Great Article, with a lot of math

[spencer rifle]

They say "do the math." This guy does it:
https://medium.com/s/story/the-surp...-of-the-tin-foil-hat-gun-prepper-15fce7d10437

 

[Cpt Caveman]

Well worth the time to read. Good links too. Thanks.

 

[9mmfan]

A great piece of writing.

 

[Wolfhound]

Great article. Props for posting it and rep given.

 

[patience0830]

Thanks for the link.

 

[PhxCollier]

Really good article. And to use the same math approach to violent crime in Indiana, I get this -
according to uniform crime data https://www.ucrdatatool.gov/Search/Crime/State/RunCrimeOneYearofData.cfm

in Indiana in 2014 we had 24,099 violent crimes, and the population was 6,596,855
odds of being a victim was 24,099/6,596,855 = .00365
and the odds for not being a victim for one year 1- .00365 = .99635
odds for not being a victim for 10 years in Indiana (.99635)^10= .96409
odds for not being a victim during your entire life in Indiana (.99635)^78.7= .74993

or there is an approximately 25% chance you will be a victim of a violent crime during your lifetime if you live in Indiana.

 

[PistolBob]

Really good article. And to use the same math approach to violent crime in Indiana, I get this -
according to uniform crime data https://www.ucrdatatool.gov/Search/Crime/State/RunCrimeOneYearofData.cfm

in Indiana in 2014 we had 24,099 violent crimes, and the population was 6,596,855
odds of being a victim was 24,099/6,596,855 = .00365
and the odds for not being a victim for one year 1- .00365 = .99635
odds for not being a victim for 10 years in Indiana (.99635)^10= .96409
odds for not being a victim during your entire life in Indiana (.99635)^78.7= .74993

or there is an approximately 25% chance you will be a victim of a violent crime during your lifetime if you live in Indiana.

None of that matters, depending on where in Indiana you live. Densely populated minority areas will have a much higher risk, especially if they are economically depressed areas as well.

 

[churchmouse]

None of that matters, depending on where in Indiana you live. Densely populated minority areas will have a much higher risk, especially if they are economically depressed areas as well.

Those who would do harm are branching out from the Urban sprawl . More than folks think they are.

The Meth/drug subculture is everywhere.

 

[eldirector]

None of that matters, depending on where in Indiana you live. Densely populated minority areas will have a much higher risk, especially if they are economically depressed areas as well.

Actually, the math is fine for that data set. If you want to use a different data set, you just need the crime rate for that population. Of course, this gets really complicated if we try to factor in visiting the nearest town for groceries and such, and then occasional trips to "the big city" for a CostCo run or to catch a movie. It is rare for one to stay completely within a single small group for an entire life.

Another way to look at the 25% probability of a violent crime: there is a 1-in-4 chance of being a victim. Look at you and 3 other people you know. One of you will (likely) be a victim of a violent crime in a lifetime.

 

[Ziggidy]

Excellent article - to make you think.

As stated, things are spreading from the inner cities, outward. Government subsidizing the move away from cities adds to the spread of the cancer. Add sanctuary cities that are cancer magnets means there is a steady flow. These tumors (cities) teach them socialism and then spreads their cancer to the rest of the body.

The tumors needs to be removed......then the cancer will stop.

The mentioned math within the article hits on a calculated time cycle when the cancer treatment will/may begin. Speculation...

 

[PhxCollier]

To pistolbob’s point, I did find this data for Marion county ( I don’t know how accurate)
https://www.neighborhoodscout.com/in/indianapolis/crime

in Marion county there were 11,946 violent crimes and the population used in that web site was 855,164. So,

your odds of of being a victim in Marion county for one year are 11,946/855,164 = .01397

your odds for not being a victim in Marion county for one year are 1- .01397 = .9860
your odds for not being a victim Marion county for 10 years are (.9860)^10 = .8688
your odds for not being a victim in Marion county during your entire life (.9860)^78.7 = .3297

so there is an approximately 2/3rds chance you will be a victim if you live in Marion county for your whole life.

Given the cavats talked about above, people not living in Marion county but being in the county for one reason or another, etc....

 

[nwihiker]

Really good article. And to use the same math approach to violent crime in Indiana, I get this -
according to uniform crime data https://www.ucrdatatool.gov/Search/Crime/State/RunCrimeOneYearofData.cfm

in Indiana in 2014 we had 24,099 violent crimes, and the population was 6,596,855
odds of being a victim was 24,099/6,596,855 = .00365
and the odds for not being a victim for one year 1- .00365 = .99635
odds for not being a victim for 10 years in Indiana (.99635)^10= .96409
odds for not being a victim during your entire life in Indiana (.99635)^78.7= .74993

or there is an approximately 25% chance you will be a victim of a violent crime during your lifetime if you live in Indiana.

Really interesting article, and this IN specific math definitely makes a good case for carrying

 

[cosermann]

Good article. Puts some numbers to what many know intuitively from history and observation.

 

[BluedSteel]

Great article. Thanks for sharing it.

I like the way INGOers have taken crime statistics and done their own calculations. But I don't like how the numbers work out. Take crime probabilities for your location times Campbell's numbers times NOAA's stats for severe weather and it's not good.

 

[searpinski]

Interesting article. Prepping is a responsible action indeed. I'm going to prep and continue prepping regardless of what statistics say. I really dislike the use of statistics here without better modeling (especially in the United States where the sample size is 2!). If you think it's right to prep, PREP (and you should)! See below for why I dislike simple models.

Olympic 100m Dash Scenario
If you examine times over the years, there's been a overall downward trend. If you calculate a line to fit this trend, you get a very reasonable correlation coefficient (0.9153). It could help us see what times to expect in the next few years, but it also predicts that in the year 3349, it will take an Olympic runner 0.0 seconds to run the 100m dash. We know that it could NEVER take 0.0 seconds for a 100m dash. At some point, the time will plateau because human beings can only run so fast.

[TABLE="width: 156"]
[TR]
[TD]date[/TD]
[TD]time[/TD]
[/TR]
[TR]
[TD="align: right"]7/6/1912[/TD]
[TD="align: right"]10.6[/TD]
[/TR]
[TR]
[TD="align: right"]9/16/1920[/TD]
[TD="align: right"]10.6[/TD]
[/TR]
[TR]
[TD="align: right"]4/23/1921[/TD]
[TD="align: right"]10.4[/TD]
[/TR]
[TR]
[TD="align: right"]8/8/1929[/TD]
[TD="align: right"]10.4[/TD]
[/TR]
[TR]
[TD="align: right"]8/25/1929[/TD]
[TD="align: right"]10.4[/TD]
[/TR]
[TR]
[TD="align: right"]8/9/1930[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]8/1/1932[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]8/12/1933[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]8/6/1934[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]8/26/1934[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]9/15/1934[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]9/23/1934[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]6/15/1935[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1936[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]9/26/1936[/TD]
[TD="align: right"]10.3[/TD]
[/TR]
[TR]
[TD="align: right"]6/6/1941[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]5/15/1948[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]7/9/1948[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]8/25/1951[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]10/31/1954[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]5/19/1956[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]6/1/1956[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]6/22/1956[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]6/29/1956[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]6/29/1956[/TD]
[TD="align: right"]10.2[/TD]
[/TR]
[TR]
[TD="align: right"]8/3/1956[/TD]
[TD="align: right"]10.1[/TD]
[/TR]
[TR]
[TD="align: right"]8/4/1956[/TD]
[TD="align: right"]10.1[/TD]
[/TR]
[TR]
[TD="align: right"]10/20/1956[/TD]
[TD="align: right"]10.1[/TD]
[/TR]
[TR]
[TD="align: right"]10/27/1956[/TD]
[TD="align: right"]10.1[/TD]
[/TR]
[TR]
[TD="align: right"]4/18/1959[/TD]
[TD="align: right"]10.1[/TD]
[/TR]
[TR]
[TD="align: right"]6/21/1960[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]7/15/1960[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]8/15/1964[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]10/15/1964[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]5/27/1967[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]6/17/1967[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]4/2/1968[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]5/31/1968[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]10[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]10/14/1968[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]7/1/1972[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]7/1/1972[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]6/21/1974[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]6/5/1975[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]7/16/1975[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]8/22/1975[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]3/27/1976[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]4/3/1976[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]5/1/1976[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]5/22/1976[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]10/15/1964[/TD]
[TD="align: right"]10.06[/TD]
[/TR]
[TR]
[TD="align: right"]6/20/1968[/TD]
[TD="align: right"]10.03[/TD]
[/TR]
[TR]
[TD="align: right"]10/13/1968[/TD]
[TD="align: right"]10.02[/TD]
[/TR]
[TR]
[TD="align: right"]10/14/1968[/TD]
[TD="align: right"]9.95[/TD]
[/TR]
[TR]
[TD="align: right"]7/3/1983[/TD]
[TD="align: right"]9.93[/TD]
[/TR]
[TR]
[TD="align: right"]8/30/1987[/TD]
[TD="align: right"]9.83[/TD]
[/TR]
[TR]
[TD="align: right"]8/30/1987[/TD]
[TD="align: right"]9.93[/TD]
[/TR]
[TR]
[TD="align: right"]8/17/1988[/TD]
[TD="align: right"]9.93[/TD]
[/TR]
[TR]
[TD="align: right"]9/24/1988[/TD]
[TD="align: right"]9.79[/TD]
[/TR]
[TR]
[TD="align: right"]9/24/1988[/TD]
[TD="align: right"]9.92[/TD]
[/TR]
[TR]
[TD="align: right"]6/14/1991[/TD]
[TD="align: right"]9.9[/TD]
[/TR]
[TR]
[TD="align: right"]8/25/1991[/TD]
[TD="align: right"]9.86[/TD]
[/TR]
[TR]
[TD="align: right"]7/6/1994[/TD]
[TD="align: right"]9.85[/TD]
[/TR]
[TR]
[TD="align: right"]7/27/1996[/TD]
[TD="align: right"]9.84[/TD]
[/TR]
[TR]
[TD="align: right"]6/16/1999[/TD]
[TD="align: right"]9.79[/TD]
[/TR]
[TR]
[TD="align: right"]9/14/2002[/TD]
[TD="align: right"]9.78[/TD]
[/TR]
[TR]
[TD="align: right"]6/14/2005[/TD]
[TD="align: right"]9.768[/TD]
[/TR]
[TR]
[TD="align: right"]5/12/2006[/TD]
[TD="align: right"]9.766[/TD]
[/TR]
[TR]
[TD="align: right"]6/11/2006[/TD]
[TD="align: right"]9.763[/TD]
[/TR]
[TR]
[TD="align: right"]8/18/2006[/TD]
[TD="align: right"]9.762[/TD]
[/TR]
[TR]
[TD="align: right"]9/9/2007[/TD]
[TD="align: right"]9.74[/TD]
[/TR]
[TR]
[TD="align: right"]5/31/2008[/TD]
[TD="align: right"]9.72[/TD]
[/TR]
[TR]
[TD="align: right"]8/16/2008[/TD]
[TD="align: right"]9.69[/TD]
[/TR]
[TR]
[TD="align: right"]8/16/2009[/TD]
[TD="align: right"]9.58[/TD]
[/TR]
[/TABLE]

y is time, x is date

above dates calculated using excel's weird date format
y = -2E-05x + 10.592
0 = 529600 or 12/28/3349

 

[cosermann]

Interesting article. Prepping is a responsible action indeed. I'm going to prep and continue prepping regardless of what statistics say. I really dislike the use of statistics here without better modeling (especially in the United States where the sample size is 2!).

Seems to me the sample size is the number of years sampled - 340.
Two events occurred during the sampled period.
The probability is estimated by the actual occurrence of events over the sampled period.
Is there a better method?

 

[rhino]

Interesting article. Prepping is a responsible action indeed. I'm going to prep and continue prepping regardless of what statistics say. I really dislike the use of statistics here without better modeling (especially in the United States where the sample size is 2!). If you think it's right to prep, PREP (and you should)! See below for why I dislike simple models.

Olympic 100m Dash Scenario
If you examine times over the years, there's been a overall downward trend. If you calculate a line to fit this trend, you get a very reasonable correlation coefficient (0.9153). It could help us see what times to expect in the next few years, but it also predicts that in the year 3349, it will take an Olympic runner 0.0 seconds to run the 100m dash. We know that it could NEVER take 0.0 seconds for a 100m dash. At some point, the time will plateau because human beings can only run so fast.

Your linear model works okay for that region of the data (what is available), but we know a higher order curve is a better approximation. As you note, there is some (as yet unknown) limit to human speed that the curve will asymptotically approach as time grows large. What we've seen (in terms of performance) over the last 50 years is almost all the result of performance-enhancing drugs and training methods. Soon the boost those provided will wane.

 

[BehindBlueI's]

Seems to me the sample size is the number of years sampled - 340.
Two events occurred during the sampled period.
The probability is estimated by the actual occurrence of events over the sampled period.
Is there a better method?

Social upheaval isn't rain fall, and the events that precipitated his two aren't equally likely to be repeated in any given time frame. It's math, but it's nonsense.

 

[Leadeye]

I would be interested in figuring the numbers on electrical failure from weather, it's the main thing I prep for.

 

[jedi]

Social upheaval isn't rain fall, and the events that precipitated his two aren't equally likely to be repeated in any given time frame. It's math, but it's nonsense.

dont worry i'll buy another of ammo and while im at it ill buy a 2nd one that math wise would have been for you.