September 2014
Intermediate to advanced
236 pages
4h 17m
Japanese
Content preview from Think Bayes ―プログラマのためのベイズ統計入門
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7.7
議論
■
83
し合わせたものとなる。
p_tie = diff.Prob(0)
p_overtime = thinkbayes.PmfProbLess(time_dist1, time_dist2)
p_win = diff.ProbGreater(0) + p_tie * p_overtime
ブルーインズが、次の試合に勝つすべての機会は
55%
となる。
シリーズで勝つためには、ブルーインズは次の
2
試合で勝つか、次の
2
試合で
1
勝
1
敗して第
3
試合で勝てばよい。再度、全体確率を次のように計算できる。
# win the next two
p_series = p_win**2
# split the next two, win the third
p_series += 2 * p_win * (1-p_win) * p_win
ブルーインズがシリーズで勝つ確率は
57%
。そして
2011
年には、その通り勝ったの
だ。
7.7
議論
いつものように、本章の分析は、モデル化の決定に基づいており、そのモデル化は
ほとんど常に反復プロセスとなる。一般に、単純でありながら近似的な解を生み出すモ
デルから始めて、誤差の原因になりそうなモデルを探し出し、改善の機会を求めていく。
今回の例では、以下のような選択肢を私は考えた。
●
各チームの一試合当たりの平均ゴール数に基づいた事前確率を選んだ。この統計
は、すべての対戦相手に対する平均だった。したがって、特定の対戦相手につい
ては、変動がより大きくなる可能性がある。例え
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.