I have to give Tom the edge over Banach because of the international careers. Wasn’t Banach’s fault and I’m glad he retired when he did, but them’s the breaks.I like your list.
They are all very close, but I would go with this:
1. Banach
2. Tom
3. McIlravy
4. Lee
5. Barry Davis (you didn't include him, but all-time wins leader for Iowa and a silver medalist)
6. Terry
I think "it" was detoured and redirected.
Ask the Mod to fix it!!Thread detoured and redirected
Which one? There are 4 new staff members.Ask the Mod to fix it!!
I ain’t fixin shitWhich one? There are 4 new staff members.
I was the football coach for the CR Prairie 9th grade team way back and Barry was a running back on that team. Ran into him in Madison when he was their coach. His father never watched him compete at Prairie in wrestling. He was a drunk. Sad.I like your list.
They are all very close, but I would go with this:
1. Banach
2. Tom
3. McIlravy
4. Lee
5. Barry Davis (you didn't include him, but all-time wins leader for Iowa and a silver medalist)
6. Terry
So was Tom and Terry’s dad. Neither Tom nor Terry have ever taken a drink in their lives.I was the football coach for the CR Prairie 9th grade team way back and Barry was a running back on that team. Ran into him in Madison when he was their coach. His father never watched him compete at Prairie in wrestling. He was a drunk. Sad.
I was the football coach for the CR Prairie 9th grade team way back and Barry was a running back on that team. Ran into him in Madison when he was their coach. His father never watched him compete at Prairie in wrestling. He was a drunk. Sad.
Some of the most driven people are "Adult Children of Alcoholics (ACOA)."So was Tom and Terry’s dad. Neither Tom nor Terry have ever taken a drink in their lives.
Long time ago, I could do the calculations in record time. As with many things, you don’t use it you lose it…I'm so smart, I knew the definiation and asked AI to confirm it.
what is: the square root of the sum of the sqaured diffeence betwen data and the average of the data population
Gemini said
That is a mouthful, isn't it? What you’ve just described is the mathematical definition of Standard Deviation (specifically for a population).
In simpler terms, it is a measure of how spread out your numbers are. If the standard deviation is low, the data points are huddled close to the average; if it’s high, they’re scattered all over the place.
Breaking Down the Definition
To see how your description turns into a formula, let's look at the steps:
- "Difference between data and the average": You take each individual number (x) and subtract the mean (μ).
- "Squared difference": You square those results so that negative differences don't cancel out positive ones.
- "Sum of the squared difference": You add all those squared values together (∑).
- "Square root": Finally, you take the square root of that sum (after dividing by the number of data points, N) to bring the scale back to the original units.
The Formula
In formal notation, the population standard deviation (σ) looks like this:
σ=N∑i=1N(xi−μ)2