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  • 28/10/2014

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    . . . . ... ... ... ...

    2014 5555

    , s2, ( 2 ). (pointestimation) (interval estimation) .

    x

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    , . - , .... . , .

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    (point estimation), , . , , , (intervalestimation), , , , .

    , , . , 25 25 ( 1

    ).

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    X (..) FX (x; ) F(x; ) . {x1, . . . , xn} X n. g(x1, . . . , xn) .

    (estimator) = g(x1, . . . , xn).

    {x1, . . . , xn} n, {x1, . . . , xn} .. {X1, . . . , Xn}, F(x; ). .. {x1, . . . , xn} ( .. {X1, . . . , Xn}) ( ..). ( {x1, . . . , xn}) , ........ = E ( ) 2 = Var( ).

    .. X 2.

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    2

    2

    ; :

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    (unbiased) () ,

    , .

    .. X .

    s2 2

    2

    x

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    , . (consistent) ( )

    . (effective) ,

    (adequate) .

    , s2 2, .

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    .. X , F(x; ) f (x; ), X X . {x1, . . . , xn}. .

    , , , , , .

    , F(x; ) 2. , 2 .

    [a, b], a b 2

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    ( 1, 2) 2, :

    1. s2 2 ,

    2. s2

    ( 1, 2) 2.

    (method ofmoments). : 2 .

    . . . .

    1 25 . 1. s2

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    5.67 2 0.375.

    .. X ( ) N(, 2), X .

    , , , .

    X = xi

    f (xi ; ) ( X P(X = xi)). {x1, . . . , xn} , n (likelihood function)

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    , {x1, . . . , xn} . L(x1, . . . , xn; 1) > L(x1, . . . , xn; 2) 1 2 , 1 2 {x1, . . . , xn}. , L(x1, . . . , xn; ) ( ) log L(x1, . . . , xn; ). (maximum likelihoodestimator)

    2 .. ,

    ( n)

    .

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    . .. n. , . . ..... . . . . . . . [ [ [ [1111, , , , 2] 2] 2] 2] .... , .

    .. X , , = E( ) = . , , n . n . 2

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    ( )

    (standarderror)

    .. =

    , .

    , X .

    . . . . 2 .. X .

    :

    1. .. X N(, 2) (n > 30)

    .. N(, 2/n).

    2. , .. X

    .

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    , .. X .. X1, . . . , Xn .

    N(, 2/n), .. z

    [z/2, z1/2], z 1 1 1 1 ,

    , z/2 z1/2, . /2 1/2 z/2 z/2

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    (z) . z < z/2 z > z1/2 . % . z [z/2, z1/2] 1.

    0 z/2 = z1/2.

    [z/2, z1/2] .

    , 1 .. z z1/2 z1/2 = 1(1/2) .

    = 0.05 [1.96, 1.96] .. z 0.95, z0.975 =

    1(0.975) = 1.96. [ , , . z1/2 z/2 z/2 z/2].

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    [z/2, z1/2] 1 .

    1 (confidence level) (confidence interval) 1.

    :

    1 1 1 1 () () () () ....

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    :

    . . . . 95% 1. 2=0.38.

    , .. , ( ).

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    Q1 Q3.

    .

    .

    X N(, 0.38) N(, 0.38/25), n = 25 .

    :

    1. 1 = 0.95 ( = 0.05).

    2. z0.975= 1(0.975) = 1.96.

    3. ( = 5.67)

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    95% [5.43, 5.91].

    = 5.67 95% .

    2 .. X s2. (n > 30) s2 2

    s2 . .

    n X , .. t

    student t n1

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    . n t z . , 2 s2 ttttn1,1/2n1,1/2n1,1/2n1,1/2 z1/2 student. [ t 1/2 n1. student n1 =24 1 = 0.95.] 1

    ( ). .. z1/2. tn1,1/2 student. s2 = 0.375

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    student, 1 /2 = 0.975 n 1 = 24,

    t24, 0.975 = 2.064

    n student .

    .. X . [ X , .. .] ( ) .

    = X .. X = X .

    . Wilcoxon . ( ).

    x~

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    . :

    2 .. X [ , ..].

    n [ n , , ].

    1 [ , ]. 95%.

    .

    .. X n .

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    .. .. . , n n n n .. .. n. , .. X , .. . ..

    n .. w

    tn1,1/2 n . n n tn1,1/2 z1/2. n

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    . . . . 95% .. student ( ) [5.42, 5.92]. .. w = 5.92 5.42 = 0.50. ( w = 0.25) 25

    2

    2 s2 2

    X2

    n 1

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    X2 . X2 .

    X2 5, 24 50

    1 X2

    X2 : 2 n1,/2 P(

    2

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    X2 n1=24 1 = 0.95.

    2 (1 )% 2

    X2 24

    1 = 0.95.

    . . . . (.1) 2 . ( ) s2=0.375. n1=24 = 0.05 X2 222224, 0.02524, 0.02524, 0.02524, 0.025= 12.4 2222 24, 0.97524, 0.97524, 0.97524, 0.975 = 39.4 ( ). 95% 2

    95% ..

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    s2 = 0.375 . 2

    s2, X2 student. ( ) X2 . .

    p

    .. , ( 1) ( 0). p. [ p Bernoulli]. . p n

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    p

    m n . n

    , p :

    p

    .. p

    n:

    0.25. w ..

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    . . . . n = 100 m = 12 .

    p

    95%

    z1/2 = z0.975 = 1.96)

    95% [0.056, 0.184] , .

    p 95% w = 0.05 ( 5 ). n ( z1/2 = z0.975 = 1.96 w = 0.05)

    . 95% .. 1/3 15