Hcs/438 Dq's

1308 words 6 pages
HCS/438 DQ’s
Week 1:
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…

Variance is the average squared difference of the scores from the mean. Standard deviation is the square root of the variance or a measure of how widely data is spread around the mean of a data set (Bennett, Briggs, & Triola, 2009).Measures of variability are essential to inferential statistics because they provide more information on the data collected. The mean, median, and mode are not always sufficient in supporting the evidence found so these methods simply supply the supporting evidence.

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.
Week 3
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