Assignment: Sampling Methods Study.

Assignment: Sampling Methods Study.

Assignment: Sampling Methods Study.

Module VIII Discussion Construct a research question and select a sampling method. Explain why you selected the specific sampling method and discuss strengths and weaknesses. Post your initial response by Wednesday at midnight. Respond to one student by Sunday at midnight. Both responses should be a minimum of 150 words, scholarly written, APA formatted, and referenced. A minimum of 2 references are required (other than your text). Refer to the Grading Rubric for Online Discussion in the Course Resource section.

At times, your survey may require you to cover the entire target population, as is the case in mapping or population studies. That’s usually referred to as a census survey. However, target populations are generally large and expensive to survey. In our example, it may not be feasible to visit all 3,200 households of the five towns. Instead, you’d want to choose a smaller sample that would be representative of the population and reflect its characteristics.

A survey that is done on a smaller number of the target population is referred to as a sample survey. You can infer your findings for the entire population based on this representative sample. In the following sections, we’ll describe the different terminologies that are associated with sample surveys, such as sample size and sampling technique. These concepts will enable you to determine the number of surveys needed to accurately reflect the true characteristics of a population and to choose the best method of selecting a sample from that population.

The first step in your sampling exercise will be to decide on an appropriate sample size. There are no strict rules for selecting a sample size. You can make a decision based on the objectives of the project, time available, budget, and the necessary degree of precision.

In order to select the appropriate sample size, you will need to determine the degree of accuracy that you want to achieve. For this, you’ll need to establish the confidence interval and confidence level of your sample.

The confidence interval, also called the margin of error, is a plus or minus figure. It is the range within which the likelihood of a response occurs. The most commonly used confidence interval is +/- 5. If you wish to increase the precision level of your data, you would further reduce the error margin or confidence interval to a +/- 2. For example, if your survey question is “does the household pay tax?” and 65% of your sampled households say “yes,” then using a confidence interval of +/- 5, you can state with confidence that if you had asked the question to all 3,200 households, between 60% (i.e. 65-5) and 70% (i.e. 65+5) would have also responded “yes.”

The confidence level tells you how sure you want to be and is expressed as a percentage. It represents how often the responses from your selected sample reflect the responses of the total population. Thus, a 95% confidence level means you can be 95% certain. The lower the confidence level, the less certain you will be.

Most surveys use the 95% confidence level and a +/- 5 confidence interval. When you put the confidence level and the confidence interval together, you can say that you are 95% sure that, if you had surveyed all (3,200) households, between 60% and 70% of the households of the target population would have answered “yes,” to the question “does the household pay tax?”.