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Y = a + bX

回帰直線の有意性を検定する 分散分析の考え方. Y = a + bX. ●. 観察値　 (Xi, Yi). Yi. ●. ●. ●. Se. 推定値　 (Xi, Yei). Yei. ●. Syy. ●. Yei = a + bXi. SR. ●. ●. 平均値　 (Xm, Ym). Ym. ●. ●. ●. 回帰による変動（ SR ） = Syy - Se. ●. ●. ●. ●. ●. 全体の変動：　 Syy 残差：　 Se. ●. ●. Xm. Xi. 観察値　 (Xi, Yi j ). Yi j. Se.

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Y = a + bX

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  1. 回帰直線の有意性を検定する 分散分析の考え方 Y = a + bX ● 観察値　(Xi, Yi) Yi ● ● ● Se 推定値　(Xi, Yei) Yei ● Syy ● Yei = a + bXi SR ● ● 平均値　(Xm, Ym) Ym ● ● ● 回帰による変動（SR）= Syy - Se ● ● ● ● ● 全体の変動：　Syy 残差：　 Se ● ● Xm Xi

  2. 観察値　(Xi, Yij) Yij Se 推定値　(Xi, Yei) Syy Yei ● Yei = a + bXi SR 平均値　(Xm, Ym) Ym ● SR = Syy - Se Xm Xi 回帰直線の有意性を検定する分散分析の考え方（２） Y = a + bX ● ● ● ● Sw 級別平均値　(Xi, Ymi) ● ● ● ● Sr Sb ● ● ● ● ● ● ● 級内変動：　Sw ● ● 級間変動：　Sb ● ● Syy = Sw + Sb 残りの変動：　Sr ● ● Se = Sw + Sr ●

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