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

Player Name	RBI's	HR's	AVG	Salary (in millions)
Hanley Ramirez	111	30	0.286	22.750
Denard Span	53	11	0.266	5.000
Robinson Cano	103	39	0.298	24.050
Carlos Gonzalez	100	25	0.298	17.454
Adrian Gonzalez	90	18	0.285	21.857
Justin Turner	90	27	0.277	5.100
Matt Kemp	108	35	0.268	21.500
Hunter Pence	57	13	0.289	18.500
Jean Segura	64	20	0.320	2.600
Joe Mauer	49	11	0.261	23.000
Shin-Soo Choo	17	7	0.242	20.000
Ben Zobrist	76	18	0.272	10.500
Yoenis Cespedes	86	31	0.284	27.500
Miquel Cabrera	108	38	0.316	28.050
Troy Tulowitzki	79	24	0.256	20.000
Adrian Beltre	104	32	0.300	18.000
Chris Davis	84	38	0.221	21.119
Adam Jones	83	29	0.265	16.000
Jayson Werth	70	21	0.244	21.571
Justin Upton	87	31	0.246	22.125
Buster Posey	80	14	0.288	20.802
Mike Trout	100	29	0.315	16.083
Jorge Soler	31	12	0.238	3.667
Aaron Hill	38	10	0.262	12.000
J.D. Martinez	68	22	0.307	6.750

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 Jacoby Ellsbury. His stats were:

RBI: 56

HR: 9

AVG: 0.263

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

His actual salary was $21.143 million.