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Min, max, ES, Average and SD

SD and ES has nothing to do with the following tune :"Barrel pointing down when MV is rising", however, with load SD/ES it would help stay in the "tuned node.
Regardless of lower SD/ES which correlates with vertical dispersion at very long range or increasing the MV to flatten the trajectory, or the actual tune, or even the group size itself.

At very long ranges. the wind would move the bullets in 10s of inches sideways when the wind call is off, or the wind is changing from mid to gusting each other minute.
Of course SD has some effect on vertical dispersion, but the exact effect is not determined using a ballistic calculator. I quit following Litz but I don't recall his ever investigating harmonics. That is why we tune with a target instead of a Chrono.
 
I don't nothing bout nuthin'.... but what that graphic shows just makes immense logical sense to me.... low SD gives consistent vertical trajectory, amd therefore vertical dispersion, leaving horizontal dispersion to be the main culprit of inaccuracy. incluidn g everything from wind to rifle cant.
It’s only a simulation of a 20 in target, if you use that as a guide for long range Benchrest shooting you’ll likely come in last place.
 
It’s only a simulation of a 20 in target, if you use that as a guide for long range Benchrest shooting you’ll likely come in last place.
Simulations based on thorough, comprehensive input parameters can be very useful. The WEZ is not, and can be very misleading.
 
It’s only a simulation of a 20 in target, if you use that as a guide for long range Benchrest shooting you’ll likely come in last place.
WEZ uses Monte Carlo simulation, at least 1000 sims are used, and it could be more depending on how many input parameters are to be varied at the same time.
 
It’s only a simulation of a 20 in target, if you use that as a guide for long range Benchrest shooting you’ll likely come in last place.

I've experienced the same IRL. Lower ES / SD's make for more good hits out to 700 rd.

My personal experience. Not saying it has to be same for anyone else. Not saying something different doesn't happen beyond 700 yd.

But... I mean....doesn't a 105 gr Berger HT have different trajectories at 3100 fps vs. 3150 fps? (ES of 50 fps) Wouldn't you rather have an ES of 20 than 50? Don't 10 rounds with a SD of 5 off 3100 have lower vert dispersion than 10 rounds with a SD of 25?
 
Simulations based on thorough, comprehensive input parameters can be very useful. The WEZ is not, and can be very misleading.

I humbly request an explantion of the problem of the WEZ methodology. I know nothing about them / it, and don't work for the company. :)
 
I humbly request an explantion of the problem of the WEZ methodology. I know nothing about them / it, and don't work for the company. :)
The methodology is fine, but it does not incorporate the major factor of harmonic tuning which greatly influences the effect of velocity deviations on vertical dispersion.
 
The methodology is fine, but it does not incorporate the major factor of harmonic tuning which greatly influences the effect of velocity deviations on vertical dispersion.
You said above the WEZ does not have "thorough comprehensive input parameters." How is that NOT a problematic methdology? Now you say the methdology of NOT having "thorough comprehensive input parameters" is just fine. Whats was wrong with WEZ's "input parameters?" And how is it "just fine" now?

Anyway.... Target hits (what WEZ shows) are WAAAAYYYY more important than whatever you just said. Above or just now. :)

Only hits count.
 
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My Excel has 9 different formulas for STDV. Which is the right one?
  • STDEV assumes that its arguments are a sample of the population. If your data represents the entire population, then compute the standard deviation using STDEVP.
  • The standard deviation is calculated using the "n-1" method.
  • Arguments can either be numbers or names, arrays, or references that contain numbers.
  • Logical values and text representations of numbers that you type directly into the list of arguments are counted.
  • If an argument is an array or reference, only numbers in that array or reference are counted. Empty cells, logical values, text, or error values in the array or reference are ignored.
  • Arguments that are error values or text that cannot be translated into numbers cause errors.
  • If you want to include logical values and text representations of numbers in a reference as part of the calculation, use the STDEVA function.
  • STDEV uses the following formula:
    Formula

    where x is the sample mean AVERAGE(number1,number2,…) and n is the sample size.
 
You said above the WEZ does not have "thorough comprehensive input parameters." How is that NOT a problematic methdology? Now you say the methdology of NOT having "thorough comprehensive input parameters" is just fine. Whats was wrong with WEZ's "input parameters?" And how is it "just fine" now?

Anyway.... Target hits (what WEZ shows) are WAAAAYYYY more important than whatever you just said. Above or just now. :)

Only hits count.

I'm speaking technically that the Monte Carlo simulation is a widely used, accepted methodology. The WEZ is not a sufficiently comprehensive implementation of a good method. On the other hand to make progress in such an application, to release something at this stage is fine in order to get people thinking as long as its significant shortcomings are noted for further discussion.
 
I'm speaking technically that the Monte Carlo simulation is a widely used, accepted methodology. The WEZ is not a sufficiently comprehensive implementation of a good method. On the other hand to make progress in such an application, to release something at this stage is fine in order to get people thinking as long as its significant shortcomings are noted for further discussion.
Ok.

I still say on target hits are more impotant to me than theoretical mathematical simulations.

WEZ shows good hits on target as a result of low SD. .. partucularly in the vertical plane

That is good enuf for me.
 
Thank you for that great definition.
The easy way to remember is to account for the difference between a sample versus a whole population.

With a sample of a population the denominator term is going to have an "n-1" term in it (that tends to make the value higher).
 

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