate in Nursing external file.

Ans:

  • Use PROC PRINTTO
  • proc print to log=”C:\Users\Deepanshu\Downloads\LOG2.txt” new;
  • run;

51. However, information Step Merge and PROC SQL handle many-to-many relationships?

Ans:

Data Step MERGE doesn’t produce an intersection inclose of a many-to-many relationship. Whereas, Proc SQL produces an intersection.

52. What’s the employment of ‘BY statement’ in information Step Merge?

Ans:

Without ‘BY’ statement, information Step Merge performs merging while not matching. In alternative words, the records area unit combined supported their relative position within the information set. The second information set gets placed to the “right” of the primary information set (no matching supports the distinctive symbol – if information isn’t sorted and supports distinctive symbols, wrong records are often merged).When you use the ‘BY’ statement, it matches observations in line with the values of the BY variables that you simply specify.

53. Use of Multiple SET Statements.

Ans:

SAS : Use of Multiple SET Statements.

54. A way to mix tables vertically with PROC SQL.

Ans:

PROC SQL : Mix tables vertically.

55. 2 ways in which to reverse order of information.

Ans:

Reverse order of information.

56 . Explain about some common errors that are sometimes committed in SAS programming.

Ans:

  • Enlisted below are a number of the common errors that are sometimes committed particularly once you are unaccustomed to this programming language.
  • The basic syntax includes a punctuation at the top of every statement and missing a punctuation is the most typical mistake.
  • Commenting errors like failing to use comments wherever necessary or victimization comments in an inappropriate approach.
  • No victimization correct debugging ways.

57 . Mention SAS system choices to right SAS macros.

Ans:

To help in trailing the macro code still because the SAS code generated by the macros, some system choices are used.

58 . Explain about the Difference between SAS functions and SAS procedures.

Ans:

The major variations are discovered/understood by the case explained for each SAS functions and Procedures.

Case.

For operation, argument price is equipped or say taken for calculation across the observation mentioned within the program statement whereas, within the case of Procedure, each observation is anticipated to possess only 1 variable through that calculation is completed as mentioned within the below example.

59 . What does one realize SYMPUT and SYMGET?

Ans:

The major variations between the 2 are mentioned below.

SYMPUT is employed for storing the worth of an information set into the macro variable whereas SYMGET is employed for retrieving the worth from the macro variable to the information set.

60 . Explain about the special input delimiters utilized in SAS programming.

Ans:

The special input delimiters utilized in SAS programming are.

  • DLM
  • DSD

61 . Is that operator employed to count the quantity of intervals between 2 SAS dates?

Ans:

Interval operator INTCK is employed for investigating the quantity of intervals between 2 given SAS dates.

62 . If you’ve got CRT, if you’ve got what you say, what did you say?

Ans:

  • Yes, I even have created a patient profile for my manager’s demands and statistics.
  • I use PROC contents and PROC SQL to make a listing of easy patients with all info about a couple of specific patients, as well as age, gender, race etc.

63 . Have you ever created traffic files?

Ans:

Yes, I even have a replica of the proximity and also the federal agency. I even have created SAS XPort files victimizing the information type for submissions. These are version five files.

We use information in every x port transport format, with the Lybin Engine and Proc Copy procedure. For version five. Labels are forty bytes, variable names are eight bytes, and also the character variables are two hundred bytes.

Because SAS x port format complies with SAS five databases, these restrictions are withheld by your copy method restrictions. Libname Dtm “c. sdtm_data”; Libname Xport “c.

64 . However, does one take a look at the plan?

Ans:

  • Before you write “test aim” you would like to examine “operational notes”.
  • Functional notes are default passionate about “requirements”, that the necessities and useful notes to put in writing a take a look at set up ought to be clearly understood.

65 . What’s the distinction between verification and validation?

Ans:

While verification and validation are on the point of what that means, “verification” is quite simply checking the accuracy or accuracy of an announcement, or experimenting, whereas it conjointly contains a sense of “true” declaring an announcement with an indication of official endorsement.

66 . What’s Proc Cdisc?

Ans:

It comes as a part of the new SAS procedure and SAS nine.1.3, that is the SAS eight.2 version.

PROC CDISC could be a method (CDISC permits the XML files to be compatible with the CDISC ODM version one.2 Schema, for a lot of details on the SAS programming pharmaceutical manuscript.

67 . Describe Sdtm?

Ans:

The CDISC’s analysis knowledge Index Model (SDTM) was developed to get the quality submitted to the federal agency.

68. What are the Mao Libraries?

Ans:

  • Macro Libraries are libraries that store all the macros for the event of TLG for clinical trials.
  • These are necessary to manage and manage macros. With the assistance of the embody statement; The macros hold on within the Macro library are mechanically known as.

69 . Why does one use ODS?

Ans:

  • ODS (output delivery system) is often accustomed to generate output of tables, lists, and diagrams.
  • Creates ODS outputs in markup language, pdf and rtf formats.

70 . What’s Great?

Ans:

If a case is filed by an associate NDA, the C-reactive protein ought to send it to the federal agency.

71. A way to produce statistics victimization ProcSql?

Ans:

  • Yes, we will produce statistics like ST, SQL, N, average, average, max, at least, STD & SUM.
  • However, the SQL procedure doesn’t figure higher than statistics as a result of it applying to PROC means that.

72 . Once victimized ProcSql?

Ans:

  • All the functions within the knowledge type for knowledge formation and manipulation of knowledge are known as LLC.
  • Supports the procedure. Compared to constant results obtained from SQL and knowledge type, PROC SQL needs less code, and a lot of significantly it needs less time to run the code.

73 . What’s the procedure used to produce a statement?

Ans:

Proc Report, proc table and knowledge _null_.

74 . What’s the distinction between Stratum and opinion within the project life?

Ans:

We see the BY statement with PROC LIFETEST to urge individual analyzes in observations outlined by BY variables.

75 . What are the advantages of victimization sauces in Clinical knowledge Management?

Ans:

Need less hardware and fewer workers.

76 . Make a case for the verification process?

Ans:

  • The verification method is employed to verify the output of the SAS program, which was created by the supply engineer.
  • Write a program and write the output to the validator during this method.

78 . Are you able to get some values that dissipate from knowledge during a totally different computer code application? However, is the area unit doing it?

Ans:

Use a macro. optimistically place statement.

79 . If you have got registered, can you get previous records?

Ans:

Using punctuation Ident .

80 . What’s the value? Why do you calculate? What area unit the procedures you’ll use?

Ans:

If bigger than P-value zero.05, freelance variables with freelance variables cannot be associated with a relative constant relationship, or the freelance variables cluster cannot be attributable to a reliable variable.

Whether freelance variables foreseen the band’s reliable speed, it’s AN overall assessment to assess freelance freelance variables that don’t have any ability to calculate the freelance variability.

81 . What does one sometimes do with Proc’s life test?

Ans:

  • Prose life is employed to get Kaplan-Meier and Life Table survival estimates (and layers).
  • ProcLifetest uses a tier statement that compares the statistics for various teams.

82. What would be the worth of a month at the top of information step execution and the way several observations would be there?

Ans:

  • Value of month would be thirteen and No. of observations would be one.
  • Because the output statement isn’t nominal within the do loop statement.
  • By Default, output statements are going to be written when the do loop finish statement.

83 . However, does one use the do loop if you don’t have skills again and again must you execute the do loop?

Ans:

We can use do till or do whereas to specify the condition.

84 . If reading a variable length file with mounted input, however, would you forestall SAS from reading the following record if the last variable didn’t have a value?

Ans:

  • By exploitation the choice MISSOVER within the infile statement.
  • If the input of some knowledge lines area unit shorter than others then we have a tendency to use TRUNCOVER choice within the infile statement.

85 . However would you produce multiple observations from one observation?

Ans:

  • The double trailing not solely prevents SAS from reading a brand new record into the input buffer once a brand new INPUT statement is encountered, however it conjointly prevents the record from being free once the program returns to the highest of the info step.
  • The trailing @ doesn’t hold a record within the input buffer across iterations of the info step.
  • @@ hold a record across iterations of information steps.
  • SAS can hold the road of information till it reaches either {the finish|the top|the tip} of the road or AN INPUT statement that doesn’t end with the trailing@@.

86 . What’s referred to as a year cut off?

Ans:

  • This worth determines the beginning of a 100-year interval that SAS uses once it encounters a two-digit year.
  • With a YEARCUTOFF worth of 1920, all two-digit years are unit within the interval from 1920 to 2019.
  • That is why the primary date (8/10/65) is given the worth 8/10/1965 and also the second date (9/13/02) is given the worth 9/13/2002.

87 . However, does one print all the numeric and character variables of a dataset?

Ans:

By exploitation _numeric_ and _character_ , we will print all the numeric and character variables of the dataset.

88 . What’s a Program knowledge Vector?

Ans:

  • It is a logical memory space wherever SAS reads observations one at a time to create the SAS dataset. once a program executes.
  • Data from raw file is browse into Input buffer then into PDV one observation at a time.
  • The data/observation is directly browse into PDV, once SAS is reading from a SAS dataset.
  • At the end. from PDV, SAS writes the values to a SAS Output knowledge set as one observation.
  • Along with knowledge set variables and computed variables, the PDV contains 2 automatic variables, finish and _ERROR_.

89 . However does one use the SAS perform with macro facility?

Ans:

Yes, by exploitation the %SYSFUNC macro performs.

90 . What area unit compile time and run time quoting functions?

Ans:

Compile Time Quoting Functions:

%NRSTR–masks % signs and ampersands additionally to the opposite special characters.

Run Time Quoting Functions.

%BQUOTE–masks special characters and method unresolved values throughout macro execution.

91 . However we will decide Macros With In knowledge Step?

Ans:

We can decision the macro with:

  • CALL SYMPUT,
  • Proc SQL ,
  • %LET statement. and macro parameters.

92 . If you utilize A Symput during a knowledge Step, once And wherever are you able to Use The Macro Variable?

Ans:

  • The macro variable created by the decision SYMPUT routine can not be utilized in a similar knowledge step within which it was created.
  • Other than that we will use the macro variable at any time.

93 . However does one type an oversized dataset?

Ans:

  • Make your knowledge set smaller. eliminate all surplus variables and set the LENGTH of variables to be not over necessary (e.g., three for dummy variables, four for integers, etc,).
  • These cut back the dimensions of the file to be sorted dramatically & must always be done (if you haven’t already).
  • With knowledge files of this size you would like to suppose arduous regarding a way to cut back file size.

94 . What’s SQL-Pass through Facility?

Ans:

  • The SQL Procedure pass-through facility is AN extension of the SQL procedure that permits you to send DBMS-specific statements to a DBMS and to retrieve DBMS knowledge.
  • You specify DBMS SQL syntax rather than SAS SQL syntax after you use the pass-through facility.
  • You can use pass-through facility statements during a PROC SQL question or store them during a PROC SQL read.

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