#statsitics

*Not including 1.6 - The Hockey Prince, the phantom update 4.19, or Hockey Shit with Ransom & Holster

Name: total main comic appearances (appearances per year)

Bitty: 90 (Y1- 21, Y2- 19, Y3- 24, Y4- 26)

Jack: 75 (Y1- 15, Y2- 18, Y3- 23, Y4- 19)

Shitty: 46 (Y1- 15, Y2- 12, Y3- 11, Y4- 8)

Lardo: 37 (Y1- 5, Y2- 10, Y3- 15, Y4- 7)

Ransom: 47 (Y1- 13, Y2- 14, Y3- 14, Y4- 6)

Holster: 48 (Y1- 13, Y2- 15, Y3- 14, Y4- 6)

Chowder: 37 (Y1- 1, Y2- 12, Y3- 9, Y4- 15)

Dex: 31 (Y1- 1, Y2- 10, Y3- 8, Y4- 12)

Nursey: 30 (Y1- 1, Y2- 9, Y3- 9, Y4-11)

Ford: 10 (Y3- 2, Y4- 8)

Tango: 15 (Y3- 7, Y4- 8)

Whiskey: 12 (Y3- 5, Y4- 7)

Tater: 14 (Y3- 9, Y4- 5)

Kent: 6 (Y2- 3, Y3- 3)

George: 8 (Y2- 2, Y3- 4, Y4- 2)

Suzanne: 16 (Y1- 2, Y2- 1, Y3- 4, Y4- 9)

Coach: 14 (Y3- 2, Y4- 12)

Hops: 10 (Y4- 10)

Bully: 8 (Y4- 8)

Louis: 9 (Y4- 9)

Alicia: 3 (Y1- 1, Y2- 1, Y4- 1)

Why Do England Always Lose on Penalties?

Statistics to win penalty shoot-outs With the World Cup nearly upon us we can look forward to another heroic defeat on penalties by England. England are in fact the worst country of any of the major footballing nations at taking penalties, having won only 1 out of 7 shoot-outs at the Euros and World Cup. In fact of the 35 penalties taken in shoot-outs England have missed 12 – which is a miss rate…

I went to the website of Japan Bureau of Statistics and found the 2015-base Consumer Price Index.

Data source: https://www.e-stat.go.jp/en/stat-search/files?page=1&layout=datalist&toukei=00200573&tstat=000001084976&cycle=0&tclass1=000001085995&tclass2=000001085936&tclass3=000001085996&tclass4=000001085976&stat_infid=000031431703&tclass5val=0

Time: 1970/02 ~ 2021/02

Frequency of data: monthly

Result: Gumbel, type I, distribution

parameters: a = 2.66, b=0.782812

Software source: http://tinyurl.com/goodnessoffit

Property of software: free portable modeling software to test 45 probability distributions and select the optimal one on the criterion of minimum chi-square test statistic.

What I mean by micro-macro is trying to get a better understanding of the world by accessing it on two levels: for one, there’s the micro-level of anecdotes where we get the good feeling of looking at actual, concrete aspects of the world instead of abstract mathematical descriptions. But we combine this with the macro-level to understand how these relatable anecdotes fit into the whole. This dual approach enables us to estimate if a given example represents normalcy (a stand-in for how things “usually” are) or is an outlier and does not allow conclusions for all cases.