Correlation, Part 6

For a recap on Correlation and the rest of the series, go here.
Part 6 focuses on the correlation of wOBA to Runs. wOBA is weighted On Base Average, and is a linear weights stat on an On Base Percentage scale. Here is the formula, and some info.
The Correlation between Runs and wOBA was .93, so it has strong correlation. The R² is .87. This is by far the strongest correlation I've had in this study, and it is stronger than average, OBP and slugging, but strangely, not OPS.
The Graph: (Click to enlargen)

Correlation, Part 5

For an explanation of Correlation, go here and for the other parts, go here.
This is the correlation of Babip to Runs: BABIP is batting average on balls in play: it shows you the percent of the time you get a hit when the ball is put in play (Home runs are excluded.)
The correlation was .57 (remember 1 is the best) and the R^2 was .33, which shows the percent of variance.
The equation of the line of regression (or best fit) was f(x)=0x+.23 (in the y=mx+b model)
Click to make larger

Correlation, Part 4

This is the correlation of Isolated Power to Runs
For a explanation of correlation, go here.
Isolated Power is Slugging Percentage-batting average, and measures a player's true power
The correlation between Isolated Power and Runs is .66, just below the cut off mark of .7 for strong correlation.
The R squared is .43, and the equation is f(x)=0x+0.03
And here is the graph: (click to make bigger)

Correlation Part 3

The 3rd part, this shows the correlation of BB/K (walk/to strikeout ratio, offensively) with runs.
For an explanation of correlation go here.
The correlation of BB/K to runs is .37. The r squared is .14. There isn't that much correlation.
The equation is f(x)=0x+.2
Here is the graph:


Click to make bigger

Correlation, Part 2

For this part, I am focusing on K%, again from the years 2004-2008. For a recap of part one and an explanation of correlation, go here.
K% doesn't have any correlation, with a correlation of .02, and an R^2 of 0. This indicates that there is no correlation.
Here is the graph:
Click to make larger.
The equation (in slope-intercept form) is f(x)=0x+18.68.

Correlation, Part One

The first part of a 10 part series, I'm following on this great post to The Hardball Times by Dan Fox. I'm going to follow with different stats, however: BB%, K%, BB/K, BABIP (batting average on balls in play), Isolated Power (Slugging-average), weighted Runs Created and weighted Runs Above Average and weighted On Base Average (see fangraphs for those 3), home run/Fly ball percentage, and line drive percentage.
I'm seeing which one correlates with run scoring the most;
correlation runs from -1 to 1
-1 indicates that a high value in one is a low value in the other; 0 means that there is no correlation, and 1 is perfect correlation. The cut off for good correlation is .7, because the R^2 is .49, which is half, which is acceptable. (R^2 is correlation squared).
My data is from 2005-2008; I may redo it with 2009 data as well.
The Correlation between runs and walk percentage is .41 which is an R^2 of .16. It's not strong, so walk percentage does not relate well with scoring runs.
The equation of the line of regression (line of best fit) is y=0.01x+3.96 (it's in the mold of the slope-intercept form: y-mx+b)

Click to make bigger