- #1
yyttr2
- 46
- 0
I just thought I would share this, I was about to ask you fine people how to do this when I realized the square root of the sum of progressive to regressive data equals the highest point.
I.E.
1+2+3+4+5+6+5+4+3+2+1=36
6[tex]^{2}[/tex]=36
and I tried this a few times and the results were the same.
so then I began to think what if the pattern is not in intervals of 1.
0+2+4+6+8+10+8+6+4+2+0=50
which is 10[tex]^{2}[/tex]/2
I JUMPED FOR JOY!
so we can say
the sum of all numbers that progress and then regress is equal to the point of regression squared divided by the average change.
[tex]\frac{R^{2}_{p}}{\bar{\Delta}}[/tex]
so... I am just working on this while I type now.
If we make the numbers non-uniform...such as: 1+2+4+5+6+8+9+7+6+5+3+2+0 which is 1,2,1,2,1,2,1,2... instead of the normal 1,1,1,1 or 2,2,2,2,2..
1+2+4+5+6+8+9+7+6+5+3+2+0=58
I have been working on this for a while now...no luck..any help?
I.E.
1+2+3+4+5+6+5+4+3+2+1=36
6[tex]^{2}[/tex]=36
and I tried this a few times and the results were the same.
so then I began to think what if the pattern is not in intervals of 1.
0+2+4+6+8+10+8+6+4+2+0=50
which is 10[tex]^{2}[/tex]/2
I JUMPED FOR JOY!
so we can say
the sum of all numbers that progress and then regress is equal to the point of regression squared divided by the average change.
[tex]\frac{R^{2}_{p}}{\bar{\Delta}}[/tex]
so... I am just working on this while I type now.
If we make the numbers non-uniform...such as: 1+2+4+5+6+8+9+7+6+5+3+2+0 which is 1,2,1,2,1,2,1,2... instead of the normal 1,1,1,1 or 2,2,2,2,2..
1+2+4+5+6+8+9+7+6+5+3+2+0=58
I have been working on this for a while now...no luck..any help?