Sampling Methods PDF

14 SAMPLING ---------. CHAPTER ,fc,inin~.ind Tyrl'~ of Sa111rling PREVIEW ' ~ 0Pu1,1uon nw~ 1 nire Univ ~II-specified group of individuals. All prrm I sof populauons. sily coun1ed· an in i ersrty...

14 SAMPLING ---------. CHAPTER ,fc,inin~.ind Tyrl'~ of Sa111rling PREVIEW ' ~ 0Pu1,1uon nw~ 1 nire Univ ~II-specified group of individuals. All prrm I sof populauons. sily coun1ed· an in i ersrty examp e n be ea 01 ; , students, all housewives, etc., are h ,,.,embers ca 11 11 "nite-. h e a t e '" a finite population is one w er 36S  366 Tests. Meas1mm1e111s a11d Researcb Me1bods tn 8(1/Ja11ioural Sciences population is one whose size is unlimited and ther~f?re, its me~bers cannot be c~unted. 1 population of university teachers is an exam~le of a finite population and th e population offis~~ in a river is an example of an infinite population because the former can be counted Whereas,~ latter cannot be counted. Likewise a population may be real o r imaBinative-a real populati?n is one which act ' exists and an imaginative population is one w ic. 1 h · h ex·sts only in the I· lJally ~agination. 1 psychological and educational researc_h, ~n many occasions, the population is imaginative. n measure based upon the entire population ,s called a parameter. A A sample is any number of persons selected to_ represent the po~u lation according to 50flle rule or plan. Thus, a sample is a smaller representation of the population. A measure based Upon a sample is known as a statistic.. Before we define the different types of samples (or the methods of sampling), it is essential define the term 'probability', which is the base of sampling th~ory. The general meaning t~ probability is less than certain and for which there e~ists some evidence. In sampling theory,,~; term 'probability' is used as equivalent to the relative frequency. Thus when we say that the probability of a tai l on a single toss of a coin is 1/2, it is meant that when we make ~~veral tosses, the relative frequency of a tail will be about y2 or 0.5. ~f one says th.at the probabtl1ty of having of a male child is o.8, it is meant that on previous occasions the relative frequency of the birth of a male child has been 0.8. Probability may be expressed in terms of a fraction or in decimal numbers. Following Blalock (1960), most sampling methods can be categorized into two- (A) Probabi lity Sampling Methods (B) Nonprobability Sampling Methods A discussion of these two is given below. (A) Probability Sampling Methods Probability sampling methods are those that clearly specify the probability or likelihood of inclusion of each element or individual in the sample. Technically, the probability sampling methods must satisfy the conditions given below. (i) The size of the parent population or universe from w h ich the sample is to be taken, musi be known to the investigator. (ii) Each element or individual in the population must have an equal chance of being included in a subsequent sample. (ii i) The desired sample size must be clearly specified. If, for example, a researcher knows that the population which he is going to study contains 500 elements, or individuals, and if he knows that all the elem ents (or individuals) are accessible and may be included in a subsequent sample, it can be said that each element (or individual) in the popufat_i~n has an _equal chance, that is, 1/ 500 of a chance of being selected. This constitutes the probabil 1ty sampling method. In practice, however, sometimes researchers are not able t~ know for certainty that conditions (i) and (ii) wi l l be satisfied. Som etimes the population studied 15 so large as to be considered infinite and unknowable for all important and practical purposes. The positive point of the probability sampling m ethod is that the obtained samples are.d d · cons, ~re. representative, and hence, the conclusions reached from such samples are wo rth general,zat,on and are comparable to sim ilar populations to which they belong.. Th: negative point of the probabi lity sampling method is that a certain amount of sampling error exi sts because the researcher has only a limited element of the entire population. Sampling error refers to the degree to h I· h th h... risticsOI w c e sampIe c aracterist1cs approximate the charac1e th e parent population. The smallerthe sample, the greater the sampl ing error.  rnaJ·or pro bability sampling methods are t he f0 11. The Simple random samplin ~ ow,ng: 1 · tified ra ndo m sampling 2 Stra..f. d ( ) Pro portio nate strati 1e random sa. a Dispro po rtio. nate strati·t·1ed randommp11ng. (b). sampling _ Area or cluste r sa mpling 3 probability Sampling Methods (B) Nonbability sampling is one method in which th. Nonpro ent o r gro up o f e Ie me nts o f the population bere. is no w ay of asse,;sin th the elenb,ability sampling methods are those that proe_ 1dng included in the samgpl,, c:,· prohbab,l,ty r,f npro. v 1 e no ba · f.!. not er noaracteristics of a sam_ pl~ approximate the parameters of the s1s or ~stimating how dr,:i:Jr;1~ chd been obtained. This is because no nprobability sam I dpopulation from which th. I h ha h · f P es on't u h e '>~rnplP iing. Important tee ntque s o no nprobability sampling h se t e techniques of rand< sarn P. met ods are· Jm 1_ Quota samp 1mg · 2 _ Accidental sam p ling 3. Judgementa l o r purposive sampling 4. Snow ba ll sa mpling s. Saturati o n sampling 6. Dense sampling (C) Mixed Sampling Systematic sampling Figure 14.1 prese nts the detai ls of classification of sampling. Types of sampling Pro bability s ampling Nonprobability sampling Mixed sampling I Simple random Stratified ran dom Cluster ' \ Systematic sampling sampling sampling sampling Proportionate stratified Quota sampling sampling Snowball sampling Accidental Disproportionate stratified Dense sampling sampling sampling Judgemental Saturation or sampling purposive sampling f sampling Fig. 14.1: De tails of cypes o NEED FOR. l "I.I l~ l\l\\ Sarnpti. SAMPL I NG. rtant reasons are, nenll01 t v111pltt"'l ng ts n d Of the 1rnpo -~rnphng'' l 1 1 (') ee ed for a variety of re asons. Some d based on 5' tht>r d lt'f'· t Sam pl. A esearch stu y d based upon l> i ,11'kl "·· 1... - tng saves time as we ll as mo ney. r. than a stu Y l>Y tr-1111t'- v tt, 11n (ii) A I a esser time and inc urs less exp e nd1ture. duc1en1 ,111L1tr L"'~ re I' g 1s ge. easur ex.p s:arc h study based upon sarnp in 'd s accuracy ,n rn enenced investigato rs. As such, it provi e  36s 7ests, Meac,urement.~and f{e..plain this pnnc,ple m a better way, /er us take an ex Pe.. I amp e. SupPo h individuals and you know I heir age. se t ere are five Individuals Age (in years) A 20 B 22 ( 19 [) 10 l 24 Tot,1/ = 105 /()5 -.! I~ l 'd(:, 5 Nm, lt-1 u, ,11/J/>""' 11111/ , , 1/1.11 ~ uu \\ ,1111 w 4,l'/ect J :.ample of two persons for making an tpoµu/Jt1on mean or parameter mean). If you adopt e!>1111l.JI