1 See Systematic Random Sampling at Wikipedia

1 see systematic random sampling at wikipedia

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1 See Systematic Random Sampling at Wikipedia 2 Refer to ‘What Are the Advantages and Disadvantages of Systematic Random Sampling’, - sampling.asp
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SYSTEMATIC RANDOM SAMPLING 4 COMPARISON BETWEEN SIMPLE, SYSTEMATIC, AND STRATIFIED SAMPLING METHOD Type of Sampling Methods Description Advantages Disadvantages Simple Random Sampling Sample drawn using random number table/generator. Produces defensible estimates of the population and sampling error. Simple sample design and interpretation. Costlier - requires a complete list of all potential respondents to be available beforehand. High chance of having a biased representation of the population. Time consuming for large population. Systematic Random Sampling Selects an element of the population at a random starting point and a fixed, periodic interval. The sampling interval, is calculated by dividing the population size by the desired sample size. Simple. - Researchers have a degree of control. Ensures cases are spread across the population. Can be costly and time- consuming due to obtaining the population list. Likely to choose common sample if there is periodicity in the population list. Stratified Random Sampling Divided into subpopulations or strata based on shared attributes and uses simple random on each stratum. Results may be weighted or combined. Ensures units from each main group are included and may therefore be more reliably representative. Should reduce the error due to sampling. Selecting the sample is more complex and requires good population information. The estimates involve complex calculations.
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SYSTEMATIC RANDOM SAMPLING 5 HOW DOES ONE CONDUCT A SYSTEMATIC RANDOM SAMPLING? 3 To construct a systematic random sampling, one must: - 1. Firstly, define the population, meaning they must decide on what they want to study and the target group. Thus, they also need to establish their sampling frame, consisting of their target group of people in an ordered fashion. 2. Secondly, they should determine the sample size. This can be done by using the sample size calculation. Margin of error, population size, and confidence level is needed to calculate the sample size. 3. A list of the elements of the population is needed. This makes it easier when we want to assign numbers to population list. 4. Next, is to assign numbers to the population list. This step is to make determining the sample easier. 5. In order to choose the sample, a k th figure is needed. To calculate k , the population, N, is divided by the sample size, n. k = N/n e.g: k = 1000/100 =10 (every 10 th person is chosen) 6. Next, we have to select the first unit by generating the random number, range from 1-N, using a software or application online.
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