toddcc1
Well-known member
- Joined
- Feb 28, 2015
- Location
- Monument...
Garbage in garbage out. You are not capturing the proper variables in your analysis so your results are flawed. Done time and IT are dependent on cooking temperature, heat transmission mechanism (conduction convection radiant) thickness volume and surface area, and the specific qualities of the meat.
Your data is based on an extremely small sample that is not representative of the full range of brisket sizes and shapes. You don't seem to have any variation in cook temperatures or heat transmission etc. You assume a normal distribution (or several) but have no evidence that shows your population can be reasonably assumed to be normally distributed.
The software is spitting out results, but you need to understand the assumptions behind the formulas and realize that where you are violating those assumptions, the resulting R squared, T stat and standard error will be incorrect, potentially grossly incorrect.
Yes, you're correct. Temps matter, which I qualify. Done time and IT are the same and they do relate to temps, which is why I control my temps and have stated as such. Thickness and surface volume, hmmmm. Now that one, that one is a challenge. I did only use weight, the mean of which was 12.6 lbs. So you got me there, though by selection alone, if the brisket was too abnormal in shape/size but weighed 13 lbs., I probably wouldn't buy it. I also suspect you and many others on this forum would likely follow suit. Not an exact science, sure. Then again, processors and butcher's attempt to create consistency in their product and the only two factors they rely upon, the grade and the weight. They don't say anything about the surface volume or thickness...just weight and beef grade.
I believe I understand a few assumptions and stated those. Fifteen samples is not reliable. Thirty is considered the bare minimum. I use the normal distribution because it's statistically convenient, because I can use the mean and I can use the standard deviation. And most importantly, because the Central Limit Theorem allows me to.