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Just another my weblog
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統計学の分類 | thinklog
https://thinklog.wordpress.com/2009/05/05/memo1
Just another my weblog. Laquo; Grammar in Use Intermediate. 縮約にはおおまかに 1.グラフ化する 2.1つの数字(統計量)で特徴を代表させる 方法があります。 詳細 – wikipedia:統計学. This entry was posted on 2009/05/05 at 09:39:04 and is filed under thinklog. You can follow any responses to this entry through the RSS 2.0. Feed You can leave a response. From your own site. WordPress.com を使って Web サイトを作成する.
簡単な区間推定 | thinklog
https://thinklog.wordpress.com/2009/05/05/memo5
Just another my weblog. 少し乱暴な表現ですが、 ある不確実な現象が正規分布に従う場合、”幅を持った未来予測”が可能 となります。 標準正規分布の性質として、 平均0から 1の範囲内に全体の68.26%が集中する というものがありました。 ということは、 次に出現する値は-1 1の間である と予言すれば、その予言は68.26%の確率で的中するということになります。 同様に、 次に出現する値は-2.5 2.5である と予言すれば、その予言は98.76%(! の確率で的中することになり、 次に出現する値は-2.58 2.58である と予言すれば、その予言は99.02%(! ちなみに、平均値μ, 標準偏差σの一般正規分布の99.02%予言的中区間は. Μ – 2.58σ以上, μ 2.58σ以下. Z = (x – μ) / σ. 258 (x – μ) / σ 2.58. 例1) ある国の成人の身長の平均は172cmであり、S.D.は8cmです。 258 (x – 172) / 8 2.58. 258 (20 – μ) / 3 2.58. From your own site.
正規分布 | thinklog
https://thinklog.wordpress.com/2009/05/05/memo4
Just another my weblog. 1 -1(平均からS.D. 1個以内)の範囲のデータの相対度数は0.6826(約68%). 2 -2(平均からS.D. 2個以内)の範囲のデータの相対度数は0.9544(約95%). 25 -25(平均からS.D. 2.5個以内)の範囲のデータの相対度数は0.9876(約99%). Μ σ μ-σ(平均からS.D. 1個以内)の範囲のデータの相対度数は0.6826(約68%). Μ 2σ μ-2σ(平均からS.D. 2個以内)の範囲のデータの相対度数は0.9544(約95%). Μ 25σ μ-2.5σ(平均からS.D. 2.5個以内)の範囲のデータの相対度数は0.9876(約99%). Z = (x – μ) / σ. 詳細 – wikipedia:正規分布. This entry was posted on 2009/05/05 at 16:00:36 and is filed under thinklog. You can follow any responses to this entry through the RSS 2.0.
Grammar in Use Intermediate | thinklog
https://thinklog.wordpress.com/2009/04/25/grammar-in-use-intermediate
Just another my weblog. Grammar in Use Intermediate. Grammar in Use Intermediate: Self-Study Reference and Practice for Students of North American English : With Answers. Cambridge Univ Pr (T) (2009-03-31), 4,111円. Details at Amazon.co.jp. This entry was posted on 2009/04/25 at 21:41:40 and is filed under readlog. You can follow any responses to this entry through the RSS 2.0. Feed You can leave a response. From your own site. WordPress.com を使って Web サイトを作成する.
カイ二乗分布 | thinklog
https://thinklog.wordpress.com/2009/05/06/カイ二乗分布
Just another my weblog. 標準正規母集団からのn個の標本x1, x2, …, xnに対して、. Z = (x – μ) / σ. X1 – μ) / σ, (x2 – μ) / σ, …, (xn – μ) / σ,. V = (80 – 76) 2 / σ 2 (80 – 85) 2 / σ 2 (80 – 83) 2 / σ 2 = 50 / σ 2. 007172 50 / σ 2 12.84. カイ二乗分布表より有意水準0.995: 0.07172, 有意水準0.005: 12.84. よって母分散σ 2は、3.894以上697.16以下と99.00%の精度で区間推定されます。 両者ともに統計量Wは自由度(n – 1)のカイ二乗分布に従います。 例) 東京都の高校1年生の物理のテスト結果をサンプル抽出したところ、点数はそれぞれ、76点, 85点, 82点, 80点, 74点でした。 標本平均 x = (76 85 82 80 74) / 5 = 79.4. 標本分散 s 2 = 省略 = 15.84. 02070 79.2 / σ 2 14.86.
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thinklog | Just another my weblog
Just another my weblog. 正規母集団からn個の標本x1, x2, …, xnを観測したとき、標本平均x は、. 例) 東京都の高校1年生の物理のテスト結果をサンプル抽出したところ、点数はそれぞれ、76点, 85点, 82点, 80点, 74点でした。 標本平均 x = (76 85 82 80 74) / 5 = 79.4. 標本分散 s 2 = 省略 = 15.84. 標本標準偏差 s = sqrt(15.84) = 3.98. 自由度5-1=4のt分布の99.00%的中区間は有意水準0.005: 4.604より、. 4604 統計量T 4.604. 4604 (79.4 – μ) * sqrt(4) / 3.98 4.604. 詳細 – wikipedia:t分布. 標準正規母集団からのn個の標本x1, x2, …, xnに対して、. Z = (x – μ) / σ. X1 – μ) / σ, (x2 – μ) / σ, …, (xn – μ) / σ,. 007172 50 / σ 2 12.84. 両者ともに統計量Wは自由度(n – 1)のカイ二乗分布に従います。
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