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CHAPTER 3 SAMPLING

CHAPTER 3 SAMPLING. DR.SHINEY CHIB PROFESSOR,DMIMS,NAGPUR. SAMPLING. THE PROCEDURE OF USING A SMALL NUMBER OF ITEMS OR PARTS OF THE WHOLE POPULATION TO MAKE CONCLUSIONS REGARDING THE WHOLE POPULATION. SAMPLE

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CHAPTER 3 SAMPLING

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  1. CHAPTER 3SAMPLING DR.SHINEY CHIB PROFESSOR,DMIMS,NAGPUR

  2. SAMPLING • THE PROCEDURE OF USING A SMALL NUMBER OF ITEMS OR PARTS OF THE WHOLE POPULATION TO MAKE CONCLUSIONS REGARDING THE WHOLE POPULATION. • SAMPLE A SAMPLE IS A SUBSET, OR SOME PART OF A LARGER POPULATION. THE PURPOSE OF SAMPLING IS TO ENABLE RESEARCHERS TO ESTIMATE SOME UNKNOWN CHARACTERISTIC OF THE POPULATION.

  3. STAGES IN SELECTION OF SAMPLE DEFINE THE TARGET POPULATION SELECT A SAMPLING FRAME DETERMINE IF A PROBABLITY OR NONPROBABLITY SAMPLING METHOD WILL BE CHOSEN PLAN PROCEDURE FOR SELECTING SAMPLING UNITS DETERMINE SAMPLE SIZE SELECT ACTUAL SAMPLING UNITS CONDUCT FIELD WORK

  4. SAMPLE ERROR • THE DIFFERENCE BETWEEN THE SAMPLE RESULT AND THE RESULT OF A CENSUS CONDUCTED USING IDENTICAL PROCEDURES, A STATISTICAL FLUCTUATIONS THAT OCCURS BECAUSE OF CHANCE VARAIATION IN THE ELEMENTS SELECTED FOR A SAMPLE. AN ESTIMATION FROM A SAMPLE IS NOT EXACTLY THE SAME AS A CENSUS COUNT. RANDOM SAMPLING ERROR IS THE DIFFERENCE BETWEEN THE SAMPLE RESULT AND THE RESULT OF A CENSUS CONDUCTED BY IDENTICAL PROCEDURES.

  5. THUMB RULE OF CONFIDENCE LEVEL • THERE IS A GENERAL RULE THAT APPLIES WHWNEVER WE HAVE A NORMAL OR BELL SHAPED DISTRIBUTION. START WITH THE AVERAGE, THE CENTRE OF THE DISTRIBUTION. IF YOU GO UP AND DOWN I.E. LEFT AND RIGHT, ONE STANDARD UNIT, YOU WILL INCLUDE APPROXIMATELY 68% OF THE CASES IN THE DISTRIBUTION (I.E. 68% OF THE AREA UNDER THE CURVE.) IF YOU GO UP & DOWN TWO STANDARD UNITS YOU WILL INCLUDE APPROXIMATELY 95% OF THE CASES. AND IF YOU GO PLUS-AND-MINUS THREE STANDARD UNITS, YOU WILL INCLUDE 99% OF THE CASES. THE SAME RULE APPLIES FOR BOTH TYPES OF DISTRIBUTIONS I.E. THE RAW DATA AND SAMPLING DISTRIBUTIONS.

  6. TYPES OS SAMPLING • PROBABLITY / RANDOM SAMPLING IT GIVES ALL MEMBERS OF THE POPULATION A KNOWN CHANCE OF BEING SELECTED . SELECTION OF INDIVIDUAL DOES NOT EFFECT THE CHANCE OF ANYONE ELSE IN THE POPULATION BEING SELECTED. • NON-PROBABLITY SAMPLING IT IS A TYPE OF QUOTA SAMPLING. GROUPING IS SUBJECTIVE IN NATURE.

  7. PROBABLITY SAMPLING METHODS SIMPLE RANDOM SAMPLING INDIVIDUALS ARE RANDOMLY SELECTED FROM A LIST OF THE POPULATION AND EVERY SINGLE INDIVIDUAL HAS AN EQUAL CHANCE OF SELECTION. SYSTEMATIC SAMPLING IN SYSTEMATIC SAMPLING , EVERY Kth ELEMENT FROM THE LIST IS SELECTED. STRATIFIED SAMPLING A STRATIFIED SAMPLING IS CONSTURCTED BY CLASSIFYING THE POPULATION, SUCH AS AGE, GENDER OR SOCI-ECONOMIC STATUS. THE SELECTION OF ELEMENTS IS THEN MADE SEPERATELY FROM WITHIN EACH STRATUM, USUALLY BY RANDOM OR SYSTEMATIC SAMPLING METHODS.

  8. STRATIFIED SAMPLING IS CLASSIFIED INTO TWO TYPES: PROPORTIONATE THE STRATA SAMPLE SIZES ARE MADE PROPORTIONAL TO POPULATION SIZES. IF FIRST STARTA IS MADE UP OF MALES, THEN THER ARE AROUND 50 % OF MALES IN KARNATAKA POPULATION, THE MALE STARTA WILL NEED TO REPRESENT AROUND 50 % OF THE TOTAL SAMPLE. DISPROPORTIONATE THE STARTA IS NOT SAMPLED ACCORDING TO THE POPULATION SIZES, BUT HIGHER PROPORTION ARE SELECTED FROM SOME GROUPS AND NOT OTHERS.

  9. CLUSTER OR MULTISTAGE SAMPLING SAMPLING IS CONDUCTED BY RANDOMLY SELECTED SUBGROUPS OF THE POPULATION, POSSIBLE IN SEVERAL STAGES, IT SHOULD PRODUCE RESULTS EQUIVALENT TO A SIMPLE RANDOM SAMPLE.IT IS SUITABLE WERE • NO LIST OF THE POPULATION EXIST • WELL-DEFINED CLUSTERS, WHICH WILL OFTEN BE GEOGRAPHIC AREAS EXIST. • A REASONABLE ESTIMATE OF THE NUMBER OF ELEMENTS IN EACH LEVEL OF CLUSTERING CAN BE MADE. • OFTEN THE TOTAL SAMPLE SIZE MUST BE FAIRLY LARGE TO ENABLE CLUSTER SAMPLING TO BE USED EFFECTIVELY

  10. NON-PROBABLITY SAMPLING CONVENIENCE SAMPLING ALSO CALLED AS HAPHAZARD OR ACCIDENTAL SAMPLING.SAMPLING BY OBTAINING UNITS OR PEOPLE WHO ARE MOSTLY CONVENIENTLY AVAIALBLE. JUDGEMENT / PURPOSIVE SAMPLING EXPERIENCED INDIVIDUAL SELECT THE SAMPLE BASED ON HIS OR HER JUDGEMENT ABOUT SOME APPROPRIATE CHARACTERISTIC REQUIRED OF THE SAMPLE MEMBERS. QUOTA SAMPLING VARIOUS SUBGROUPS IN A POPULATION ARE REPRESENTED ON PERTINENT SAMPLE CHARAXTERISTIC TO THE EXACT EXTENT THAT THE INVESTIGATORS DESIRE. SNOWBALL SAMPLING INTITIAL RESPONDENTS ARE SELECTED BY PROBABLITY METHODS AND ADDITIONAL RESPONDENTS ARE THEN OBTAINED FROM INFORMATION OROVIDED BY INTIAL RESPONDENTS.

  11. CALCULATION OF SAMPLE SIZE • HOW ACCURATE YOU WISH TO BE ? • HOW MUCH CONFIDENT YOU ARE IN THE RESLTS TO BE ? • WHAT BUDGET YOU HAVE AVAILABLE ?

  12. CALCULATION OF SAMPLE SIZE • BASED ON MEAN S= (z/e)2 S=sample size Z =a number relating to the degree of confidence you wish to have in result , e=error you are prepared to accept.

  13. Solved example Imagine we are estimating mean income, and wish to know what sample sixe to aim for so that we can be 95% confident in the result. Assuming that we are prepared to accept an error of 10 % of the population standard deviation. s=(1.96/.1)2 s= 384.16 In other words , 385 people should be sampled to meet our criterion.

  14. THANK YOU

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