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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161
161
11.6 ロジスティック回帰
race
の推定パラメータは、特に、収入を制御したために、予期していたよりも大
きくなっています。符号化は、黒人が
1
、白人が
2
、その他が
3
です。黒人の母親の
新生児の体重は、他の人種の体重よりも
0.27
〜
0.36
ポンド軽いです。
すでに見たように、男子は約
0.3
ポンド重く、双子などの多胎児は、
1.4
ポンド軽
くなっています。
家を持っている人には、収入を制御しているにもかかわらず、約
0.12
ポンド重い
新生児が生まれます。母親の年齢のパラメータは、「
11.2
重回帰」で見たよりも小
さく、他の変数のいくつかが、おそらく
paydu
と
totincr
を含めて相関していること
を示唆します。
すべての変数が、非常に低い
p
値を持つものも含めて、統計的に有意ですが、
R
2
は
0.06
しかなくて、まだかなり小さな値です。モデルを使わなくても
RMSE
が
1.27
ポンドで、モデルを使うと
1.23
に減少します。したがって、賭けに勝つ確率はそれ
ほど増えません。すみませんね。
11.6
ロジスティック回帰
先ほどの例では、説明変数のいくつかは数値変数で、いくつかはカテゴリ変数（論
理型も含めて）でしたが、従属変数は、常に数値でした。
線形回帰は、他の種類の従属変数を扱えるよう一般化できます。従属変数が論理型
なら、一般化モデルはロジスティック回帰（
logistic regression
）と呼ばれます。従
属変数が整数カウントデータなら、ポワソン回帰（
Poisson regression
）と呼ばれます。 ...
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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.
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.