Help me resolve some model uncertainty for a real-world application?

I have a set of 3 data points where X represents the amount of gunpowder in a cartridge (by weight in grains), and Y represents the peak chamber pressure of the round when it is fired:

  • (0, 200) – no powder, but >0 pressure because the casing still has a primer ignition when the trigger is pulled.
  • (23.2, 37400)
  • (25.8, 51200)

I’m trying to decide on which type of equation to use to find a curve that intersects each of the points in a way that allows me to most accurately estimate chamber pressure for any given powder charge above 0.

y = AeBx + C seems like a good option, but then so does y = Arx + C.

Perhaps these are effectively the same, and somebody can educate me on reasons to use one or other other?

submitted by Nevin Manimala Nevin Manimala /u/B_Huij
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I put a Shelby Mustang shifter in my 1993 Impreza. Now I have another question.

Long story short, I bought a 2008 Shelby Mustang shift knob from eBay for my sim rig for $5 and put it in my Impreza since my rig is in storage three states away at the moment.

It’s been funny and nice so far.

And then a friend of mine said I should get a cloth boot for it now. My question is: what boot should I get that will fit the Mustang shifter AND the Impreza boot hole, and how would I get it to fit especially since a vandal broke the plastic that surrounds the boot (or am I approaching this all wrong)?

submitted by Nevin Manimala Nevin Manimala /u/MDGLee
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Exploratory data analysis and tests

Hello everyone,

I have a question for the experienced people out there :

When you get started with a dataset, – let’s say tabular data concerning credit fraud, churns or insurance – you need to analyze, what are your go-to reflexes and tools?

What are some tests you can rely on and interprete further down the road?

Thanks, a newbie

submitted by Nevin Manimala Nevin Manimala /u/DiogenicOrder
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How can I get better at driving when it’s dark and raining hard?

I’m trying to figure out why driving in the dark and heavy rain is so insanely stressful for me. I was driving home from a trip last night and white knuckling my way through Eastern Pennsylvania. I don’t usually have a problem with driving at night, or in the rain, but both is just a problem. I could barely see the side lines or the lane markers, especially when my headlights reflected off the signs onto puddles on the road, and was constantly getting passed by semis kicking up water so I could barely see. I think part of the problem is that when I drive in daylight my vision is focused really far ahead of me – usually about 1/10th of a mile, from what I can tell – and when I’m trying to drive in the rain I have to constrict my vision to staring at the road markings directly in front of my car, which freaks me the hell out.

submitted by Nevin Manimala Nevin Manimala /u/sxeQ
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Is there a way I can give a greater weight to records with higher total observations for my odds ratio?

Sorry if this is not written with proper terminology, I am new to this and not exactly sure what it is I am looking for.

I have a data set of census tracts (the observations). In each census tracts, there are two values 1) the number of all tweets geocoded from within that tract and 2) the number of tweets about a particular topic, say, Trump.

I am using a calculation that is:

( [trump tweets in the census tract] / [sum of all trump tweets] ) / ( [ tweets in the census tract] / [sum of all tweets] )

There are census tracts where 75% of the tweets are about Trump but that only means three out of four tweets are about him. Whereas there are other census tracts where maybe only 10% of the tweets are about Trump but there are 60 tweets. Is there a way to give greater weight to the census tracts that have a total number of observations?

Again, if anything isn’t clear, please let me know and I will try to clarify.

submitted by Nevin Manimala Nevin Manimala /u/giscard78
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