August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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144
10 章 線形最小二乗法
図
10-3
inter
と
slope
の標本誤差に起因する適合線での変動を示す
50
％と
90
％との信頼区間
10.5
適合度
線形モデルの品質、すなわち、適合度（
goodness of fit
）を測定するには複数の方
法があります。最も単純なのは、残差の標準偏差です。
予測するのに線形モデルを使っているなら、
Std(res)
が予測の平均二乗誤差の平
方根（
RMSE
）になります。例えば、出生時体重を予測するために母親の体重を使う
なら、予測の
RMSE
は、
1.40
ポンドです。
母親の年齢を知らずに出生時体重を予測するなら、その予測の
RMSE
は、
Std(ys)
なので、
1.41
ポンドです。したがって、母親の年齢を知ることが予測を大きく改善
するわけではありません。
適合度を測るもう
1
つの方法は、決定係数（
coefficient of determination
）
R
2
†
で
次のコードで求めます。
def CoefDetermination(ys, res):
return 1 - Var(res) / Var(ys)
Var(res)
は、このモデルを使った予測の
MSE
（平均二乗誤差）で、
Var(ys)
はモ
†
通常、
R
2
は英語では「
R square
」と読む。
年齢（歳）
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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.
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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.