Question

Compare the different types of random sampling methods. Describe an example in which stratified sampling and cluster sampling should be used

Answer 1

ANSWER::

1. Simple Random Sampling-----Simple random sampling is the most basic and well-known type of random sampling technique. In simple random sampling, every case in the population being sampled has an equal chance of being chosen. It is an equal probability sampling method (EPSEM). EPSEMs are important because they produce representative samples. The most basic way to do a simple random sample is to pull names out of a hat, but today researchers usually use computer programs to select the samples.

2. Systematic Sampling------Systematic sampling, a variation of simple random sampling, is also an EPSEM. In systematic sampling, you make a list of potential samples and then choose every nth element on the list as a sample.

3. Stratified Random Sampling-----Stratified random sampling involves dividing the potential samples into two or more mutually exclusive groups based on categories of interest in the research. The purpose is to organize the potential samples into homogenous subsets before sampling. For example, you could divide the potential samples based on gender, race or occupation. You then draw a random sample from each subset. Stratified random sampling is common because it ensures that each subgroup of the larger group is adequately represented in the sample.The two types of stratified sampling random sampling are proportionate and disproportionate. In proportionate sampling, the sample sizes are proportional to the population sizes

4. Cluster Random Sampling--------In cluster random sampling, you randomly select clusters instead of individual samples in the first stage of sampling. For example, a cluster might be a school, a team or a village. This technique is used when no list of individual samples is available. Usually, the way this type of sampling is done is by starting at the higher level clusters and then sampling at subsequent levels until individual samples are reached.

stratified sampling ex----------Let’s say, 100 (N_h) students of a school having 1000 (N) students were asked questions about their favorite subject. It’s a fact that the students of the 8th grade will have different subject preferences than the students of the 9th grade. For the survey to deliver precise results, the ideal manner is to divide each grade into various strata. Here’s a table of the number of students in each grade:

Grade	Number of students (n)
5	150
6	250
7	300
8	200

Stratified Sample (n5) = 100 / 1000 * 150 = 15

Stratified Sample (n6) = 100 / 1000 * 250 = 25

Stratified Sample (n7) = 100 / 1000 * 300 = 30

Stratified Sample (n8) = 100 / 1000 * 200 = 20

cluster sampling------------a researcher wants to survey academic performance of high school students in Spain. He can divide the entire population (population of Spain) into different clusters (cities). Then the researcher selects a number of clusters depending on his research through simple or systematic random sampling.

NOTE:: I HOPE YOUR HAPPY WITH MY ANSWER....***PLEASE SUPPORT ME WITH YOUR RATING...

***PLEASE GIVE ME "LIKE"...ITS VERY IMPORTANT FOR ME NOW....PLEASE SUPPORT ME ....THANK YOU