The following is a chart of 25 baseball players' salaries and statistics from 2016.

Player Name	RBI's	HR's	AVG	Salary (in millions)
Brian McCann	58	20	0.242	17.000
Joe Mauer	49	11	0.261	23.000
Coco Crisp	55	13	0.231	11.000
Justin Turner	90	27	0.277	5.100
Mark Teixeira	44	15	0.204	23.125
Miquel Cabrera	108	38	0.316	28.050
Buster Posey	80	14	0.288	20.802
Yoenis Cespedes	86	31	0.284	27.500
Victor Martinez	86	27	0.289	18.000
Matt Kemp	108	35	0.268	21.500
Matt Holliday	62	20	0.246	17.000
Ben Zobrist	76	18	0.272	10.500
Jorge Soler	31	12	0.238	3.667
Albert Pujols	119	31	0.268	25.000
Prince Fielder	44	8	0.212	18.000
Leonys Martin	47	15	0.245	4.150
Jason Heyward	49	7	0.230	21.667
Chris Davis	84	38	0.221	21.119
Aaron Hill	38	10	0.262	12.000
Ryan Howard	59	25	0.196	25.000
Adrian Gonzalez	90	18	0.285	21.857
Mike Trout	100	29	0.315	16.083
Logan Forsythe	52	20	0.264	2.750
Matt Wieters	66	17	0.243	15.800
Justin Upton	87	31	0.246	22.125

A) RBI vs. Salary

Complete a correlation analysis, using RBI's as the x-value and salary as the y-value.

1) In order to have positive correlation at a 5% significance level, the r test statistic (the correlation coefficient) needs to be greater than what?  

2) Correlation coefficient:

3) Regression Equation: $\displaystyle {y}=$ Preview Question 6 Part 3 of 12  

4) Do you have significant positive correlation? ? Yes No

B) HR vs. Salary

Complete a correlation analysis, using HR's as the x-value and salary as the y-value. 

1) Correlation coefficient:

2) Regression Equation: $\displaystyle {y}=$ Preview Question 6 Part 6 of 12    

3) Do you have significant positive correlation? ? Yes No  

C) AVG vs. Salary

Complete a correlation analysis, using AVG as the x-value and salary as the y-value. 

1) Correlation coefficient:

2) Regression Equation: $\displaystyle {y}=$ Preview Question 6 Part 9 of 12    

3) Do you have significant positive correlation? ? Yes No

D) Prediction

1) Based on your analysis, if you had to predict a player's salary, which method would be the best? Select an answer Regression equation with RBI's Regression equation with HR's Regression equation with AVG The average of the 25 salaries

2) Using that method, predict the salary for Jayson Werth. His stats were:

RBI: 70

HR: 21

AVG: 0.244

Based on your analysis, his predicted salary would be: $ million

His actual salary was $21.571 million.