SJFC MSTI 130 - Correlation (32 pages)

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Correlation



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Correlation

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Lecture Notes


Pages:
32
School:
St. John Fisher College
Course:
Msti 130 - Mathematical Modeling and Quantitative Analysis

Unformatted text preview:

Chapter 7 Correlation1 So far in this book we have limited ourselves to looking at only one variable at a time trying to learn as much as possible about that single variable However most of our data is made up of many variables all interacting and having effects on each other In this chapter you will explore relationships between two variables using graphical methods scatterplots computational methods correlation and algebraic methods equations of functions As a result of this chapter students will learn How to read and interpret a scatterplot How correlation describes the relationship between two variables The meanings of positive and negative relationships between two variables About the slope and y intercept of straight lines and how to compute these As a result of this chapter students will be able to Identify variables with a positive or negative relationship using the correlation coefficient Construct a correlation table using StatPro to determine which variable relation ships are most influential Estimate the correlation coefficient of two variables based on a scatterplot Set up a scatterplot according to conventions about axes etc Add trendlines to a scatterplot 1 c 2011 Kris H Green and W Allen Emerson 199 200 7 1 CHAPTER 7 COORELATION Picturing and Quantifying the Relationship Between Two Variables In many of the previous examples in this book you have probably been tempted to go too far in your conclusions For example if you were to look at information about employees at a company and you learned that the salaries were negatively skewed and that the ages of your employees were also negatively skewed you might be tempted to claim that one variable for instance age influences the other variable in this case salary However it would be dishonest to make such a claim with the tools we have discussed so far In fact the relationship between the two variables could be exactly the opposite of what you claim it could be that the low salaries are all earned by



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