Friday, November 30, 2018

North Dakota #1, GDP Per Capita, 2014 -- Compare To Europe -- The Market, Energy, And Political Page, T+24 -- November 30, 2018

Amazing graphic / link from a reader. The data is from 2014, but probably not a lot different than 2018: so, apples to apples.
AEI’s Perry writes: “Most European countries (including Germany, Sweden, Denmark and Belgium) if they joined the US, would rank among the poorest one-third of US states on a per-capita GDP basis, and the UK, France, Japan and New Zealand would all rank among America’s very poorest states, below No. 47 West Virginia, and not too far above No. 50 Mississippi. Countries like Italy, S. Korea, Spain, Portugal and Greece would each rank below Mississippi as the poorest states in the country.”
Here is the chart:
But look at this. from wiki:
North Dakota is the fastest-growing state in U.S. by GDP. Its growth rate is about 8.3%. The economy of North Dakota had a gross domestic product of $36.8 billion in 2013. The per capita income in 2013 was $50,899, ranked 16th in the nation. The three-year median household income from 2002–2004 was $39,594, ranking 37th in the U.S.
Okay, so in 2013, North Dakota's GDP per capita was less than $51,000. One year later, North Dakota's GDP per capita was almost $73,000.

Based on the Federal Reserve, North Dakota GDP per capita:
  • 2018: $72,847.
  • 2014, the all-time peak: $78,808
Most interesting data points on the chart above:
  • California at #10 much higher than one might expect;
  • Idaho, coming in just ahead of Mississippi (dead last) -- but both besting South Korea, and Idaho; even besting Japan and New Zealand
The most amazing thing about all of this: I doubt most NoDaks know how significant this is.

The Book Page

Seriously, seriously, seriously. For serious book readers with reading abilities greater than that of an eighth grader, I seriously cannot recommend Ben Orlin's Math With Bad Drawings: Illuminating The Ideas That Shape Our Reality, c. 2018.

It's a fun book to read, but doesn't break any new ground. It reads like a blog and the "bad drawings" are huge distractions.

My hunch is that this is the kind of book middle school (and probably high school math teachers, unfortunately) will recommend to their students.

I find myself going back to the book often throughout the day to read snippets -- it is entertaining but unrewarding.

The ultimate tic-tac-toe game might be worth the price of the book; some sections on probability are reasonably good; and, the author's discussion of the US electoral college is nice.

Speaking of the US electoral college: thank goodness our Founding Fathers understood the importance of protecting our population-challenged states: each state gets two US senators; and, for the most part, states are still mandating that all electors align with the state's popular vote.

These is, frustratingly enough, no index. There are end notes at the end of the book which are very, very rewarding.

There's probably more to the book than I realize -- if so, very subtle. Sublime? I don't think so.

I'm glad it was a freebie. I'll keep it around for a year and then donate it to a school.

From Chapter 17, "The Last .400 Hitter," p. 223:
As baseball came of age in the 1850s, a player batted until he either hit the ball into play, or swung and missed three times. With patient enough batters, the game flowed like cold molasses. Thus, in 1858 (before the US Civil War), "called strikes" were born.

If a player let a juicy pitch sail past, then it was treated as equivalent to swinging and missing.

But now the pendulum swung too far; cautious pitchers refused to throw anything hittable. The solution, introduced in 1863 (during the middle of the US Civil War), was to also call "balls": pitches deemed too far off target for the batter to hit. Enough such "balls" would grant the batter a free walk to first base.

Walks stumped [cricket fans]. Cricket's closest equivalent is a "wide," generally viewed as a mistake by the thrower. So batting average (BA) ignored walks, as if the at-bats had never occurred. Walks weren't deemed an official statistic until 1910.

Today, the most skilled and patient hitters walk 18% or 195 of the time; their reckless, swing-happy peers, just 2% or 3%. Hence ... a convoluted [mathematical] expression for what we now call "on-base percentage," or OBP. It's your rate of getting on base, via either hits or walks -- in ther words, your rate of not making an out.

Which statistic better predicts the number of runs a team will score: BA or OBP? Running the correlations for 2017, BA is pretty strong, with a coefficent of0.73. But OBP is outstanding, with a coefficient of 0.91.

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