Origanlity in post needed . Chapter 7 talks about sampling and sampling distribu

Question

Origanlity in post needed.

Chapter 7 talks about sampling and sampling distributions. The calculations in Chapter 7 are an extension of the probability calculations that use the standard normal distribution in Chapter 6. The main difference between Chapter 6 and 7 is that in Chapter 7 we are substituting the standard deviation of x-bar (aka the standard error of the mean) as a substitute for the sample standard deviation.

Origanlity in post needed.

In this week's discussion, describe what you see as the major concern with using a sample to draw conclusions about the population. What should a researcher, business owner or any other person conducting a scientific study consider when sampling a population in order to make sure that his results will give the best conclusions?

Explanation / Answer

While sampling from a population you need to remember a few things namely :

1. The sample you are drawing should be a good representative of the population.

For example : Suppose you are trying to estimate the average height of fourth grade male students of a school. For this purpose you need to consider a good sample. If your sample involves students who are apparently quite short in height and if you use that sample to estimate the average height of all the fourth grade male students then the estimate will be very bad. So, your sample should include students of different heights so that it won't be a biased sample.

2. A sample should be very economical in the sense that while sampling it should cost you very less and it should not be destructive

For example : Suppose you are trying to estimate the average lifetime of a light bulb and also suppose you chose a good representative sample. You will get the lifetime of a bulb only when it goes out completely. So, in this case you are wasting resource (the used light bulbs would not do you any good) and cost. So, here the sample is destructive and you should consider in minimizing your cost and effort in such cases.

3. The sampling method is also very important. There are many types of sampling viz. simple random sampling with replacement, simple random sampling without replacement, linear systematic sampling, stratified sampling cluster sampling etc. You should choose proper sampling method to fulfill your purposes. You should also consider the standard errors of the same estimator under different sampling methods. You should choose the estimator for which the standard error is less.

4. The sampling should be probabilistic sampling where you can select the sample randomly unless you need a judgment sampling where the units are selected using one's judgment (which will happen very rarely).

5. The sample size should be proportional to the population size which means that if population size is large then the sample size should also be large and vice versa. This characteristic is required for the sample for it to become a good information provider sample.

6. You should always try to minimize the sampling and non-sampling errors which often occur during the process of sampling.

By considering the above characteristics, one can obtain a sample which can often leads to results which are really helpful and purposeful for the objective of the sampling.

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