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Temple University Large Sample Size Problem & Misleading Statistic Discussion

 

The answer has to be between 150-250 words, including one reference or two. You have to agree with what he said.

Discussion post:

I agree that a larger sample size makes results more reliable. If you have too small of a sample size, data can be skewed. For example, if you ask people if they like chocolate milk and your sample size is four, if one person says no, your data will show that 25% of people do not like chocolate milk.

A larger sample size also leads to a smaller margin of error (Zamboni, 2018). This means that the data collected will be more accurate.

The only problem is to not get too large of a sample size. If the sample size becomes too large, the cost and effort may be too much, leading to more human error with cutting corners. It is also possible that more differing and abstract results could occur. Going back to the chocolate milk example, it is possible with a sample size of 2,500 people, 25 of those could be allergic to chocolate milk or lactose intolerant, skewing the results even further.

References

Armstrong, Richard A. “Is There a Large Sample Size Problem?” Wiley Online Library, John Wiley & Sons, Ltd, 17 Apr. 2019, onlinelibrary.wiley.com/doi/10.1111/opo.12618.

Zamboni, Jon. “The Advantages of a Large Sample Size.” Sciencing, 2 Mar. 2019, sciencing.com/advantages-large-sample-size-7210190.html.