b. With a small sample, a single point can have a large effect on the magnitude of the correlation.
Change the score X = 5 to X= 0 and compute the Pearson correlation again. You should find that the change has a dramatic effect on the value of the correlation.

18. Sketch a graph showing the line for the equation Y= 2X + 4. On the same graph, show the line for Y = X - 4.

20. A set of n = 20 pairs of scores (X and Y values) has SSx = 25, SSy =16, and SP = 12.5. If the mean for the X values is M = 6 and the mean for the Y values is M = 4.

a. Calculate the Pearson correlation for the scores.

b. Find the regression equation for predicting Y from the X values.

22. For the following data:

a. Find the regression equation for predicting Y from X.

b. Use the regression equation to find a predicted Y for each X.

c. Find the difference between the actual Y value and the predicted Y value for each individual, square the differences, and add the squared values to obtain SSresidual.

d. Calculate the Pearson correlation for these data. Use r2 and SSY to compute SSresidual with Equation 15.18. You should obtain the same value as in part c.
X Y
1 2
4 7
3 5
2 1
5 14
3 7

Solution Summary

The solution provides step by step method for the calculation of correlation and regression analysis. Formula for the calculation and Interpretations of the results are also included.

Conduct a correlation matrix using the Forbes 500 dataset. Determine which variables have a significant relationship.
Select an independent and dependent variables and run a regressionanalysis. What can you conclude from the findings?

Question 1:
What is correlation? Does correlation prove causation? Why or why not? Explain and provide examples to support your explanation.
Questions 2:
What are the differences between regressionandcorrelation analysis?

When we carry out a regression, we assume a direct causal relationship. In a correlation analysis, we don't make such an assumption, but nevertheless determine whether 2 variables are related. Briefly explain how two variables can be correlated without one directly influencing the other (=without causal relationship)

The coefficient of correlation was computed to be -0.60. This means
a. the coefficient of determination is .
b. as X increase Y decreases.
c. X and Y are both 0.
d. as X decreases Y decreases.
Which of the following is a stronger

Please help answer the following question. Provide at least 200 words.
What is the possible uses of regressionandcorrelation analysis in doctoral-level research? Would I be able to use these techniques in my dissertation, or any application in other areas?

1. Conduct a regression analysis to determine if age (independent variable) has any effect on the number of vitamins/supplements people take. State what you are testing and what the x (independent) and y (dependent) variables are. Test for correlationand explain the regression results, if necessary.
2. Conduct a regression a

You are interested in finding out if a student's ACT score is a good predictor of their final college grade point average (GPA). You have obtained the following data and are going to conduct a regressionanalysis. What is the best fit to conduct this analysis?
ACT | GPA
22.0 | 3.0
32.0 | 3.78
33.0 | 3.68
21.0 | 2.94
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