Tag: Statistics

No One Is Really Average

Even though I was born in Perth, Western Australia, I have lived in the UK for so long, my accent is now 60 to 80 percent British. While I enjoy sports, I’m not a super-fan of any of them, and it has been a very long time since I’ve applied a prawn to a barbecue. I’m not a typical Australian. But then again, no one is.

After the 2011 census, the Australian Bureau of Statistics published who the average Australian was: a thirty-seven-year-old woman who, among other things, “lives with her husband and two children (a boy and a girl aged nine and six) in a house with three bedrooms and two cars in a suburb of one of Australia’s capital cities.” And then they discovered that she does not exist. They scoured all the records and no one person matched all the criteria to be truly average. As they rightly pointed out:

While the description of the average Australian may sound quite typical, the fact that no one meets all these criteria shows that the notion of the “average” masks considerable (and growing) diversity in Australia. – Australian Bureau of Statistics

…
Having unmasked one Mr. Average, I was prepared to make amends and find a replacement. I contacted the Australian Bureau of Statistics (ABS) to see if it was possible to find someone with the reduced criteria the newspaper used, instead of the full average Australian range of statistics. The fine people at ABS found my request interesting enough to dig through the data for me. Expanding the population considered from West Australia to the whole country subtly changed the averages: Mr. Average is now a woman with one fewer bedrooms in her house. They estimated that, for the loosest definition of average (using only a few main statistics), there would only be “roughly four hundred” matching people out of Australia’s then population of 23,401,892. So there you have it: 99.9983 percent of the Australian population is not average. I’m in pretty good company after all.

Humble Pi: When Math Goes Wrong in the Real World
Matt Parker

Recommended book

Some Random Facts

Over the past decade, California has added a little over three times as many people as housing units, driving its median home price over $800,000, which is more than twice the national figure.

Legislators Find Way to Let U.C. Berkeley Increase Its Enrollment

The richest 20 percent of people worldwide take 80 percent of all flights, according to estimates by the International Council on Clean Transportation.

Nations Agree to Curb Emissions From Flying by 2050

Since there is only one active official cemetery in Manhattan, the borough’s most popular final resting place may be Central Park — a legal site for the scattering of human ashes.

Where the Bodies Are Buried

Nearly half of all millennials have tattoos, compared with 13 percent of the baby boomer generation, according to a 2015 survey by the Harris Poll.

A 10-Year-Old Got a Tattoo. His Mother Was Arrested.

71 of Our Favorite Facts of 2022
Each day, Times Insider editors scour the newspaper for the most interesting facts to appear in articles. Here are facts that surprised, enlightened or entertained us this year.

Unnderrated Statistical Methods


[D] What is in your opinion an underrated Statistical method that should be used more often? from statistics

oose_rajamaeki
Plotting the data and inspecting it visually. Should be done every time if possible before doing any analyses.

Wu_Fan
Yeah fam. Visualise it. Not visualising is like a doctor who doesn’t read your notes.

HoosierTrip
LCA, LPA, and LTA are all underutilized. I think the perception is that they’re no different than cluster analysis, so why not use the easier method (like k means cluster analysis). I’ve seen so many people conflate IRT and CFA with them as well. I think a general lack of understanding about the approach is definitely a contributing factor.

IllmaticGOAT
Thinking about and modeling the generative process of your data.

Lewba
coarsened exact matching for causal inference.

Alkanste
Came to see this

USA 2000 vs 2019 – a few numbers

Population
The population of the U.S. on April 1, 2000 was 281,421,906
https://www.census.gov/main/www/cen2000.html

The nation’s population was 328,239,523 in 2019, growing by 0.5% between 2018 and 2019, or 1,552,022 people. 
https://www.census.gov/newsroom/press-releases/2019/popest-nation.html

Labor force participation rate
January 2000 – 67.3
January 2019 – 63.2
https://data.bls.gov/pdq/SurveyOutputServlet

Housing units (thousands of units)
April 1, 2000 – 116,047 
October 1, 2019 – 140,074 
https://fred.stlouisfed.org/series/ETOTALUSQ176N

Minimum Wage
2000 – $5.15
2019 – $7.25
https://www.dol.gov/agencies/whd/minimum-wage/history/chart

Federal Debt: Total Public Debt as Percent of Gross Domestic Product
Q1 2000 – 57.72
Q1 2019 – 104.40
https://fred.stlouisfed.org/series/GFDEGDQ188S

Tabulating Crime, Difficulties With

The first problem with understanding crime is that measuring it is harder than it sounds. The Department of Justice approaches the problem in two ways. The F.B.I.’s Uniform Crime Reporting Program, or U.C.R., solicits data from about twenty thousand law-enforcement agencies around the country. Simultaneously, the Bureau of Justice Statistics’ National Crime Victimization Survey, or N.C.V.S., interviews about a hundred and fifty thousand nationally representative citizens, asking them whether they have been victims of a crime.

Both datasets have problems. An obvious one is that there’s no consensus about what counts as criminal activity. In some jurisdictions, only offenses worthy of incarceration are considered crimes. In others, fined infractions also count. (Is speeding a crime? What about manspreading, for which one can be fined seventy-five dollars in Los Angeles?) Because the U.C.R. draws its data from investigators, and the N.C.V.S. relies on victims, they can present starkly different pictures of crime. According to the U.C.R., the incidence of rape nearly doubled from 1973 to 1990. The N.C.V.S., by contrast, shows that it declined by around forty per cent during the same period. Researchers at Vanderbilt University looked into the discrepancy; they found that the upward trend in the U.C.R. data correlated with upticks in the number of female police officers, and with the advent of rape crisis centers and reformed investigative styles. It could be, in short, that a modernized approach to the policing of rape drastically increased the frequency with which it was reported while reducing its incidence. But coherent stories like these only sometimes emerge from the conflicting data.

Matthew Hutson, New Yorker

Efficient Market Hypothesis

The efficient-market hypothesis (EMH) is a theory in financial economics that states that asset prices fully reflect all available information. A direct implication is that it is impossible to “beat the market” consistently on a risk-adjusted basis since market prices should only react to new information or changes in discount rates (the latter may be predictable or unpredictable).

The EMH was developed by Professor Eugene Fama who argued that stocks always trade at their fair value, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by chance or by purchasing riskier investments.[1] His 2012 study with Kenneth French confirmed this view, showing that the distribution of abnormal returns of US mutual funds is very similar to what would be expected if no fund managers had any skill—a necessary condition for the EMH to hold.[2]

via Wikipedia