Monday Book Review: Wait Till Next Year April 6, 2010Posted by dataduchess in Book Reviews.
Tags: baseball, book review, books, Doris Kearns Goodwin, memoirs, spring
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Springtime is a wonderful time of year for lots of reasons, but one of the best things about Spring is the return of BASEBALL! In honor of the opening of baseball season this week, I’m reviewing a book I read a number of years ago, but think about each year at this time. Wait Till Next Year, by Doris Kearns Goodwin, is a memoir focused on a young girl’s life growing up in Brooklyn in the 1950’s, her relationships with her friends, mother and especially her father with whom she shared a special bond of love for the Brooklyn Dodgers.
Ms. Goodwin is a presidential historian, author of numerous accounts of historical events, and is a frequent guest on a variety of political and current event news and commentary programs. Her father taught her how to score a game when she was only 6, and she can still recount games she heard on the radio that summer. The tale focuses on a time when even Brooklyn was a small town, and families and communities were brought together around radios or new-fangled televisions to watch and hear about current events – things that were changing and shaping our country in the tumultuous post-World War II era. But the best memories of this girl’s childhood center on her obsession with the Brooklyn Dodgers, (even forsaking all other teams and players, including greats like Mickey Mantle who dared to play for the Yankees!) and the whole neighborhood’s hopes that the Dodgers would win the pennant, maybe next year.
The memoir is incredibly well-written, and I highly recommend it to anyone interested in 1950’s suburbia, family relationships, father-daughter relationships, and most of all, baseball.
Numbers Don’t Lie, or Do They? Simpson’s Paradox Explains December 2, 2009Posted by dataduchess in Uncategorized.
Tags: baseball, data, graphs, statistics, unemployment, WSJ
The Numbers Guy over at The Wall Street Journal had a really interesting article today. He explains a concept called Simpson’s Paradox, which essentially says aggregated data is sometimes misleading. For example,
… in both 1995 and 1996, Derek Jeter of the New York Yankees had a lower batting average for each season than David Justice, then of the Atlanta Braves.
Combining the two years, however, Mr. Jeter had a better average. The paradox resulted from the fact that in 1995 Mr. Jeter had only 48 at-bats with a .250 average while Mr. Justice had more at-bats (411) with a .253 average. The following year, Mr. Jeter had 582 at-bats with a .314 average while Mr. Justice had only 140 at-bats with a higher average of .321, pushing the two-year average in Mr. Jeter’s favor.
Other examples of the paradox can be found in all types of data, from air travel delay statistics and medical procedure success statistics, to education and unemployment data.
In the graph below, you can see that although the unemployment rates for each of the separate groups are higher now than they were in 1983, because the size of the group with the lower rate is so much bigger, the overall unemployment rate is lower than it was in 1983.
Confused? Don’t worry about it. The lesson here is to be wary of “hard data,” and remember that statistics can still be spun to fit any argument. This WSJ graph shows that unemployment is both better than in 1983, and worse. It only depends on which point you want to make.
Yankees in 6? October 28, 2009Posted by dataduchess in Uncategorized.
Tags: baseball, data, statistics
We’re in the home stretch here of baseball season with Game One of the World Series later tonight, if it ever stops raining in the Northeast. Baseball is a great sport for fans of physics, data and statistics. WhatIfSports is a site affiliated with Fox Sports on MSN that runs simulations of every and any game you can think of, in all different sports, past and present. They ran a simulation of this World Series, between the Yankees and Phillies, 10,000 times – and Yankees won 72.3% of the time. Those are some good odds.