Simple Random Sampling 1.Use a data list to number all the members / elements of the target groupfrom 1 to n . 2.Generatexrandom numbers from 1 to n. 3.The members / elements of the target group corresponding to the random numbers will be selected into the sample. +Suitable for small sample size. +Easy to conductVS Stratified & Systematic Need to ensure that the sampling frame is fixed. If the selection of samples is not done face-to-face, it may not be easy to get access to the selected members / elements of the target group. Not all groups within the target group will be fairly representedVSStratified. Systematic Random Sampling 1.Use a data list to number the members / elements of the target group from1 to n . 2.Determine the sampling interval, k = size Sampleframe Sampling 3.A number between 1 andk , inclusive is selected at random. The corresponding member / element of the target group and everyk th member / element of the target group thereafter are included in the sample until a sample size ofxis obtained. If the sampling frame is not available, the sampling interval, k , can be randomly chosen. 1.To survey 2% of the target group, a number between 1 and50 , inclusive is selected at random. 2.The corresponding member / element of the target group and every50 th member / element of the target group thereafter are included in the sample until the required sample size is obtained. +Suitable for large sample size. +Sample selected will be at random VSQuota +Sample is more evenly spread VSSimple Random If the selection of samples is not done face-to-face, it may not be easytoget access to the selected members / elements of the target group. Biasness can be formed if the listing of the data list has a periodic / cyclic pattern. n : total number of target group x : sample size If the sampling frame aka total number of members / elements under investigation is not known, Use: Systematic or Quota Alternate JC-Math.com This disadvantage will not be valid for the alternate description. Need to explain periodic / cyclic pattern in context of the given question. If the sample has to be 2 % of the population, with unspecified sample size. Stratified Random Sampling 1.Draw random samples from the sub-groups with sample size in the same proportion as the size of each sub-group with respect to the population. 2. 3.The number of sample randomly drawn from each subgroup is shown in the table above. Alternatively 1.Percentage of sample size against population = % 5100050= 2. 3.The number of sample randomly drawn from each subgroup is shown in the table above. +Gives a good representation sample of the population. +Gives more accurate estimates VSSimple Random & Quota Time consuming VSSimple Random & Quota Sample is not evenly spread VSSystematic If the selection of samples is not done face-to-face, it may not be easytoget access to the selected members / elements of the target group. Quota Sampling 1.The breakdown of the number of members / elements of the target group to be selected for the sample is shown in the table below. +Fast in gathering data. +Easy to conduct VS Systematic & Stratified +No need sampling frameVS Simple Random & Stratified

The interviewer / selector has the discretion ofwhich members / elements of the target group to select for the sample which can cause the results to be biased. Not a good representation of the population as a whole VSSystematic &Stratified ABCD 20 501000400= 14 1 . 14 501000282 = 10 501000200= 6 9 . 5 501000118 = ABCD 400282200118 ABCD 20 400 % 5 = 14 1 . 14 282 % 5 = 10 200 % 5 = 6 9 . 5 118 % 5 = BatchAB 0011015 002520 Crossing at least between 2 categories - age - gender - nationality - area of residence - sizes - batches JC-Math.com Assuming quota is 50. Need to ensure that the total number is equal to 50. Ensure that each subgroup is mutually exclusive. To get a sample of 50 from the given data.