-Answer the following questions:
1) Indicate two common methods used to understand the relationship between variables with bivariate
data sets:
2) How do these two main methods used with bivariate data sets differ?
3) What is meant by correlation analysis? What is it used for?
4) What is the correlation coefficient symbolized as?
5) What values does the correlation coefficient range between?
6) What value is expected for the correlation coefficient if the two variables are not correlated?
7) What value of the correlation coefficient is expected for a perfect NEGATIVE correlation:
8) Why is linear correlation analysis not appropriate to be applied when the relationship between the
variables is curved?
9) What type of plot is most appropriate for visualizing the relationship between two variables in a
correlation analysis?
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use attachment to answer following questions
10) Estimate the correlation coefficients for the plots in A and B.
A: r = B: r =
11) What distribution is used to test for significance in correlation analysis?
12) What are the null and alternative hypotheses that are being tested in correlation analysis?
Null:
Alternative:
13) What is the equation for the degrees of freedom used to look up the critical value in correlation
analysis? What does n represent in this equation?
14) How is the coefficient of determination symbolized in correlation analysis?
15) What is the range of the coefficient of determination?
16) What does the coefficient of determination represent in correlation analysis?
17) Is correlation analysis influence by the range of the data used? That is, if you are looking at the
relationship between two variables and use a limited range of the available variation in the variables,
does this affect the result? How?
18) What is a confounding variable?
19) How do confounding variables impact correlation analysis?
20) Can causation be determined in correlation analysis? Explain why or why not?