Question

There are many factors that impact a sample size. Discuss the factors in regard to a large sample and a small sample, elaborate on the factors for each, 2-3 pages.

Answer 1

Sampling of a population is a process that consists of taking a subgroup of subjects that are representative of the entire population. Generally, sampling is done because it is impossible to test each individual in a population. It is also use in order to save time and money.

It is not possible to speak of an exact size of the sample, since it can vary depending on the different research frameworks. However, if everything else is equal, a large sample provides more accurate estimates than a small sample. Nevertheless, having a large sample without really having to can be seen as a waste of limited resources. The important question to be answer is: what is the representative sample of the population that I want to investigate?

The choice of sample size depends on both, statistical and no statistical considerations. Non-statistical considerations may include the availability of resources such as enough workers to conduct interviews or surveys, lack of budget, ethical issues, inability to reach the entire population and the type of sampling that is chose. On the other hand, statistical considerations include margin error, confidence level and degree of variability.

1. The margin error. Also referred to as the confidence interval measures the precision with which an estimate from a single sample approximates the population value. The margin error selected depends on the precision needed to make population estimates from a sample. If the margin of error is small, the sample size will increase. On the contrary, if the margin error is big it means that accuracy is no so important so the sample size can be small.
2. Confidence level. Is the probability that population estimate lies within a given margin of error. Common confidence levels in scientific research are 90%, 95% and 99%. The larger the confidence lever, the greater the accuracy. Confidence levels closely relate to sample size. A researcher that chooses a confidence level of 90% will need a smaller sample.
3. Degree of variability. Depending on the target population and its specific attributes, the degree of variability changes considerably. The more heterogeneous a population is, the larger the sample size must be to obtain an optimal level of precision.