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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148
10 章 線形最小二乗法
いずれにせよパラメータの標本分布を計算するのが普通なので、
2
番目のほうが容
易です。それに、標本サイズが小さくて、なおかつ、残差の分布が偏っていない限り
は、そちらが良い近似になります。
p
値は、精密である必要はないので、通常はそれ
で十分です。
標本分布を用いて傾きの
p
値を推定するコードは次のようになります。
inters, slopes = SamplingDistributions(live, iters=1001)
slope_cdf = thinkstats2.Cdf(slopes)
pvalue = slope_cdf[0]
再び、
p
＜
0.001
になります。
10.7
重み付けリサンプリング
ここまでは、
NSFG
のデータを代表標本として扱ってきましたが、「
1.2
全米世帯
動向調査」で述べたように、実は代表標本ではありません。この調査では、いくつか
のグループについて意図的にオーバーサンプリングすることにより、統計的に有意な
結果が得られる機会を改善しています。すなわち、これらのグループを含めた検定力
を改善しています。
この調査設計は多目的に有用なことですが、それは、標本化過程を検討しないまま
では母集団の値の推定にこの標本を使うわけにはいかないことを意味します。
各回答者に対して、
NSFG
データには、
finalwgt
という変数があり、回答者が
母集団の中のどれだけの人数を代表するかを示しています。この値は、標本化重み
（
sampling weight
）とか、単に「重み」と呼ばれます。 ...
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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.