MINIMUM OF 150 WORDS FOR EACH QUESTION AND PLEASE PROVIDE REFERENCE FOR EACH QUESTION AS WELL

Research cosmic question | Nursing homework help

A. The simple random sampling method is used widely to choose a sample of a large number. This method selects a random subset from a large population. Each member has the same chance of selection. It is crucial to use simple random sample in large populations because this ensures that the samples are representative and reduces the chance of bias. This also increases the accuracy for statistical analysis. By randomly selecting individuals from the population, the sample is more likely to reflect the population’s characteristics and diversity, allowing researchers to generalize their findings to the larger population. Random sampling can be an effective method of selecting samples, as it is easy to use and requires little knowledge about the population. It is crucial to make sure that the size of the sample is large enough to improve the accuracy and reliability of the results.

B. Sample size can lead to bias when it isn’t representative of the entire population. The following techniques can be used by researchers to avoid bias when selecting a sample size:

1. Stratified sampling: This technique divides the population according to specific criteria such as gender or age, then selects a sample at random from each stratum. This ensures that the sample represents the population’s diversity and reduces bias.
2. Cluster sampling: In this technique, the population is divided into groups, like geographical areas or schools. Then, a sample at random from each group is selected. To obtain their samples, researchers sample people from within each cluster. The technique can be used when the sample size is small and the population is spread out. It is also a good way to reduce the time and cost involved with selecting the sample.
3. Oversampling – This is a technique that involves choosing a bigger sample of subgroups who may not be adequately represented within the population. This technique can enhance the accuracy of statistical analysis and reduce bias.
4. Power Analysis Power analysis consists of determining sample sizes needed to detect specific effect sizes with a specified level of statistical strength. Using this method researchers can be sure that the sample size they use is enough to detect significant differences between groups.

References:

Babbie, E. R. (2017). Basics in social research. Cengage Learning.

Creswell, J. W. (2014). Research design: quantitative, qualitative and mixed method approaches. Sage publications.