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Velocity change with seating depth?

The standard deviation of the noise ( difference between the actual vs calculated results ) is sd = 4.5, which is typical for sd of individual velocity measurements. The probability that this is not a statistically relevant correlation is .001. In this example the signal due to jump overwhelmed the noise associated with the small sample size.

Regression Analysis: Velocity versus Jump

The regression equation is
Velocity = 3298 - 787 Jump


Predictor Coef SE Coef T P
Constant 3298.17 3.29 1001.28 0.000
Jump -786.8 137.9 -5.70 0.001


S = 4.52606 R-Sq = 84.4% R-Sq(adj) = 81.8%


Analysis of Variance

Source DF SS MS F P
Regression 1 666.59 666.59 32.54 0.001
Residual Error 6 122.91 20.49
Total 7 789.50


Unusual Observations

Obs Jump Velocity Fit SE Fit Residual St Resid
7 0.0330 3263.00 3272.21 2.31 -9.21 -2.37R

R denotes an observation with a large standardized residual.

No evidence of lack of fit (P >= 0.1).
 
The standard deviation of the noise ( difference between the actual vs calculated results ) is sd = 4.5, which is typical for sd of individual velocity measurements. The probability that this is not a statistically relevant correlation is .001. In this example the signal due to jump overwhelmed the noise associated with the small sample size.

Regression Analysis: Velocity versus Jump

The regression equation is
Velocity = 3298 - 787 Jump


Predictor Coef SE Coef T P
Constant 3298.17 3.29 1001.28 0.000
Jump -786.8 137.9 -5.70 0.001


S = 4.52606 R-Sq = 84.4% R-Sq(adj) = 81.8%


Analysis of Variance

Source DF SS MS F P
Regression 1 666.59 666.59 32.54 0.001
Residual Error 6 122.91 20.49
Total 7 789.50


Unusual Observations

Obs Jump Velocity Fit SE Fit Residual St Resid
7 0.0330 3263.00 3272.21 2.31 -9.21 -2.37R

R denotes an observation with a large standardized residual.

No evidence of lack of fit (P >= 0.1).

I misinterpreted what the OP was actually asking. ^^^This is the correct answer!
 
Last edited:

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