Correlation revelation-chi-squared analysis

Reference no: EM1395689

Regression and Correlation are two of the most often used and abused tools in research. People are quick to jump to conclusions that if a relationship exists between two variables, then one must cause (causation) the other. There are many reasons why two variables can be related without causality. Please respond to the following:

Comparing the amount of money people spend and the amount people save, your analysis revealed an R-squared=0.97. Should you use this for predictive purposes and why?

Comparing the number of cops on our streets and the number of reported crimes, your analysis revealed an R-squared=0.40. Should you use this for predictive purposes and why?

How could this apply in your profession?

Suppose your instructor randomly surveyed his or her performance (i.e., students "graded" the teacher) this semester). The frequency of ratings are as follows: A: 10 B: 6 C: 6 D: 3 F: 2 Please answer the following: Did your instructor, over many years of teaching, perform outstandingly? Why or why not? Provide analysis. Can you describe a chi-squared application in your profession?

Reference no: EM1395689

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