DQ1: What are the differences between descriptive and inferential statistics?
According to Bennett (2009), the biggest difference between descriptive and inferential statistics is that descriptive statistics "deals with describing raw data in the form of graphics and sample of statistics" and inferential statistics "deals with estimating population parameters from sample data." This means that inferential statistics would be an estimate because the data would be estimated from sample data rather than using specific data whereas descriptive statistics would be more accurate. An example of descriptive statistics would be trying to find an average of something such as a G.P.A. or your overall grade in a class. …show more content…
Bennett, J. O., Briggs, W. L., & Triola, M. F. (2009). Statistical Reasoning for everyday life, Third Edition. Retrieved from https://ecampus.phoenix.edu/content/eBookLibrary2/content/eReader.aspx.
DQ1: Type I error is when the null hypothesis is wrongly rejected and this leads to wasting money trying to fix a process that isn't broken. (Bennett, Briggs, & Triola, 2009).
Type II error is when we wrongly fail to reject the hypothesis. (Bennett, Briggs, & Triola, 2009).
Researchers need to be concerned with both types of errors because they can cause a patient mental and physical suffering if they think they are suffering from something that they are not. Patients trust health care professionals and everything they say and when they tell us something we take it as accurate, for the most part, even when it is not what we want to hear. As far as I am concerned both errors are just as bad as the other. Both errors are going to cause some type of