TYPES OF SAMPLING

• TYPES OF SAMPLING
  PAPER 1 FOR NET AND NET COMMERCE/MGMT/ECONOMICS
• METHOD OF DATA COLLECTION
• COMPLETE ENUMERATION METHOD:_ DATA ARE COLLECTED FOR EACH AND EVERY UNIT(PERSON,FIELD,SHOP,FACTORY ETC) BELONGING TO POPULATION OR UNIVERSE
• SAMPLE : SAMPLING IS ONLY A TOOL WHICH HELPS TO KNOW THE FEATURES OF THE UNIVERSE OR POPULATION BY EXAMINING A SMALL PART OF IT.THE VALUE OBTAINED FROM THE STUDY OF SAMPLE SUCH AS AVERAGE OR VARIANCE ARE KNOWN AS STATISTIC AND ON THE OTHER HAND SUCH VALUES FOR THE POPULATION ARE CALLED PARAMETERS.
• MEANING OF SAMPLING
• AS THE PROCESS OF SELECTING CERTAIN MEMBERS OR SUBSETS OF THE POPULATION TO MAKE STATISTICAL CONCLUSIONS FROM THEM AND TO ESTIMATE CHARACTERISTICS OF THE WHOLE POPULATION.
• POPULATION:-CONSISTS OF THE TOTALITY OR AGGREGATE OF THE OBSERVATION WITH WHICH THE RESEARCHER IS CONCERNED. IT SHOULD BE CLEARLY DEFINED SO THAT THE SAMPLE CAN BE ACCURATELY DEFINED.
• SAMPLE: IS SUBSET OF THE POPULATION THAT IS SELECTED FOR STUDY
• SAMPLING IS THE PROCESS OF CHOOSING A REPRESENTATIVE PORTION OF THE ENTIRE POPULATION

• TERMINOLOGY
• ELEMENTS: THE MOST BASIC UNITS ABOUT WHICH INFORMATION IS COLLECTED
• REPRESENTATIVENESS MEANS THE SAMPLE MUST BE LIKE THE POPULATION IN AS MANY WAYS POSSIBLE
• THE SPECIFIC POPULATION TYPE:-
• TARGET POPULATION:-IS A GROUP OF INDIVIDUALS WHO MEETS THE CRITERIA
• RESPONDENT POPULATION:-GROUP OF INDIVIDUALS PARTICIPATION IN THE STUDY
• SAMPLING FRAME DESCRIBES THE COMPLETE LIST OF SAMPLING UNITS FROM WHICH THE SAMPLE IS TAKEN
• SAMPLE IS CHOSEN BY ON SOME ELIGIBILITY CRITERIA AND IT MAY INCLUDE GENDER,AGE,MARITAL STATUS INCOME ETC
• SAMPLING UNIT REFERS TO SPECIFIC PLACE OR LOCATION FROM WHERE DATA WILL BE COLLECTED
• SAMPLING FRAME:-DESCRIBES THE COMPLETE LIST OF SAMPLING UNITS FROM WHICH THE SAMPLING UNITS IS DRAWN
• DETERMINE THE SAMPLE SIZE

• TYPES OF SAMPLING TECHNIQUES
• PROBABILITY SAMPLING: IS A SAMPLING TECHNIQUE IN WHICH SAMPLE FROM A LARGER POPULATION ARE CHOSEN USING A METHOD BASES ON THE THEORY OF PROBABILITY. IT CONSIDER EVERY MEMBER OF THE POPULATION AND SAMPLE IS SELECTED ON THE BASIC OF FIXED PROCESS
• NON PROBABILITY SAMPLING:-IS a sampling technique where the samples are gathered in a process that does not give all the individuals in the population’s equal chances of being selected.
• PRINCIPLE OF SAMPLING
• PRINCIPLE OF STATISTICAL REGULARITY: _DERIVED FROM THE MATHEMATICAL THEORY OF PROBABILITY. THIS PRINCIPLES POINTS OUT THAT IF SAMPLE IS TAKEN AT RANDOM FROM A POPULATION IT IS LIKELY TO POSSESS ALMOST THE SAME FEATURES AS THAT OF THE POPULATION. BY RANDOM SELECTION WE MEAN A SELECTION WHERE EACH AND EVERY ITEM OF THE POPULATION HAS AN EQUAL CHANCE OF SELECTED.
• PRINCIPLE OF INERTIA OF LARGE NUMBERS: OTHER THINGS EQUAL THE LARGER THE SIZE OF THE SAMPLE,MORE ACCURATE THE RESULTS LIKELY TO BE

• NON PROBABILITY

1. CONVENIENCE
2. QUOTA
3. PURPOSIVE OR JUDGMENTAL SAMPLING
4. SNOWBALL SAMPLING

• PROBABILITY

1. SIMPLE RANDOM
2. SYSTEMATIC
3. STRATIFIED
4. CLUSTER
5. MULTISTAGE

• CONVENIENCE /ACCIDENTAL SAMPLING
• SAMPLE IS SELECTED ACCORDING TO THE CONVENIENCE OF THE SAMPLE. THE RESEARCHER SELECTS SAMPLE WHICH IS CONVENIENT FOR HIM. IT ENSURES CONVENIENCE IN RESPECT OF  AVAILABILITY OF SOURCE LIST AND ACCESSIBILITY OF THE UNITS
• SUITABILITY:-

1. NO CLEAR DEFINITION OF THE UNIVERSE
2. SAMPLING UNIT IS NOT CLEAR
3. A COMPLETE SOURCE LIST IS NOT AVAILABLE
4. EVALUATION

• MERITS

1. SAVES TIME AND MONEY
2. SAVES EFFORT
3. EASY TO COLLECT DATA

DEMERITS

1. NO REPRESENTATIVE
2. POSSIBLE RESTRICTING OF GENERALIZATION ABOUT THE STUDY FINDING

• JUDGMENTS SAMPLING

1. INVOLVES THE SELECTION OF A GROUP FROM THE POPULATION ON THE BASIS OF AVAILABLE INFORMATION
2. SELECTION OF THE GROUP  BY INTUITION ON THE BASIS OF CRITERIA DEEMED TO BE SELF EVIDENT
3. UNITS ARE INCLUDED IN THE SAMPLE ON THE BASIS OF THE JUDGMENT
4. IS USED WHEN SIZE OF THE SAMPLE IS SMALL.

• SUITABLE TO SOLVE EVERY DAY BUSINESS PROBLEMS AND MAKING PUBLIC POLICY DECISIONS.
• MAY BE USED TO CONDUCT PILOT STUDY
• MERITS

1. SAVES THE TIME AND COST
2. TO INCLUDE THE POSITIVE STRATIFICATION IN THE SAMPLE
3. CHANCES OF BIASEDNESS
4. SUCCESS DEPENDS ON THE RIGHT JUDGMENT
5. UNSCIENTIFIC

• QUOTA SAMPLING

1. QUOTA ARE SET UP ACCORDING TO GIVEN CRITERIA BUT WITH IN THE QUOTA SELECTION OF SAMPLE ITEMS DEPENDS UPON PERSONAL JUDGMENT.
2. LIKE IN A RADIO LISTENING SURVEY THE INTERVIEWERS MAY BE TOLD TO INTERVIEW OF 500 PEOPLE LIVING IN PARTICULAR LOCALITY AND THAT OUT OF EVERY 100 PERSONS INTERVIEWED 60 ARE TO HOUSEWIVES, 25 FARMERS AND 15 CHILDREN UNDER THE AGE OF 15. WITH IN THESE QUOTA,THE INTERVIEWER IS FREE TO SELECT THE PEOPLE INTERVIEWED

• MERITS:COST PER PERSON WILL BE LESS
• DEMERIT:_

1. RISK OF PERSONAL PREJUDICE
2. CHANCES OF BIASEDNESS

• SNOW BALL SAMPLING

1. IS A WELL KNOWN NON PROBABILITY METHOD OF SURVEY SAMPLE
2. USED FOR LOCATING HIDDEN POPULATION
3. RELIES ON REFRRAL FROM INTIALLY SAMPLES RESPONDENTS

• ADVANTAGE: COST AND EFFICIENCY
• DEMERIT:
• NON RANDOM SELECTION PROCEDURE
• RELIES ON THE SUBJECTIVE JUDGMENT OF INFORMANTS
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• RANDOM SAMPLING METHODS

1. SIMPLE RANDOM SAMPLING
2. STRATIFIED SAMPLING
3. SYSEMATIC SAMPLING
4. MULTI STAGE SAMPLING

• SIMPLE RANDOM SAMPLING

1. REFERS TO THE SAMPLING TECHNIQUE IN WHICH EACH AND EVERY ITEM OF THE POPULATION IS GIVEN AN EQUAL CHANCE OF BEING INCLUDED IN THE SAMPLE
2. SELECTION OF THE ITEMS ON CHANCE ,THIS METHOD IS ALSO KNOWN AS THE METHOD OF CHANCE SELETION
3. FREE FROM PERSONAL BIAS BUT CONSCIOUS EFFORTS IS MADE TO ENSURE IT FREE FROM BIAS
4. ALSO KNOWN AS REPRESENTIVE SAMPLING AND IF THE SIZE OF THE SAMPLE IS LARGE IT WILL BE REPRESENTATIVE OF THE GROUP
5. ALSO KNOWN AS PROBABILITY SAMPLE BECAUSE EVERY ITEM OF THE POPULATION HAS AN EQUAL OPPORTUNITY OF BEING SELECTED IN THE SAMPLE

• METHODS OF OBTAINING SIMPLE RANDOM SAMPLING

1. LOTTERY METHODS
2. TABLE OF RANDOM NUMBERS

• LOTTERY METHODS: - ALL ITEMS OF THE POPULATION ARE NUMBERED OR NAMED ON SEPARATE SLIPS OF PAPER OF IDENTICAL SIZE, COLOUR AND SHAPE.  THESE SLIPS ARE THEN FOLDED AND MIXED UP IN A CONTAINER OR DRUM. A BLINDFOLDED SELECTION IS MADE.
• SUITABILITY OF LOTEERY METHOD:- POPULAR WHERE A DECISION ABOUT PRIZES IS TO BE TAKEN IN LOTTERY DRAWN
• CHECKING OF SLIPS

·         POSSIBILTY OF PERSONAL BIAS

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• THE TABLE OF RANDOM NUMBERS

1. TIPPETT’S TABLE OF RANDOM NUMBERS
2. FISHER AND YATES NUMBERS
3. KENDALL AND BABINGTON SMITH NUMBERS

• TIPPET; S NUMEBRS ARE QUITE POPULAR. THEY CONSISTS OF 41600 DIGITS TAKEN FROM CENSUS REPORT AND COMBINED BY FOUR TO GIVE 10,400 FOUR FIGURE NUMBER.
• EXAMPLE USING RANDOM NUMBERS
• POPULATION OF 600 BBA FIRST YEAR STUDENT ARE ASSIGNED NUMBERS 1 THROUGH 600. SAMPLE OF 10% I.E 60 STUDENTS ARE TAKEN

• SUPPOSE WE HAVE TO SELECT 20 ITEMS OUT OF 6000, THE PROCEDURE IS TO NUMBER ALL 6000 ITEMS FROM 1 TO 6000. A PAGE FROM TIPPET’S TABLE MAY BE THEN CONSULTED AND FIRST TWENTY NUMBERS UP TO 6000 ARE NOTED DOWN, ITEMS BEARING THESE NUMBERS WILL BE SELECTED IN THE SAMPLE
• POPUATION SIZE LESS THAN 1000: SAMPLE OF 10 ITEMS OUT OF 400, ITEMS WILL BE NUMBERED FROM 1 TO 400 AS 0001 TO 0400
• FISHER AND YATE TABLE CONSISTES OF 15,000. THESE HAVE BEEN ARRANGED IN TWO DIGITS IN 300 BLOCKS AND EACH BLOCK CONSISTS OF 5 ROWS AND 5 COLUMS.
• KENDALL AND SMITH CONSTRUCTED 10000 IN ALL BY USING A RANDOMISING MACHINE.
• MERIT

1. NO POSSIBILITY OF PERSONAL BIAS
2. MORE REPRESENTATIVE AS COMPARED TO JUDGMENTAL SAMPLING

3.     CAN EASILY ACCESS THE ACCURACY OF THE ESTIMATE

DEMERITS

1. NECESSARY TO MAKE A LIST AND IT IS VERY DIFFCIULT TO MAKE
2. PREPRATION OF THE SLIPS IS EXPENSIVE AND TIME CONSUMING
3. SAMPLE SIZE IS REUQIRED VERY LARGE
4. SAMPLE SELECTED ON THIS METHOD MAY BE SCATTERED GEOGRAPHICALLY

• STRATIFIED SAMPLING

1. THE PROCESS OF STRATIFICATION REQUIRES THAT POPULATION MAY BE DIVIDED INTO HOMOGENEOUS METHODS GROUPS OR CLASSES CALLED STRATA
2. SAMPLE MAY BE TAKEN FROM EACH GROUP BY SIMPLE RANDOM METHODS
3. IT MAY BE PROPORTIONAL OR DISPROPORTINATE
4. IN CASE OF PROPORTINAL STRATIFIED SAMPLING PLAN,THE NUMBER OF ITEMS DRAWN FROM EACH STRATUM IS PROPORTIONAL TO THE SIZE OF THE STRATA

• STRATIFIED SAMPLING
• PROPORTIONAL STRATA:- FOUR STRATA ARE CREATED, AND THEIR RESPECTIVE SIZE IS 10,25,15 AND 50 PERCENT FROM THE POPULATION

1. FIRST STRATA= 1000X10/100=100
2. SECOND STRATA= 1000X15/100=150
3. THIRD STRATA=1000X25/100=250
4. FOURTH STRATA= 1000X50/100=500

• TOTAL = 1000
• IN ORDER TO MAINTAIN MAXIMUM EFFICIENCY, GREATER REPRESENTATION TO A STRATUM WITH LARGE VARIATION.
• DISPROPOTIONATE STRATIFIED INCLUDES PROCEDURE OF TAKING AN EQUAL NUMBER OF ITEMS FROM EACH STRATUM
• MERITS

1. MOST EFFICIENT SYSTEM OF SAMPLING AS THE POPULATION IS DIVIDED INTO DIFFERENT STRATA
2. GREATER ACCURACY
3. MORE CONCENTRATED GEOGRAPHICALLY

DEMERITS

1. DIFFICULTY IN CREATING STRATA
2. SKILLED SUPERVISOR IS REQUIRED FOR RANDOM SELECTION FROM EACH STARTA

• SYSTEMATIC SAMPLING

1. SUITABLE WHERE A COMPLETE LIST OF THE POPULATION FROM WHICH SAMPLING IS TO BE DRAWN IS AVIALABLE
2. THE METHOD IS TO SELECT KTH ITEM FROM THE LIST WHERE KTH REFERS TO SAMPLING INTERVAL
3. IF WE HAVE A COMPLETE LIST OF 1000 STUDENTS AND WE WANT TO DRAW SAMPLE OF 200 STUDENTS,1000/200=5 TH
4. WE MUST TAKE EVERY FIFTH ITEM. THE FIRST ITEM BETWEEN 1 AND 5 IS TO BE SELECTED AT RANDOM. SUPPOSE 4 TH ITEM IS SELECTED,SECOND WILL BE 9,14 AND SO ON

• MERITS

1. MORE CNVENIENT
2. TIME AND WORK IS VERY LESS AS COMPARED TO OTHER METHODS

• IF POPULATIION ARE QUITE LARGE IT WILL PRODUCE THE SIMILAR RESULT TO PROPORTIONAL
• DEMERITS

1. NOT SUITABLE WHERE THE POPULAYION HAVING HIDDEN PERIODCITIES
2. BIASEDNESS IN SUCH CASES

• MULTISATGE SAMPLING
• SAMPLING PROCEDURE WHICH IS CARRIED OUT IN SEVERAL STAGES
• THE MATERIAL IS REGARDED AS MADE UP OF A NUMBER OF FIRST STAGE SAMPLING UNITS,EACH OF WHICH IS MADE OF NUMBER OF SECOND SATGE UNITS ETC
• FIRST STAGE UNITS ARE SAMPLED BY SOME SUITABLE METHOD SUCH AS RANDOM SAMPLING
• THEN A SAMPLE OF THE SECOND STAGE IS SELECTED FROM EACH OF THE SELECTED STAGE BY SOME SUITABLE METHOD
• FURTHER STAGES MAY BE ADDED AS REQUIRED
• EXAMPLE
• LIKE WE WANT TO TAKE A SAMPLE OF 5000 FROM THE STATE OF U.P
• FIRST STAGE THE STATE MAY BE DIVIDED INTO NUMBER OF DISTRICTS
• FEW DISTRICTS WILL BE SELECTED AT RANDOM
• AT THE SECOND STAGE SELECTED DISTRICTS WILL BE DIVIDED INTO NUMBER OF VILLAGES AND SAMPLE OF VILLAGES WILL BE TAKEN AT RANDOM
• OUT OF SELECTED VILLAGES, A NUMBER OF HOUSEHOLD MAY BE SELECTED
• IN THIS WAY SAMPLE SIZE GOES ON SMALLER AND SMALLER
• MERITS

1. FLEXIBILITY
2. PERMITS THE FIELD WORK TO BE CONCENTRATED

·         DEMERITS

• LESS ACCURATE