ANALYTICS

FIND THE ANSWER

TO MAKE ANYTHING WITH PERFECTION

TO MAKE THINGS WORK. THEN, TAKE ACTION TO PRODUCE A RESULT PURPOSEFULLY, MEANINGFULLY AND PRODUCTIVELY.

HOW IT WORKS

01

DATA VALIDATION

THE PURPOSE OF DATA VALIDATION IS TO FIND OUT, AS FAR AS POSSIBLE, WHETHER THE DATA COLLECTION WAS DONE AS PER THE PRE-SET STANDARDS AND WITHOUT ANY BIAS. IT IS A FOUR-STEP PROCESS, WHICH INCLUDES…
FRAUD, TO INFER WHETHER EACH RESPONDENT WAS ACTUALLY INTERVIEWED OR NOT.
SCREENING, TO MAKE SURE THAT RESPONDENTS WERE CHOSEN AS PER THE RESEARCH CRITERIA.
PROCEDURE, TO CHECK WHETHER THE DATA COLLECTION PROCEDURE WAS DULY FOLLOWED.
COMPLETENESS, TO ENSURE THAT THE INTERVIEWER ASKED THE RESPONDENT ALL THE QUESTIONS, RATHER THAN JUST A FEW REQUIRED ONES.

02

DATA EDITING

TYPICALLY, LARGE DATA SETS INCLUDE ERRORS. FOR EXAMPLE, RESPONDENTS MAY FILL FIELDS INCORRECTLY OR SKIP THEM ACCIDENTALLY. TO MAKE SURE THAT THERE ARE NO SUCH ERRORS, THE RESEARCHER SHOULD CONDUCT BASIC DATA CHECKS, CHECK FOR OUTLIERS, AND EDIT THE RAW RESEARCH DATA TO IDENTIFY AND CLEAR OUT ANY DATA POINTS THAT MAY HAMPER THE ACCURACY OF THE RESULTS.
FOR EXAMPLE, AN ERROR COULD BE FIELDS THAT WERE LEFT EMPTY BY RESPONDENTS. WHILE EDITING THE DATA, IT IS IMPORTANT TO MAKE SURE TO REMOVE OR FILL ALL THE EMPTY FIELDS.

03

DATA CODING

THIS IS ONE OF THE MOST IMPORTANT STEPS IN DATA PREPARATION. IT REFERS TO GROUPING AND ASSIGNING VALUES TO RESPONSES FROM THE SURVEY. FOR EXAMPLE, IF A RESEARCHER HAS INTERVIEWED 1,000 PEOPLE AND NOW WANTS TO FIND THE AVERAGE AGE OF THE RESPONDENTS, THE RESEARCHER WILL CREATE AGE BUCKETS AND CATEGORIZE THE AGE OF EACH OF THE RESPONDENT AS PER THESE CODES. (FOR EXAMPLE, RESPONDENTS BETWEEN 13-15 YEARS OLD WOULD HAVE THEIR AGE CODED AS 0, 16-18 AS 1, 18-20 AS 2, ETC.)