equation-012

equation-012

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

\( y = a + bx \)

\( x = c + dy \)

\( y = a_{1}x_{1} + a_{2}x_{2} + \cdots +a_{n}x_{n} + b \)

\(  y = a + bx + cx^2 \) 

 

\( ( x_{ i } – \bar{ x } )^2 \)

\( ( y_{ i } – \bar{ y } )^2 \)

\( ( x_{ i } – \bar{ x } )( y_{ i } – \bar{ y } ) \)

\( b = \displaystyle\frac{ S_{(xy)} }{ S_{(xx)} } = \displaystyle\frac{ \sum_{i=1}^{n} ( x_{ i } – \bar{ x } )( y_{ i } – \bar{ y } ) }{ \sum_{i=1}^{n} ( x_{ i } – \bar{ x } )^2 } \)

\( a = \bar{ y } – b \bar{ x } \)

 

\( \bar{x} と \bar{y} の計算 \)

\( \bar{x} \)     \( \bar{y} \)

\( \bar{x} = 35.93 \)    \( \bar{y} = 14.05 \)

\( S_{(xx)} と S_{(xy)} の計算 \)

\( S_{(xx)} = 231.907 \)    \( S_{(xy)} = -197.122 \)   \( S_{(yy)} = 177.067 \)

\( b = \displaystyle\frac{ S_{(xy)} }{ S_{(xx)} } = \displaystyle\frac{ -197.122 }{ 231.907 } = -0.850 \)

\( a = \bar{y} – b \bar{x} = 14.05 – (-0.850) \times 35.93 = 44.597 \)

\( y = 44.597 – 0.850 x \)

 

\( y = \beta_{0} + \beta_{1} x + \varepsilon \)

\( \varepsilon \)

\( E( \varepsilon ) = 0 \)

\( V( \varepsilon ) = \sigma_{ \varepsilon }^2 \)

 

\( y = a + bx \)

\( x \)  \( y \)   \( x_{i} \)   \( y_{i} \)

\( y_{i} = a + bx_{i} \)

\( ( x_{i}, y_{i} ) \)   \( ( a + bx_{i} ) \)   \( y_{i} – ( a + bx_{i} ) \)

\( 残差 = y_{i} – ( a + bx_{i} ) \)

\( Q = 残差^2 の合計 = \sum_{i=1}^{n} e_{i}^2 = \sum_{i=1}^{n} | y_{i} – ( a + bx_{i})|^2 \)

\( x  = c + dy \)

\( y = – \displaystyle\frac{c}{d} + \displaystyle\frac{1}{d}x \)

\( y = 44.597 – 0.850 x \)

 

\( d = \displaystyle\frac{ S_{(xy)} }{ S_{(yy)} } = \displaystyle\frac{ -197.122 }{ 177.067 } = -1.113 \)

\( c = \bar{x} – b \bar{y} = 35.93 – (-1.113) \times 14.05 = 51.578 \)

\( x = 51.578 – 1.113 x \)

\( y = 46.331 – 0.898 x \)

 

\( 寄与率 = (相関係数)^2 = r^2 \)

\( 寄与率 = \displaystyle\frac{ S_{ (xy) }^2 }{ S_{ (xx) }S_{ (yy) }} \)

\( 寄与率 = \displaystyle\frac{ S_{ (xy) }^2 }{ S_{ (xx)}S_{ (yy) }} = \displaystyle\frac{ (-197.122)^2 }{ 231.907 \times 177.067 } = 0.9463 \)

 

\( S_{R} = \displaystyle\frac{ S_{ (xy) }^2 }{ S_{ (xx) }} = \displaystyle\frac{ (-197.122 )^2 }{ 231.907 } = 167.555 \)

\( S_{T} = S_{ (yy) } = 177.067 \)

\( S_{E} = S_{T} – S_{R } = 177.067 – 167.555 = 9.513 \)

\( \phi_{R} = 1 \)

\( \phi_{T} = n – 1 = 19 – 1 =18 \)

\( \phi_{E} = \phi_{T} – \phi_{R} = 18 – 1 = 17 \)

\( V_{R} = \displaystyle\frac{S_{R}}{\phi_{R}} = \displaystyle\frac{ 167.555 }{ 1 } = 167.555 \)

\( V_{E} = \displaystyle\frac{S_{E}}{\phi_{E}} = \displaystyle\frac{ 9.513 }{ 17 } = 0.560 \)

\( 分散比 = \displaystyle\frac{V_{R}}{V_{E}} = \displaystyle\frac{ 167.555 }{ 0.560 } = 299.433 \)

\( F(1,17:0.05) = 4.45 \)

\( 分散比 = \displaystyle\frac{V_{R}}{V_{E}} = 299.433 >  F(\phi_{R}, \phi_{E}:0.05) = F(1,17:0.05) = 4.45 \)

 

 

 

\( \mu = 0 \)   \( \sigma^2 = 1 \)   \( N( 0 , 1^2 ) \) 

\( Pr( X = x ) \)    \( Pr( X = x ) = {}_n \mathrm{ C }_x P^{ x } ( 1 – P)^{ n – x } = \displaystyle\frac{ n! }{ x! ( n – x )! } P^{ x } ( 1 – P )^{ n – x } \)

\( {}_n \mathrm{ C }_x \)   \( {}_n \mathrm{ C }_x = \displaystyle\frac{ n! }{ x! ( n – x )! } \)

\( E( X ) = nP \)    \( D( X ) = \sqrt{ n P ( 1 – P ) } \) 

\( p = X/n \)   \( E( p ) = P \)   \( D( p ) = \sqrt{ \displaystyle\frac{ P ( 1 -P ) }{ n } } \)

\( nP \geq 5 ,   n ( 1-P ) \geq 5 \)

\( np = \lambda \)

\( Pr( X = k ) = \displaystyle\frac{ e^{ – \lambda } \lambda ^k }{ k! }   ( k = 0, 1, 2, \cdots  ) \)

\( E( k ) = \lambda \)   \( D( k ) = \sqrt{ \lambda } \)

 

\( Pr( u \geq K_{ p } ) = P \)

\( U = \displaystyle\frac{ X  – \mu }{ \sigma } \)

\( N( 20, 4^2 ) \)

\( U = \displaystyle\frac{ 24  – 20 }{ 4 } = 1 \)

\( N( 100, 30^2 ) \)

\( U = \displaystyle\frac{ 53.5  – 100 }{ 30 } = 1.55 \)

 

\( S(xy) = \displaystyle \sum_{ i=1 }^n ( x_{ i } – \bar{ x })( y_{ i } – \bar{ y }) \)

\( S(xy) = \displaystyle \sum_{ i=1 }^n  x_{ i }y_{ i } – n \sum_{ i=1 }^n x_{ i } \sum_{ i=1 }^n y_{ i } \)

\( S(xy) = \displaystyle \sum_{ i=1 }^n  x_{ i }y_{ i } – \displaystyle\frac{\sum_{ i=1 }^n x_{ i } \sum_{ i=1 }^n y_{ i } }{ n } \)

\( S(xy) = – \displaystyle\frac{\sum_{ i=1 }^n x_{ i } \sum_{ i=1 }^n y_{ i } }{ n } \)

 

 

\( F( \phi_{ R }, \phi_{ E } : 0.05 ) \)

\( F(\phi_{R}, \phi_{E}:0.05) \)

 

 

\( CL = \bar{ X } \)    \( UCL = \bar{ X } + 2.660 \bar{ Rs } \)    \( LCL = \bar{X} – 2.660 \bar{ Rs } \)

\( CL = \bar{ Rs } \)    \( UCL = 3.267 \bar{ Rs } \) 

\( CL = \bar{ s } \)    \( UCL = B_{ 4 } \bar{ s } \)    \( LCL = B_{ 3 } \bar{ s } \)  

 

\( CL = \bar{ c } \)    \( UCL = \bar{ c } + 3 \sqrt{ \bar{ c }} \)    \( LCL = \bar{ c } – 3 \sqrt{ \bar{ c }} \)

\( CL = \bar{ u } \)  \( UCL = \bar{ u } + 3 \sqrt{ \displaystyle\frac{ \bar{ u }}{ n} } \) \( LCL = \bar{ u } – 3 \sqrt{ \displaystyle\frac{ \bar{ u }}{ n} } \)