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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150
10 章 線形最小二乗法
10.8
演習問題
†
演習問題
10-1
BRFSS
のデータを用いて、
log
（体重）対身長の線形最小二乗適合を計算しなさい。
変数の
1
つが対数変換された、このようなモデルに対する推定パラメータをどのよう
にうまく表すとよいか。誰かの体重を推量しようとするとき、身長を知ることがどれ
だけ役立つだろうか。
NFSG
同様
BRFSS
もいくつかのグループでオーバーサンプリングしており、各回
答者に標本化重みを与えている。
BRFSS
データでは、この重みの変数名は、
totalwt
である。重みのある場合とない場合とでリサンプリングを用いて、
BRFSS
の回答者
の平均身長、平均の標準誤差、
90
％信頼区間を推定しなさい。正しい重み付けは推
定にどの程度影響しただろうか。
10.9
用語集
線形適合（
linear fit
）
変数間の関係をモデル化する直線。
最小二乗適合（
least squares fit
）
残差の二乗の和を最小にするようなデータセットのモデル。
残差（
residual
）
実際の値とモデルとの偏差。
適合度（
goodness of fit
）
モデルがデータにどれだけよく適合しているかの尺度。
決定係数（
coefficient of determination
）
適合度を量化するための統計量。
標本化重み（
sampling weight
）
標本が母集団のどの部分を代表するかを示す、標本の観察に伴う値。
†
この問題の解答は
chap10soln.ipynb
にある。
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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.