Following are the case summary and discussion by four students based on the case in the attachment. Please select one student's post and provide your own reflection. Any thoughts or question relate to his/her post will be fine. What am looking for just couple sentences. Also please check out the attachment for the case.
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|The pearson correlation between total advertising expenditure and new personal injury cases is 0.202 according to minitab. The pearson correlation between total advertising expenditure and new workers compensation is 0.197.This tells me that there is a minutely closer correlation between ad expenditure and personal injury than ad expenditures and compensation. However, the pearson coefficient ideally wants to be closer to 1 or -1 to show a close correlation and .202 and .197 are far from both.|
A correlation is a mutual relationship or connection between two or more things. Pearson correlation of Total Advertising Expenditures and New Personal Injury Cases is 0.202 with a P-Value of 0.169. Pearson correlation of Total Advertising Expenditures and workers compensation is 0.197 with a P-Value of 0.180
The easiest way to get the answers is to use technology such as minitab. On page 620 of the book, it shows how to use minitab to get the answers for this data set. As always, youtube has lots of videos on calculating regression using minitab, excel, graphing calculator, etc. Correct, linear regression allows us to add in an equation to try to interpret the dataset. We know this by an easier term, "line fit". I use this "line fit" model at lot at work. I use it to predict the lifetime of a component and try to have people replace the component before it fails (usually it is linear fit). In the semiconductor industry, having a multi-million dollar machine failing is not acceptable so you have to perform maintenance (PM) on the machine.
Minitab is a great resource, but I am a bit of a novice as well. As for online help, I prefer Khan Academy for almost everything. They have videos on youtube as well.