Week 2 DQ 1 – Response to fellow classmate – Martha Grice, psychology homework help

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When designing an experiment choosing the sample size, based on the purpose and type of study, may be one of the most important aspects for the researcher to determine. Although greater sample sizes equate to greater statistical power, it may not be financially feasible for the researcher to have a very large sample. The idea is to identify the optimal sample size that will produce statistically accurate results, while staying within the research budget (Guo & Luh, 2009). Faber & Fonseca (2014) argue that in epidemiological studies, too small of a sample may not be generalizable, while too large a sample may statistically highlight differences that are not clinically relevant. This indicates that there are many varying opinions about the ideal sample size for statistical analysis, and widely varying schools of thought (de Winter, Gosling, & Potter, 2016; Kalkan, & Kelecioğlu, 2016). The general “rule of thumb” is a sample size 3 to 20 times the number of variables used in the study (Kalkan, & Kelecioğlu, 2016), however, it is reasonable for most studies to have a sample of at least 150 for accuracy and confidence (de Winter, Gosling, & Potter, 2016). When Kalkan & Kelecioğlu (2016) conducted a study of sample sizes using descriptive statistics, ranging from 50 to 2000, there were no excessive deviations from the normal distributions, with the skewness and kurtosis coefficients. When sample sizes are 25, errors are produced and the observed correlations may be rendered meaningless (de Winter, Gosling, & Potter, 2016). Depending on what one is seeking, different statistical tests may be used to ensure accuracy.

Faber and Fonseca (2014) gave an example of the implications of too small a sample in a study in comparing a new medical device that may be uncomfortable but very effective, to an existing device. The researcher only assigned 15 patients to each group, which was not enough to generalize the statistical analysis results. The small sample increased the chance of a false premise being assumed as true, meaning that the new device had no disadvantages compared to the existing therapy. People were subjected to potential suffering, the goals of the study were not realized, and financial resources were wasted. However, too large a sample size would have presented ethical considerations in using too many human subjects than necessary to produce valid statistical results.

Please provide a 250 word response to the above question. Please also use at least 1 peer reviewed article as a reference and please list reference in paper in APA 6th edition format.


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