MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_NextPart_01C71D49.FEF73360" このドキュメントは単一ファイル Web ページ (Web アーカイブ ファイル) です。お使いのブラウザ、またはエディタは Web アーカイブ ファイルをサポートしていません。Microsoft Internet Explorer など、Web アーカイブをサポートするブラウザをダウンロードしてください。 ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定

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マスタ タイトルの書式設定
マスタ テキストの書式設定
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第 3 レベル
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マスタ タイトルの書式設定
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------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/pres.xml Content-Transfer-Encoding: quoted-printable Content-Type: text/xml; charset="utf-8" ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0001.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
データ分布= と予測
仮説検定
堀田敬介
2006/12/15,Fri.
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quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
Contents
•仮説検定とは？
–有意水準
–帰無仮説と対立仮説
–仮説検定における誤り=
–片側検定と両側検定
•母集団の母数に対する= 仮説検定
–母平均の検定（母分散= が既知の場合） = ;
–母平均の検定（母分散= が未知の場合） = ;
–母分散の検定<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 71%;display:none'>
–母比率の検定<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 71%;display:none'>
•2に対する仮説検定 = ;
–既知の場合） <= /span>
–未知だが等しい場合） <= /span>
–未知で等しくない場合） <= /span>
–分散の比の検定
•<= /span>適合度検定と独立性の検定
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仮説検定と= は？
仮説検定
hypo= thesis testing
推測統計=
stat= istical inference
標本データの平均値と分散（標準偏差）から，= 齒W団の平均値と分散（標準= ﾎ差），母比率などの母数（= pラメータ）を推定する
標本データの平均値= ﾆ分散（標準偏差）などを= 烽ﾆに，母集団に対する= 「ある仮説」が間違いかどうか判定する
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仮説検定と= は？
•例：日本人成人女性の平均身長
= 211;　仮説　「日本人成人女性の平均身長は160cmである」
=
母集団
<= /span>成人女性 = ;
3D"環状矢印:
ランダ= サンプリング
（無作為抽出）
標本平均の値：157.5cm
仮説は間違っていた（正しかった）と言えるのか？&= #13;
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仮説検定と= は？
•例：日本人成人女性の平均身長
= 211;　仮説　「日本人成人女性の平均身長は160cmである」
= 標本平均の値：157.5cm
標本標準偏差の値：10.78cm
標本平均　　，標本分散　　とすると，= ﾈ下の確率変数 T が自由度 n-1 の t 分布に従う
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仮説検定と= は？
•例：日本人女性の平均身長
R= 11;　仮説　「日本人女性の平均身長は160cmである」
自= 由度9の
t分布に従う
　標本平均　　がこの分布の中心から= 大きく外れ= た位置にあるならば，仮説は間違って= いると判= 定できるのではないか？
注意<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";font-size:111%;mso-fareast-hint:yes'>：仮説が間違いであ= 確率は0にはならない！&= #13;
仮説が間違いである= ﾍ囲を決める！&= #13;
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データ分布と予測　5．仮説検定
仮説検定と= は？
•採択域と棄却域
–例：自由度9のt分布における下側<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";mso-fareast-hint:yes;mso-fareast-l= anguage: JA'>5%棄却域
棄却域= rejection region
（臨界= 域 critical region）
採択域 region of acceptance
95%
5%
T=3D-1.833
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仮説検定と= は？
•採択域と棄却域
–例：自由度9のt分布における= 下側5％棄却域
つまり，
棄却域：
= 採択域= ： となり，標本= 平均値が153.4cm以下であれば，仮説：「日本人成人女性の平均身長は160cmである」が棄却 (rejection of hypothesis)される
例題の場合は= ，標本平均値が157.5cmで棄却域にないため，棄却されない
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有意水準
<= span style=3D'mso-fareast-hint:yes'>•仮説検定の手順
&#= 8211;1．母集団に対する「仮説」を立てる
&#= 8211;2．「仮説」の棄却域を設定する
• 棄却域が5%とすれば95%信頼区間から外れて= いれば「仮説」を「棄却」することになる
棄却域：小
信頼区間：広=
棄却域：大
信頼区間：狭=
★ 棄却域が5%で「仮説」が「棄却」されるとき，5%はその「仮<= span style=3D'position:absolute;top:58.13%;left:0%;width:83.88%;height:44.18%'>= 説」が正しい可能性= ｪ残る！&= #13;
5%の間違いの危険性がある =
5%：有= 意水準(significance level)
     〔危険率(risk)〕
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帰無仮説と= 対立仮説
•検定における仮説は<= u>対立する2つ
= 211;〔仮説<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";font-size:86%;mso-fareast-hint:yes; mso-fareast-language:JA'>1〕日本人成人男性の平均体重は60kgである <= /span>
= 211;〔仮説<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";font-size:86%;mso-fareast-hint:yes; mso-fareast-language:JA'>2〕日本人成人男性の平均体重は60kgではない
帰無仮説 (null hypothesis)
　棄却されてはじめて意味を持つ<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; font-size:111%;mso-special-format:lastCR;display:none'>
★ 仮説1を統計的に検定したとき，その起こる確= ｦが棄却域= にあれば，この仮説= ｪ棄却される．
★ 仮説1が棄却されない場合，「仮説1が正しい= ﾆいう結論= は出せな= ｢」！
★ 仮説1は「棄却されてはじめて意味を持つ」
★ 仮説2は仮説1が棄却された場合に採択される&= #13;
対立仮説 (alternative hypothesis)
　本当に示したいこと
統計的検定の目的は「= 対立仮説の正しさを示す」こと！<= /div>
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仮説検定における誤りと検出力 <= /span>
•仮説検定における誤り = ;
–第１種の誤り error of the first kind
•帰無仮説H0= が正しいのにそれを棄却してしまう
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 90%;mso-fareast-hint:yes'>例：品質管理において「合格するはずの良製品を不合= 格判定」する
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 90%;mso-fareast-hint:yes'>例：刑事犯罪において「無罪の人を有罪」にする
–第２種の誤り error of the second kind
•帰無仮説H0= が誤っているのにそれを採択してしまう
–例：品質管理において「不合格のはずの不良品を合格= 判定」する
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 90%;mso-fareast-hint:yes'>例：刑事犯罪において「有罪の人を無罪」にする
正しい
（確率：1-β=3D検出力）
1
H1=
第2種の誤り
1-α）
H0=
= 検<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; font-size:71%;mso-fareast-hint:yes'>結 <= /div>
対立仮説 = H1
帰無仮説 = H0
= <= /div>
<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; font-size:71%;mso-special-format:lastCR;display:none'> <= /div>
= <= /div>
<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; font-size:71%;mso-special-format:lastCR;display:none'> <= /div>
α：大⇔β：小
α：小⇔β：大
となるので，共に小さくはできない
•帰無仮説が限定的なのでα（有意水準）は= 1つに定まる．<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";font-size:89%;display:none'> •<= /span>サンプル数が大きけれ= ばβは小さくなる．&#= 13;
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両側検定と= 片側検定
•両側検定 two tailed test%） <= /span>
R= 11;〔帰無仮説〕
= 211;　　日本人男性の平均体重は60kgである <= /span>
= 211; （μ＝60） <= /span>
R= 11;〔対立仮説〕
= 211;　　日本人男性の平均体重は60kgではない <= /span>
= 211; （μ≠60）
•片側（右側）検定 one tailed test（有意水準α%） <= /span>
R= 11;〔帰無仮説〕
= 211;　　日本人男性の平均身長は160cmである
= 211; （μ＝160） <= /span>
R= 11;〔対立仮説〕
= 211;　　日本人男性の平均身長は160cmより大きい
= 211; （μ＞160
α%
α%
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•片側検定か両側検定か？
–両側検定…母数の値がある目標値と等しいかどうかだけを調べたいときに用いる
•例：生産ラインの機械が正しく動= ｢ているか？
•<= /span>
–片側検定…母数の大きさが理論的・経験的に予測されるときに用いる
•例：補習後に成績が上がったか？&= #13;
•　（通常上がると考えられるので下がる場合は考慮しない）&= #13;
•例：今年の夏は寒い気がする．本= 魔ｩ？
•　（「寒い」という経験から平均気温が低いことを予測）
両側検定と= 片側検定
------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0028.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
•母平均に関する仮説検定（母分散　　既知）
•
•
•
•<= /span>母平均に関する仮説検定（母分散　　未知）
•
•
•
•<= /span>母分散に関する仮説検定
母数に関する仮説検定
= 搆v量　　　　　　　　　　　　　　が標準正規分布N<= /span>(<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";mso-fareast-language:JA'>0<= /span>,<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";mso-fareast-language:JA'>1<= /span>)<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"'>に従うことを利用
= 搆v量　　　　　　　　　　　　　　　が自由度 n-1 の t 分布に従うことを利用
= 搆v量　　　　　　　　　　　　　が自由度 n-1 のχ2分布に従うことを利用
Z検定
t検定
χ2= 検定
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f/EBhxIhEWg88pLKHLNZe0Jlt+lQamVhszrusup1gsPRMZl6xm3TnzV74353zPIT5DC66/cHgP8P GEjXEVhoeIiYqCjIYbD4CBmJmBQgaXkpSeeIydl5OFbpKTrqh0B66lcAADs= ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0010.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
母数に関する仮説検定
•母平均の検定〔Z<= /span>検定〕 （母分散が既知の場合）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：BMIによる肥満検査
= 226; BMI＝(体重)kg ÷ {()m}2
R= 26;　
= 226;　　ある会社の無作為抽出100
= 226;　　のBMI=3D22.35だった．
= 226;　　肥満の程度に問題があるといえるか？= 有意水準5
–〔帰無仮説〕 母平均μ＝22
–〔対立仮説〕 母平均μ≠22
–で両側検定．ただし，母標準偏差は過去の= 経験から2.5とする．
確率変数Zは
標準正規分布
N(0,1)に従う
〔出展：『図解雑学 統計解析』 p.192〕
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<= span style=3D'mso-fareast-hint:yes'>•母平均の検= 定〔Z<= /span>検定〕 （母分散が既知の場合）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：BMIによる肥満検査 = ;
–　　有意5を表す不等式
母数に関する仮説検定
帰無仮説は= 棄却されない
–結論：肥満の程度に問題があるとはいえない
–　　　　ただし，「問題がない」とまでは= いえない
標準正規分布：両側5%<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";mso-fareast-hint:yes'>棄却域
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母数に関する仮説検定
•母平均の検定〔t検定〕（母分散が未知の場合）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：酒屋の不正疑惑 <= /span>
R= 26;　　ある酒屋では酒の量をごまかして売っ= ているという噂があったので実際に1(=3D180cc)のお酒を5
–〔帰無仮説〕 母平均μ＝180
–〔対立仮説〕 母平均μ＜180
–　　とし，有意水準5%で左片側検定．
確率変数T は
自由度n-1のt分布tα(n-1) に従う
標本平均値は172.0cc であり，180ccより8ccも少ないが，果たしてこの店は不当表示で訴えられるか？
〔出展：『なるほど統計学』 p.125〕
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file:///C:/4ECB5C15/06dist_5.files/slide0026.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
母数に関する仮説検定
•母平均の検定〔t検定〕（母分散が未知の場合）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：酒屋の不正疑惑 = ;
–　　　有意5を表す不等式
よって，
より，帰無仮説 H0= は棄却される．
= ｱの酒屋は酒量をご<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック"'>まかしているらしい…
t分布：片側= （下側）5%棄却域
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•母平均の検定〔t検定〕（母分散が未知の場合）
–演習1：空調システムの作動状況検査
&#= 8211;　　 設定温度を25℃とし，7日間室内温度測定し，このシステムが正しく動いているかどうか5%有意水準で両側検定
&#= 8211;
–　　〔帰無仮説〕μ＝25.0
–　　〔対立仮説〕μ≠25.0
有意水準5％で帰無仮説は棄却できない
母数に関する仮説検定
この空調システムは= ｳ常に動いてるらし= い．
〔出展：『統計学入門』 p.241〕
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S4ir2/vG6xtsxSpcvAdsXIycHLzM3Ov8nBstXUtdHXuN3aq9ndrtXQoePjpO/ml+vpmunsneXvkO Pyk//1hv34iffyvJb7vvn6GAAnf5K+iKIMJjBxd+a+hQHMSI5SZSRGfx4rqMNBrdcewY7yNIeiJH 3itpUh/KlP2IsdSk8GVMljNT1jR5c2ROkDs7BvoJNKjQoUSLGj0KqAAAOw== ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0018_image099.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhBgATAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAQAF ABEAgAAAAP9mAAIPhBGXetjrmDQQRvrm3bYAADs= ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0019.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
•母平均の検定〔t検定〕（母分散が未知の場合）
–演習2：補習授業の効果測定
= 211;　　　英語の補習を行った後の試験成績は上がったか？5%有意水準で効果を検定せよ．10名の対象学生に対する補習前後の得点差は下表
–
–　　　〔帰無仮説〕μ＝0
–　　　〔対立仮説〕μ>0
母数に関する仮説検定
有意水準5％で帰無仮説は棄却される
試験成績は上昇した= 轤ｵい（補習の効果= はあったらしい）
〔出展：『統計学入門』 p.241〕
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•母平均の検定〔t検定〕（母分散が未知の場合）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; font-size:86%'>演習3 ：今年の生徒は出来= ｪよいか？
= 211;　　　数学の定期試験で10人の採点を終えた所= C平均が71点で昨年度（65.7点）より5.3= _も良い！今年の生徒は出来がよいのだろうか？ 5%有意水準で検定せよ．
= 211;
–　　　〔帰無仮説〕μ＝65.7
–　　　〔対立仮説〕μ>65.7
母数に関する仮説検定
有意水準5％で帰無仮説は棄却される
今年の生徒は昨年= xよりも出来が良い= らしい．
〔出展：『図解雑学 統計解析』 p.202〕
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Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
&#= 8226;母分散の検定〔χ2検定〕
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：製品のばらつき検査 = ;
–　　　目標重量25sの製品の重量のばらつきが大きいことがわかり修理した．修理後の製品を無作為抽出した結= 果が以下．修理前の分散が9s2のとき，この製品は性能が向上したといえ= るか？ <= /div>
母数に関する仮説検定
修理後は性能が向上したと考えられる
　　⇒　分散は小さくなったはず
　　⇒　片側（下側）検定
　〔帰無仮説〕 σ2= =3D9
　〔対立仮説〕 σ2= <9
確率変数χ2は =
自由度n-1の
χ2分布に従う
〔出展：『なるほど統計学』 p.132〕
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<= span class=3DBB style=3D'position:absolute;left:-4.57%'>•母分散の検定<= /span>〔χ2検定〕
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：製品のばらつき検査 = ;
–　　有意水準5%の棄却域を表す不等式
母数に関する仮説検定
有意水準5％で帰無仮説は棄却できない
この製造機械が修理後によくなったと= 結論できない．
χ<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";font-size:67%;position:relative; top:-.45em;mso-text-raise:30%;mso-fareast-language:JA'>2分布：片側（下側）5%<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";mso-fareast-hint:yes'>棄却域
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<= span class=3DBB style=3D'position:absolute;left:-4.57%'>•母分散の検定<= /span>〔χ2検定〕
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>演習：小学校の知能テスト = ;
= 211;　　　ある小学校の入学時知能テストの結果は平均50，分散36だった．本年度入学児25名を無作為抽出したところ平均53，分散48だった．本年度入学児の揃い方は例年と違うか？
= 211;
–　　〔帰無仮説〕 σ2=3D36
–　　〔対立仮説〕 σ2≠36
= 211;
–有意水準10%棄却域
母数に関する仮説検定
有意水準10％で= = 帰無仮説は棄却= できない
今年度入学児童が例年と違うとはいえ= ない．
〔出展：『統計学入門』 p.242〕
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<= span style=3D'color:#003399;text-shadow:auto;mso-fareast-hint:yes'>•母平均の差の検定
&= #8211;2つの正規母集= cについて母平均の差の検定
•母分散が既知の場合
•
•母分散が未知だが等しい場合
•
•母分散が未知で等しくない場合
•
•母分散の比の検定
–2つの正規母= 集団について母分散の比の検定
2標本検定 two-sample test
Z <= /span>検定
ウェルチの検定
t 検定
3D"ホームベース:
F 検定
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•母平均の差の検定
&= #8211;2つの正規母集= cについて母平均の差の検定
〔帰無仮説〕
〔対立仮説〕
2標本検定 two-sample test
m<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; mso-fareast-hint:yes'>個 無作為抽出
n<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; mso-fareast-hint:yes'>個 無作為抽出
←2つの正規母集団の母平均に差がない
←2つの正規母集団の母平均に差がある
両側検定の場合
片側検定の場合
〔帰無仮説〕
〔対立仮説〕
←2つの正規母集団の母平均に差がない
←2つの正規母集団の母平均に差がある
標本平均：
標本平均：
２= つの母平均に
「= 差がある」か「ない」か
の= 検定
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•母平均の差の検定
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>２標本の標本平均の差の標本分布 = ;
–
–
–
–
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>この検定の例：医薬の効果の検証 = ;
•患者を新薬を使った治療を行うグループ（処理群）とそれ以外（対照群）に分け，グループで結果に差があるかどうか（新薬の効果があるかどうか）を検定する．
2標本検定 two-sample test
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charset="shift_jis" データ分布と予測　5．仮説検定
•母平均の差の検定（母分散が既知のとき）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>標本平均の差の標本分布
2標本検定 two-sample test
Z検定
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•母平均の差の検定（母分散が未知だが等しい　　　　　　 ）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>標本平均の差の標本分布 = ;
•
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>合併分散 pooled varian= ce
–
–
–
•
•
–補足：『合併分散は不偏推定量である』
2標本検定 two-sample test
ただし，　　　　　 は不偏推定量
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•母平均の差の検定（母分散が未知だが等しい　　　　　　 ）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";mso-fareast-hint: yes;mso-special-format:lastCR;display:none'>
2標本検定 two-sample test
t検定
= （ただし，Zとχ2は独立）
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Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
=
–5%有意水準で両側検定 = ;
–  （〔帰無仮説〕　　　　  〔対立仮説〕　　　    ）
•母平均の差の検定（母分散が未知だが等しい　　　　　　 ）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：苗木の生長における2社の肥料の違い = ;
= 211;　　ある苗木の生長について2社の肥料に違いがあるか？
2標本検定 two-sample test
t検定
より，仮説を棄却
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•母平均の差の検定（母分散が未知で等しくない　　　　 ）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>標本平均の差の標本分布 = ;
•<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 83%;mso-fareast-hint:yes'>どのように工夫しても，2つの母分散に拠らない統計量を作れない
= 226; ↓ = ;
•<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 83%;mso-fareast-hint:yes'>標本平均の差の正確な分布を求められない
= 226; ↓ = ;
•<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 83%;mso-fareast-hint:yes'>近似的に分布を求める〔ウェルチの近似法〕
2標本検定 two-sample test
ウェルチの検定
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Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
=
–5%有意水準で両側検定 = ;
–  （〔帰無仮説〕　　　　  〔対立仮説〕　　　    ）
•母平均の差の検定（母分散が未知で等しくない　　　　 ）
–<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 86%;mso-fareast-hint:yes'>例：2つの鉱山から採れる鉱石に含まれる物質の含有量 = ;
= 211; 各鉱山から採れる鉱石の物質含有量に差があるか？
2標本検定 two-sample test
ウェルチの検定=
より，自由度17のt分布を考える
より，仮説を棄却
〔出展：『パソコンによるデータマイニ= 塔O』 p.132〕
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Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhHAAeAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAAAAgAa ABoAhAAAAACAANH/0dT/1Nn/2d//39r/2s7/zuX/5ez/7PL/8vb/9vr/+v3//f7//vf/9+b/5uD/ 4AECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwWPICCOpBiUaJoGrOqi gSCcbx0MOF2rAeETul0pUCgWgyOWcrlEOJ9IQCBBrVqvVmRAwe16v99gYEEum89oXYDBbrvfcAYt 0Kjb7/h8/RRw+P+AgYJ/LIOGhyx6iop8cY5xcw+Sk5SVlmpgmZliWJ1YWkyhARCkpVE7ARGqqqeo Bq8Grag4A7KoMraoB7movCEAOy== ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0035.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
•母分散の比の検定〔F検定〕
&= #8211;2つの正規母集= cについて母分散の比<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック"'>の検定
2標本検定 two-sample test
m<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; mso-fareast-hint:yes'>個 無作為抽出
n<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; mso-fareast-hint:yes'>個 無作為抽出
〔帰無仮説〕
〔対立仮説〕
←2つの正規母集団の母分散に差がない
←2つの正規母集団の母分散に差がある
両側検定の場合
片側検定の場合
〔帰無仮説〕
〔対立仮説〕
←2つの正規母集団の母分散に差がない
←2つの正規母集団の母分散に差がある
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file:///C:/4ECB5C15/06dist_5.files/slide0050.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
•母分散の比の検定〔F検定〕
–F分布とフィッシャーの分散比<= span style=3D'font-family: "ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-special-fo= rmat:lastCR; display:none'>
2標本検定 two-sample test
フィッシャー
の分散比
自由度(m-1, n-1)<= /span>のF分布に従う
F分布：両側= 5%棄却域
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–5%有意水準で両側検定 = ;
–  （〔帰無仮説〕　　　　  ，〔対立仮説〕　　　    ）
•母分散の比の検定〔F検定〕
–例題：2つの工作機械の製品バラツキ検査
2標本検定 two-sample test 3D"テキスト
＞
より，仮説は=
棄却される&= #13;
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4AECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwWPICCOpBiUaJoGrOqi gSCcbx0MOF2rAeETul0pUCgWgyOWcrlEOJ9IQCBBrVqvVmRAwe16v99gYEEum89oXYDBbrvfcAYt 0Kjb7/h8/RRw+P+AgYJ/LIOGhyx6iop8cY5xcw+Sk5SVlmpgmZliWJ1YWkyhARCkpVE7ARGqqqeo Bq8Grag4A7KoMraoB7movCEAOy== ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0052.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
•母分散の比の検定〔F検定〕
–F分布表からのF値の求め方
= 226;F分布表はαが通常｢0.1,0.05,0.25,0.01,0.005｣のときの表のみ表示されていて，下側(左側)パーセント点は表示されていない．そこで…
= 226;
= 226;
= 226;
= 226;であることを利用して求める．
–例：自由度(10,13)のF<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:"Times New Ro= man"; mso-fareast-font-family:"ＭＳ Ｐゴシック";mso-hansi-font-family:"Times New= Roman"; mso-fareast-hint:yes'>分布の下側(左側)5%点
2標本検定 two-sample test
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<= span style=3D'mso-fareast-hint:yes'>•適合度のχ2検定 〔χ2-test of good= ness of fit〕
= 211;　　　仮定された理論上の確率分布に対し，標本から求められた度数が適合するか否かを検証する．
–例：さいころ投げ = ;
–　　さいころを300回投げると理論上は1〜6の目が50回ずつ出る (さいころの目は一様分布と= なる） ．実際に300回投げると…
= 211;
= 211;
= 211;
–　〔帰無仮説〕　さいころの目の出方に偏りがない(一様分布に従う)
–　〔対立仮説〕　さいころの目の出方に偏りがある(一様分布に従わない)
適合度検定
適合度検定：
　　母集団分布の従う確率分布につい= て= 立てた帰無仮説を検証する
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&#= 8226;適合度の測定
R= 11;例：さいころ投げ
= 211;　〔帰無仮説〕　さいころの目の出方に偏りがない(一様分布に従う)
= 211;　〔対立仮説〕　さいころの目の出方に偏りがある(一様分布に従わない)
適合度検定
K.Pearsonの適合度基準
（nが十分大きければ= j
自由度k-1の
χ2分布に従う
　　　　　　　　　= @はk個の確率変数だが，
より，自由度は1つ減る&= #13;
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&#= 8226;適合度の測定
R= 11;例：さいころ投げ
= 211;　有意水準5%棄却域を表す不等式
適合度検定
このさいころは、目の出方に= 偏りがない（一様分布に従う）といえるようだ
より，棄却域にない= ﾌで，帰無仮説は棄却できない&= #13;
χ<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";font-size:67%;position:relative; top:-.45em;mso-text-raise:30%;mso-fareast-language:JA'>2分布：上側5%棄却域
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<= span style=3D'mso-fareast-hint:yes'>•適合度のχ2検定 〔χ2-test of good= ness of fit〕
= 211;　例：メンデルの法則〔えんどう豆の形質遺伝〕
= 211;
= 211;
= 211;
= 211;
–　〔帰無仮説〕　えんどう豆の表現型はメンデルの法= 則に適合している
–　〔対立仮説〕　えんどう豆の表現型はメンデルの法= 則に適合していない
適合度検定
より，5%有意水準の棄却域にないので，帰無仮説は棄却でき= ﾈい&= #13;
えんどう豆の表現型= ﾍメンデル= の法則に適合してい= 驍謔､だ&= #13;
〔出展：『統計学入門』 p.245〕
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file:///C:/4ECB5C15/06dist_5.files/slide0038_image316.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFQAVAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIAAQAS ABIAgQAAAP8AAP9mAAECAwI5hICpeRa9lHiORjQDzVBqW3UViGlQRjLmKHrP1y5oeqGx/K1XaXK7 zWsBVaShq2HEPQS+XchwkxwKADs= ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0034.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
<= span style=3D'mso-fareast-hint:yes'>•独立性のχ2検定 〔χ2-test for independence〕
•　　　　2つの属性の間に関係があるかどうかを検証する = ;
•　　　例：支持政党に男女差があるか？
独立性の検定
支持政= 党に男女差= があるか？=
〔出展：『図解雑学 統計解析』 p.224〕
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------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/slide0039.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis" データ分布と予測　5．仮説検定
= <= span style=3D'mso-fareast-hint:yes'>•独立性の測定 = ;
•　　　例：支持政党に男女差があるか？
•　　　　〔帰無仮説〕= 支持政党に男女差がない ⇒ <= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-fareast-font-family:"ＭＳ Ｐゴ= Vック";font-size: 63%;mso-fareast-hint:yes'>ともに全体比率に等しい = ;
•　　　　〔対立仮説〕= 支持政党に男女差がある
独立性の検定
観測<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";font-size:111%;display:none'>
度数<= span style=3D'font-family:"ＭＳ Ｐゴシック";mso-ascii-font-family:Verdana;mso-f= areast-font-family: "ＭＳ Ｐゴシック";font-size:111%;mso-special-format:lastCR;display:none'><= b>
理= 論 <= /span>
度= 数
独立性の基準
（nが十分大きければ）
自由度(r-1)(c-1)の
χ2分布に従う
この差を適合度検定&#= 13;
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<= span style=3D'mso-fareast-hint:yes'>•独立性の測定 = ;
•　　　例：支持政党に男女差があるか？
•　　　　　有意水準5%棄却域を表す不等式
独立性の検定
χ<= span lang=3DEN-US style=3D'font-family:"Times New Roman";mso-ascii-font-family:= "Times New Roman"; mso-hansi-font-family:"Times New Roman";font-size:67%;position:relative; top:-.45em;mso-text-raise:30%;mso-fareast-language:JA'>2分布：上側5%棄却域
支持政党に男女間の= ｷ= があるとはいえない<= /span>&= #13;
より，棄却域にない= ﾌで，帰無仮説は棄却できない&= #13;
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•独立性のχ2検定 〔χ2-test for independence〕
= 211;　演習：某工学部の期末試験成績：代数と解析の成績に関係があるか？
R= 11;
= 211;
= 211;
R= 11;
R= 11;　〔帰無仮説〕　代数と解析の成績に関係がない
R= 11;　〔対立仮説〕　代数と解析の成績に関係がある
独立性の検定
より，5%有意水準の棄却域にないので，帰無仮説は棄却でき= ﾈい&= #13;
代数と解析の成績に= ﾍ関係があ= るとはいえない&= #13;
〔出展：『統計学入門』 p.248= 〕
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データ分布と予測　5．仮説検定
•演習1：サイコロの目の出方に偏りがあるか？　= 有意水準5%で検定せよ．
適合度検定= ・独立性の検定
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賽の目
•演習2：コーヒーの嗜好に違いがあるか？　有意= 水準5％で検定せよ．
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参考文献
<= span style=3D'font-size:63%'>•東大教養学部統計学教室編　「統計学入門」<= /span> 東大出版会（1991）
<= span style=3D'font-size:63%'>•東大教養学部統計学教室編　「自然科学の統= v学」 東大出版会（1992）
•鈴木達三・高橋宏一 「標本抽出の計画と方法」 = 放送大学 （1991）
<= span style=3D'font-size:75%'>•永田靖 「サンプルサイズの決め方」 朝倉書店 （2003）
<= span style=3D'font-size:75%'>•村上雅人 「なるほど統計学」 海鳴社 （2002）
<= span style=3D'font-size:75%'>•丹慶勝市 「図解雑学 統計解析」 ナツメ社 （2003）
<= span style=3D'font-size:63%'>•高橋信[著]・トレンドプロ[マンガ]「マンガでわかる統計学」オーム社（= 2004）
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<= /div>
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<日付/時刻>
マスタ テキストの書式設定
第 2 レベル
第 3 レベル
第 4 レベル
第 5 レベル
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_InitAnimations(); =09 if( IsWin("PPTSld") ) parent.SldUpdated(GetSldId()) g_origSz=3DparseInt(SlideObj.style.fontSize) g_origH=3Dsld.style.posHeight g_origW=3Dsld.style.posWidth g_scaleHyperlinks=3D(document.all.tags("AREA").length>0) if( g_scaleHyperlinks ) InitHLinkArray() if( g_scaleInFrame||(IsWin("PPTSld") && parent.IsFullScrMode() ) ) document.body.scroll=3D"no" _RSW() if( IsWin("PPTSld") && parent.IsFullScrMode() ) FullScrInit(); =09 MakeSldVis(); ChkAutoAdv() if( runAnimations ) { if( document.all("NSPlay") ) document.all("NSPlay").autoStart =3D false; if( sld.filters && sld.filters.revealtrans ) setTimeout( "document.body.start()", sld.filters.revealtrans.duration * = 1000 ); else document.body.start(); } } function MakeSldVis()=20 { var fTrans=3Dg_showAnimation && SldHasTrans() if( fTrans )=09 { if( g_bgSound ) { idx=3Dg_bgSound.indexOf(","); pptSound.src=3Dg_bgSound.substr( 0, idx ); pptSound.loop=3D -(parseInt(g_bgSound.substr(idx+1))); } SlideObj.filters.revealtrans.Apply()=09 } SlideObj.style.visibility=3D"visible" if( fTrans ) SlideObj.filters.revealtrans.Play() } function MakeNotesVis()=20 { if( !IsNts() ) return false=20 SlideObj.style.display=3D"none" nObj =3D document.all.item("NotesObj") parent.SetHasNts(0) if( nObj ) {=20 nObj.style.display=3D"" parent.SetHasNts(1) } return 1 } function ChkAutoAdv() { if(SldHasTrans()) SlideObj.onfilterchange=3DAutoAdv else AutoAdv() } function AutoAdv() { if(!IsWin("PPTSld") || !gUseSldTimings )return var sld=3DGetCurSld() if( (sld.mAdvDelay>0) && !parent.IsFramesMode() ) setTimeout("parent.GoToNextSld()",sld.mAdvDelay) } function GetObj(id) { if(g_supportsPPTHTML) return document.all(id); else return document.getElementById(id); } function SldHasTrans() { return SlideObj.style.filter !=3D ""; } function GetSldId()=20 { var regExp =3D /file:\/\/\//i var pos =3D location.href.search(regExp) if (MHTMLPrefix !=3D "" && pos !=3D -1) sId =3D location.href.substring(pos) else { sId =3D RemoveFilePrefixFromHref(location.href); var regExp =3D /\// var fixedHref =3D sId var pos =3D -1 =09 pos =3D fixedHref.search(regExp) while (pos !=3D -1) { fixedHref =3D fixedHref.replace(regExp, "\\") pos =3D fixedHref.search(regExp) } =09 if (g_fBaseHyperlink =3D=3D true) sId =3D "file:///" + fixedHref; else sId =3D fixedHref.substring(fixedHref.lastIndexOf('\\') + 1) } =09 return sId } function HideMenu() { if( frames["PPTSld"] && PPTSld.document.all.item("ctx= tmenu") && PPTSld.ctxtmenu.style.display!=3D"none" ) { PPTSld.ctxtmenu.styl= e.display=3D'none'; return true } return false } function IsWin( name ) { return window.name =3D=3D name } function IsNts() { return IsWin("PPTNts") } function IsSldOrNts() { return( IsWin("PPTSld")||IsWin("PPTNts") ) } function SupportsPPTAnimation() { return( navigator.platform =3D=3D "Win32"= && navigator.appVersion.indexOf("Windows")>0 ) } function SupportsPPTHTML() { var appVer=3Dnavigator.appVersion, msie=3DappVer.indexOf("MSIE "), ver=3D0 if( msie >=3D 0 ) ver=3DparseFloat( appVer.substring( msie+5, appVer.indexOf(";",msie) ) ) else ver=3DparseInt(appVer) return( ver >=3D 4 && msie >=3D 0 ) } function _RSW() { if( !g_supportsPPTHTML || IsNts() || ( !g_scaleInFrame && (!IsWin("PPTSld") || !parent.IsFullScrMode()) ) ) return var padding=3D0; if( IsWin("PPTSld") && parent.IsFramesMode() ) padding=3D6 cltWidth=3Ddocument.body.clientWidth-padding cltHeight=3Ddocument.body.clientHeight-padding factor=3D(1.0*cltWidth)/g_origW if( cltHeight < g_origH*factor ) factor=3D(1.0*cltHeight)/g_origH newSize =3D g_origSz * factor if( newSize < 1 ) newSize=3D1 s=3DSlideObj.style s.fontSize=3DnewSize+"px" s.posWidth=3Dg_origW*factor s.posHeight=3Dg_origH*factor s.posLeft=3D(cltWidth-s.posWidth+padding)/2 s.posTop=3D(cltHeight-s.posHeight+padding)/2 if( g_scaleHyperlinks ) ScaleHyperlinks( factor ) } function _InitAnimations() { animRuntimeInstalled =3D ''+document.body.localTime !=3D 'undefined'; isFullScreen =3D (window.name =3D=3D "PPTSld") && !parent.IsFramesMode(); g_animUseRuntime =3D g_showAnimation && animRuntimeInstalled && !(isFullSc= reen && parent.IsSldVisited()); if( g_animUseRuntime ) { collSeq =3D document.all.tags("seq"); if( collSeq !=3D null ) { for(ii=3D0;ii numSlds ) gSldJumpIdx =3D numSlds; if ( gSldJumpIdx >=3D 0 ) { if ( gSldJumpIdx =3D=3D 0 ) gSldJumpIdx =3D 1; var jumpTo =3D parseInt(gSldJumpIdx); gSldJump =3D 0; gSldJumpIdx =3D ""; win.GoToSld( parent.GetSldList().mList[jumpTo-1].mSldHref ) } } } function _KDH() { if( event.keyCode =3D=3D 8 ) { event.returnValue =3D 0; parent.GoToPrevSld(); } }function DocumentOnClick() { if( IsNts() || parent.HideMenu() ) return; if( ( g_allowAdvOnClick && (window.name=3D=3D"PPTSld") && !parent.IsFrames= Mode() ) || (event && event.keyCode=3D=3D32) ) { =09 if( g_animUseRuntime && g_animMainSequence && g_animMainSequence.cangonex= t ) return; parent.GoToNextSld(); } } var g_supportsPPTHTML =3D SupportsPPTHTML(), g_scaleInFrame =3D 1, gId=3D""= , g_bgSound=3D"", g_scaleHyperlinks =3D false, g_allowAdvOnClick =3D 1, g_showInBrowser = =3D 0, gLoopCont =3D 0, gUseSldTimings =3D 1; var g_showAnimation =3D g_supportsPPTHTML && SupportsPPTAnimation() && ( (w= indow.name=3D=3D"PPTSld" && !parent.IsFramesMode()) || g_showInBrowser );va= r g_animManager =3D null; var g_animUseRuntime =3D false; var g_animItemsToHide, g_animInteractiveItems, g_animSlideTime; var g_animMainSequence =3D null; var ENDSHOW_MESG=3D"スライド ショーの最後です。 クリックすると終了します。"= , SCREEN_MODE=3D"Frames", gIsEndShow=3D0, NUM_VIS_SLDS=3D47, SCRIPT_HREF=3D= "script.js", FULLSCR_HREF=3D"fullscreen.htm"; var gCurSld =3D gPrevSld =3D 1, g_offset =3D 0, gNtsOpen =3D gHasNts =3D gO= tlTxtExp =3D 0, gHasNarration =3D 0, gOtlOpen =3D true window.gPPTHTML=3DSupportsPPTHTML() var g_fBaseHyperlink =3D false; var gMainDoc=3Dnew Array(new hrefList("slide0001.htm",1,-1,1),new hrefList(= "slide0002.htm",1,-1,1),new hrefList("slide0003.htm",1,-1,1),new hrefList("= slide0005.htm",1,-1,1),new hrefList("slide0006.htm",1,-1,1),new hrefList("s= lide0007.htm",1,-1,1),new hrefList("slide0008.htm",1,-1,1),new hrefList("sl= ide0009.htm",1,-1,1),new hrefList("slide0011.htm",1,-1,1),new hrefList("sli= de0012.htm",1,-1,1),new hrefList("slide0024.htm",1,-1,1),new hrefList("slid= e0013.htm",1,-1,1),new hrefList("slide0025.htm",1,-1,1),new hrefList("slide= 0028.htm",1,-1,1),new hrefList("slide0010.htm",1,-1,1),new hrefList("slide0= 014.htm",1,-1,1),new hrefList("slide0015.htm",1,-1,1),new hrefList("slide00= 26.htm",1,-1,1),new hrefList("slide0018.htm",1,-1,1),new hrefList("slide001= 9.htm",1,-1,1),new hrefList("slide0027.htm",1,-1,1),new hrefList("slide0020= .htm",1,-1,1),new hrefList("slide0029.htm",1,-1,1),new hrefList("slide0030.= htm",1,-1,1),new hrefList("slide0048.htm",1,-1,1),new hrefList("slide0021.h= tm",1,-1,1),new hrefList("slide0044.htm",1,-1,1),new hrefList("slide0031.ht= m",1,-1,1),new hrefList("slide0042.htm",1,-1,1),new hrefList("slide0046.htm= ",1,-1,1),new hrefList("slide0049.htm",1,-1,1),new hrefList("slide0043.htm"= ,1,-1,1),new hrefList("slide0047.htm",1,-1,1),new hrefList("slide0035.htm",= 1,-1,1),new hrefList("slide0050.htm",1,-1,1),new hrefList("slide0051.htm",1= ,-1,1),new hrefList("slide0052.htm",1,-1,1),new hrefList("slide0033.htm",1,= -1,1),new hrefList("slide0036.htm",1,-1,1),new hrefList("slide0037.htm",1,-= 1,1),new hrefList("slide0038.htm",1,-1,1),new hrefList("slide0034.htm",1,-1= ,1),new hrefList("slide0039.htm",1,-1,1),new hrefList("slide0040.htm",1,-1,= 1),new hrefList("slide0041.htm",1,-1,1),new hrefList("slide0054.htm",1,-1,1= ),new hrefList("slide0053.htm",1,-1,1)); /********************************************* Frameset functions These functions control slide navigation and state of the frameset. **********************************************/ function RemoveFilePrefixFromHref(href) { var regExp =3D /^file:\/\/\//i; return href.replace(regExp, "") } function FullScrInit() { g_allowAdvOnClick =3D GetCurSld().mAdvOnClk document.body.style.backgroundColor=3D"black" document.oncontextmenu=3Dparent._CM; document.onkeydown =3D _KDH; document.ondragstart=3DCancel document.onselectstart=3DCancel self.focus() } function Redirect( frmId ) {=09 var str=3Ddocument.location.hash,idx=3Dstr.indexOf('#'), sId=3DGetSldId() if(idx>=3D0) str=3Dstr.substr(1); if( window.name !=3D frmId && ( sId !=3D str) ) { obj =3D GetObj("Main-File") window.location.href=3Dobj.href+"#"+sId return 1 } return 0 } var MHTMLPrefix =3D CalculateMHTMLPrefix();=20 function CalculateMHTMLPrefix() { if ( document.location.protocol =3D=3D 'mhtml:') {=20 href=3Dnew String(document.location.href)=20 Start=3Dhref.indexOf('!')+1=20 End=3Dhref.lastIndexOf('/')+1=20 if (End < Start)=20 return href.substring(0, Start)=20 else=20 return href.substring(0, End)=20 } return ''; } function GetTags(base,tag) { if(g_supportsPPTHTML) return base.all.tags(tag); else return base.getElementsByTagName(tag); } function UpdNtsPane(){ if(frames["PPTNts"]) PPTNts.location.replace( MHTMLP= refix+GetHrefObj( gCurSld ).mNtsHref ) } function UpdNavPane( sldIndex ){ if(gNavLoaded) PPTNav.UpdNav() } function UpdOtNavPane(){ if(gOtlNavLoaded) PPTOtlNav.UpdOtlNav() } function UpdOtlPane(){ if(gOtlLoaded) PPTOtl.UpdOtl() } function SetHasNts( fVal ) { if( gHasNts !=3D fVal ) { gHasNts=3DfVal UpdNavPane() } } function ToggleOtlText() { gOtlTxtExp=3D!gOtlTxtExp UpdOtlPane() } function ClearMedia() { // Clear any sounds playing before launching another browser window. Other= wise, // in fullscreen mode, you'll continue to hear the sound in the frames mod= e. if (PPTSld.pptSound) PPTSld.pptSound.loop =3D 0; } function FullScreen() {=20 if ( PPTSld.g_animUseRuntime ) PPTSld.document.body.pause(); ClearMedia(); var href =3D ( document.location.protocol =3D=3D 'mhtml:') ? FULLSCR_HREF = : FULLSCR_HREF+"#"+GetHrefObj(gCurSld).mSldHref; if (MHTMLPrefix !=3D "") href =3D RemoveFilePrefixFromHref(href) if(PPTNav.event.ctrlKey) { var w =3D (window.screen.availWidth * 1.0) / 2.0 var h =3D w * (PPTSld.g_origH * 1.0) / PPTSld.g_origW win =3D window.open( MHTMLPrefix+href,null,"toolbar=3D0,resizable=3D1,top= =3D0,left=3D0," + "width=3D"+ w + ",height=3D" + h ); if( win.document.body && PPTSld.g_animUseRuntime ) win.document.body.PPTSldFrameset=3Dwindow; } else { win =3D window.open( MHTMLPrefix+href,null,"fullscreen=3Dyes" ); if( win.document.body && PPTSld.g_animUseRuntime ) win.document.body.PPTSldFrameset=3Dwindow; } } function ToggleVNarration() { rObj=3DPPTSld.document.all("NSPlay") if( rObj && !PPTSld.g_animUseRuntime ) { if( (rObj.playState =3D=3D 1)||(rObj.playState =3D=3D 0) ) rObj.Play() else if( rObj.playState =3D=3D 2 ) rObj.Pause() else return; } else if( PPTSld.g_animUseRuntime ) { narObj =3D PPTSld.document.all("narrationID") if( narObj ) narObj.togglePause() } } function GetCurSldNum() { =20 obj=3DGetHrefObj(gCurSld) if( obj.mOrigVis =3D=3D 1 ) return obj.mSldIdx else =20 return gCurSld } function GetNumSlds() { =20 if( GetHrefObj(gCurSld).mOrigVis =3D=3D 1 ) return GetSldList().mNumVisSlds; else return GetSldList().mList.length } function GetSldNum( href ) { for(ii=3D0; ii 1 ) PopSldList(); else if( !IsFramesMode() ) { if( gLoopCont ) GoToFirst() else EndShow() } } function GoToPrevSld() { ii=3DgCurSld-1 if( ii > 0 ) { obj=3DGetHrefObj(ii) while ( obj && ( obj.mVis =3D=3D 0 ) && ( ii>0 ) ) obj=3DGetHrefObj(--ii) if( ii =3D=3D 0 ) ii=3D1 GoToSldNum(ii) } } function GoToFirst(){ GoToSld( GetHrefObj(1).mSldHref ) } function GoToLast() { ii=3DGetSldList().mList.length if( ii !=3D gCurSld ) GoToSld( GetHrefObj(ii).mSldHref ) } function GoToSldNum( num ) { if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue obj =3D GetHrefObj( num ) obj.mVis=3D1 gPrevSld=3DgCurSld gCurSld =3D num; =09 if (MHTMLPrefix !=3D "") PPTSld.location.replace(MHTMLPrefix+RemoveFilePrefixFromHref(obj.mSldHref= )) else PPTSld.location.replace(obj.mSldHref) =09 if( IsFramesMode() ) { UpdNavPane(); UpdOtlPane(); UpdNtsPane() } } function GoToSld( href ) { if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue GetHrefObj( GetSldNum(href) ).mVis=3D1 if (MHTMLPrefix !=3D "") PPTSld.location.replace(MHTMLPrefix+RemoveFilePrefixFromHref(href)) else PPTSld.location.replace(href) } function SldUpdated( id ) { if( id =3D=3D GetHrefObj(gCurSld).mSldHref ) return gPrevSld=3DgCurSld gCurSld=3DGetSldNum(id) if( IsFramesMode() ) { UpdNavPane(); UpdOtlPane(); UpdNtsPane() } } function PrevSldViewed(){ GoToSld( GetHrefObj(gPrevSld).mSldHref ) } function HasPrevSld() { return ( gIsEndShow || ( gCurSld !=3D 1 && GetHrefO= bj( gCurSld-1 ).mVis =3D=3D 1 )||( GetCurSldNum() > 1 ) ) } function HasNextSld() { return (GetCurSldNum() !=3D GetNumSlds()) } function CloseWindow() { if( HideMenu() ) return; =09 var event =3D PPTSld.event; if( !IsFramesMode() && event && (event.keyCode=3D=3D27 || event.keyCode=3D= =3D32 || event.type=3D=3D"click" ) ) window.close( self ); CatchNumKeys( self, event ); } function Unload() { gIsEndShow=3D0; } function SetupEndShow() { gIsEndShow=3D1; PPTSld.document.body.scroll=3D"no"; PPTSld.document.onkeypress=3DCloseWindow; PPTSld.document.onclick=3DCloseWindow; PPTSld.document.oncontextmenu=3D_CM; } function EndShow() { if( IsFramesMode() ) return if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue doc=3DPPTSld.document var dir =3D doc.body.dir if( dir !=3D "rtl" ) dir =3D "ltr"; doc.open() doc.writeln('


' + ENDSHOW_MESG + '

') doc.close() } function SetSldVisited(){ GetSldList().mList[gCurSld-1].mVisited=3Dtrue } function IsSldVisited(){ return GetSldList().mList[gCurSld-1].mVisited } function hrefList( sldHref, visible, advDelay, advClk ) { this.mSldHref=3D this.mNtsHref =3D sldHref this.mOrigVis=3D this.mVis =3D visible this.mVisited=3D false this.mAdvDelay=3D advDelay this.mAdvOnClk=3D advClk } function SldList(arr,curSld,fEnd) { this.mCurSld =3D curSld; this.mList =3D new Array(); var idx =3D 1; for(ii=3D0;ii 0) { PushSldList(sldList,fEnd); gCurSld =3D 1; } else if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue } function PushSldList(arr,fEnd) { var ii =3D gSldStack.length; gSldStack[ii] =3D new SldList(arr,gCurSld,fEnd); GoToSld( gSldStack[ii].mList[0].mSldHref ); } function PopSldList() { if (gSldStack[gSldStack.length-1].fEndShow) EndShow() else { gCurSld =3D gSldStack[gSldStack.length-1].mCurSld; gSldStack[gSldStack.length-1] =3D null; gSldStack.length--; var sldList =3D gSldStack[gSldStack.length-1]; GoToSld( sldList.mList[gCurSld - 1].mSldHref ); } } var custShowList=3Dnew Array(); /********************************************* Navigation button implementation There are 2 types of buttons: ImgBtn, TxtBtn implemented as function objects. They share a similiar interface so the event handlers can call SetActive, for example, on a button=20 object without needing to know exactly=20 what type of button it is. **********************************************/ //---------------------------------- function ImgBtn( oId,bId,w,action ) //---------------------------------- { var t=3Dthis t.Perform =3D _IBP t.SetActive =3D _IBSetA t.SetInactive=3D _IBSetI t.SetPressed =3D _IBSetP t.SetDisabled=3D _IBSetD t.Enabled =3D _IBSetE t.ChangeIcon =3D null t.UserAction =3D action t.ChgState =3D _IBUI t.mObjId =3D oId t.mBorderId=3D bId t.mWidth =3D w t.mIsOn =3D t.mCurState =3D 0 } function _IBSetA() { if( this.mIsOn ) { obj=3Dthis.ChgState( gHiliteClr,gShadowClr,2 ) obj.style.posTop=3D0 } } function _IBSetI() { if( this.mIsOn ) { obj=3Dthis.ChgState( gFaceClr,gFaceClr,1 ) obj.style.posTop=3D0=20 } } function _IBSetP() { if( this.mIsOn ) { obj=3Dthis.ChgState( gShadowClr,gHiliteClr,2 ) obj.style.posLeft+=3D1; obj.style.posTop+=3D1 } } function _IBSetD() { =20 obj=3Dthis.ChgState( gFaceClr,gFaceClr,0 ) obj.style.posTop=3D0=20 } function _IBSetE( state ) { var t=3Dthis GetObj( t.mBorderId ).style.visibility=3D"visible" if( state !=3D t.mIsOn ) { t.mIsOn=3Dstate if( state ) t.SetInactive() else t.SetDisabled() } } function _IBP() { var t=3Dthis if( t.mIsOn ) { if( t.UserAction !=3D null ) t.UserAction() if( t.ChangeIcon ) { obj=3DGetObj(t.mObjId) if( t.ChangeIcon() ) obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-4)*t.mWidth else obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-0)*t.mWidth } t.SetActive() } =20 } function _IBUI( clr1,clr2,nextState ) { var t=3Dthis SetBorder( GetObj( t.mBorderId ),clr1,clr2 ) obj=3DGetObj( t.mObjId ) obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-nextState)*t.mWidth-obj= .style.posTop t.mCurState=3DnextState return obj } //----------------------------------------- function TxtBtn( oId,oeId,action,chkState ) //----------------------------------------- { var t=3Dthis t.Perform =3D _TBP t.SetActive =3D _TBSetA t.SetInactive=3D _TBSetI t.SetPressed =3D _TBSetP t.SetDisabled=3D _TBSetD t.SetEnabled =3D _TBSetE t.GetState =3D chkState t.UserAction =3D action t.ChgState =3D _TBUI t.mObjId =3D oId t.m_elementsId=3D oeId t.mIsOn =3D 1 } function _TBSetA() { var t=3Dthis if( t.mIsOn && !t.GetState() ) t.ChgState( gHiliteClr,gShadowClr,0,0 ) } function _TBSetI() { var t=3Dthis if( t.mIsOn && !t.GetState() ) t.ChgState( gFaceClr,gFaceClr,0,0 ) } function _TBSetP() { if( this.mIsOn ) this.ChgState( gShadowClr,gHiliteClr,1,1 ) } function _TBSetD() { =20 this.ChgState( gFaceClr,gFaceClr,0,0 ) this.mIsOn =3D 0 } function _TBSetE() { var t=3Dthis if( !t.GetState() ) t.ChgState( gFaceClr,gFaceClr,0,0 ) else t.ChgState( gShadowClr,gHiliteClr,1,1 ) t.mIsOn =3D 1 } function _TBP() { var t=3Dthis if( t.mIsOn ) {=20 if( t.UserAction !=3D null ) t.UserAction() if( !t.GetState ) return if( t.GetState() ) t.SetPressed() else t.SetActive() } =20 } function _TBUI( clr1,clr2,lOffset,tOffset ) { SetBorder( GetObj( this.mObjId ),clr1,clr2 ) Offset( GetObj( this.m_elementsId ),lOffset,tOffset ) } function Offset( obj, top, left ){ obj.style.top=3Dtop; obj.style.left=3Dle= ft } function SetBorder( obj, upperLeft, lowerRight ) { s=3Dobj.style; s.borderStyle =3D "solid" s.borderWidth =3D 1=20 s.borderLeftColor =3D s.borderTopColor =3D upperLeft s.borderBottomColor=3D s.borderRightColor =3D lowerRight } function GetBtnObj(){ return gBtnArr[window.event.srcElement.id] } function BtnOnOver(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetActive() } function BtnOnDown(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetPressed() } function BtnOnOut(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetInactive() } function BtnOnUp() { b=3DGetBtnObj() if( b !=3D null ) b.Perform() else Upd() } function GetNtsState(){ return parent.gNtsOpen } function GetOtlState(){ return parent.gOtlOpen } function GetOtlTxtState(){ return parent.gOtlTxtExp } function NtsBtnSetFlag( fVal ) { s=3Ddocument.all.item( this.m_flagId ).style s.display=3D"none" if( fVal ) s.display=3D"" else s.display=3D"none" } function _BSetA_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etActive() } function _BSetI_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etInactive() } function _BSetP_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etPressed() } function _BSetA_BorderImg() {=20 b =3D gBtnArr[this.mBorderId]=20 if( b !=3D null && this.mIsOn && !b.GetState() ) { obj=3Dthis.ChgState( gHiliteClr,gShadowClr,2 ) obj.style.posTop=3D0 } } function _BSetI_BorderImg() {=20 b =3D gBtnArr[this.mBorderId] if( b !=3D null && this.mIsOn && !b.GetState() ) { obj=3Dthis.ChgState( gFaceClr,gFaceClr,1 ) obj.style.posTop=3D0 } } var gHiliteClr=3D"THREEDHIGHLIGHT",gShadowClr=3D"THREEDSHADOW",gFaceClr=3D"= THREEDFACE" var gBtnArr =3D new Array() gBtnArr["nb_otl"] =3D new TxtBtn( "nb_otl","nb_otlElem",parent.ToggleOtlPan= e,GetOtlState ) gBtnArr["nb_otlElem"] =3D new TxtBtn( "nb_otl","nb_otlElem",parent.ToggleOt= lPane,GetOtlState ) gBtnArr["nb_nts"] =3D new ImgBtn( "nb_nts","nb_ntsBorder",10,parent.ToggleN= tsPane ) gBtnArr["nb_nts"].SetActive =3D _BSetA_BorderImg; gBtnArr["nb_nts"].SetInactive =3D _BSetI_BorderImg; gBtnArr["nb_ntsBorder"] =3D new TxtBtn( "nb_ntsBorder","nb_ntsElem",parent.= ToggleNtsPane,GetNtsState ) gBtnArr["nb_ntsElem"] =3D new TxtBtn( "nb_ntsBorder","nb_ntsElem",parent.To= ggleNtsPane,GetNtsState ) gBtnArr["nb_prevBorder"] =3D gBtnArr["nb_prev"]=3D new ImgBtn( "nb_prev","n= b_prevBorder",30,parent.GoToPrevSld ) gBtnArr["nb_nextBorder"] =3D gBtnArr["nb_next"]=3D new ImgBtn( "nb_next","n= b_nextBorder",30,parent.GoToNextSld ) gBtnArr["nb_sldshw"]=3D new ImgBtn( "nb_sldshw","nb_sldshwBorder",18,parent= .FullScreen ) gBtnArr["nb_sldshwBorder"] =3D new TxtBtn( "nb_sldshw","nb_sldshwBorder",pa= rent.FullScreen,null ) gBtnArr["nb_sldshwBorder"].SetActive =3D _BSetA_Border; gBtnArr["nb_sldshwBorder"].SetInactive =3D _BSetI_Border; gBtnArr["nb_sldshwText"] =3D new TxtBtn( "nb_sldshw","nb_sldshwText",parent= .FullScreen,null ) gBtnArr["nb_sldshwText"].SetActive =3D _BSetA_Border; gBtnArr["nb_sldshwText"].SetInactive =3D _BSetI_Border; gBtnArr["nb_voice"] =3D gBtnArr["nb_voiceBorder"] =3D new ImgBtn( "nb_voice= ","nb_voiceBorder",18,parent.ToggleVNarration ) gBtnArr["nb_otlTxtBorder"] =3D gBtnArr["nb_otlTxt"]=3D new ImgBtn( "nb_otlT= xt","nb_otlTxtBorder",23,parent.ToggleOtlText ) gBtnArr["nb_ntsBorder"].m_flagId=3D "nb_nts" gBtnArr["nb_ntsBorder"].SetFlag =3D NtsBtnSetFlag gBtnArr["nb_otlTxt"].ChangeIcon=3D GetOtlTxtState /********************************************* Context menu implementation _CM() is the function that's hooked up to the oncontextmenu event. Once we're asked to show the menu, we first build it by creating DIVs on-the-fly. Then we position it=20 within the screen area so it doesn't get clipped. Creating the DIVs using createElement() means we don't have to write out any extra HTML into the slide HTML files. **********************************************/ var sNext=3D"次へ",sPrev=3D"前へ",sEnd=3D"スライド ショーの終了",sFont=3D"= lＳ 明朝",sArrow=3D"矢印",sFreeform=3D"フリーフォーム",sRect=3D"四角形",sOv= al=3D"楕円" function ShowMenu() { BuildMenu(); var doc=3DPPTSld.document.body,x=3DPPTSld.event.clientX+doc.scrollLeft,y= =3DPPTSld.event.clientY+doc.scrollTop m =3D PPTSld.document.all.item("ctxtmenu") m.style.pixelLeft=3Dx if( (x+m.scrollWidth > doc.clientWidth)&&(x-m.scrollWidth > 0) ) m.style.pixelLeft=3Dx-m.scrollWidth m.style.pixelTop=3Dy if( (y+m.scrollHeight > doc.clientHeight)&&(y-m.scrollHeight > 0) ) m.style.pixelTop=3Dy-m.scrollHeight m.style.display=3D"" } function _CM() { if( !parent.IsFullScrMode() ) return; if(!PPTSld.event.ctrlKey) { ShowMenu() return false } else HideMenu() } function BuildMenu() { if( PPTSld.document.all.item("ctxtmenu") ) return var mObj=3DCreateItem( PPTSld.document.body ) mObj.id=3D"ctxtmenu" mObj.style.visibility=3D"hidden" var s=3DmObj.style s.position=3D"absolute" s.cursor=3D"default" s.width=3D"120px" SetCMBorder(mObj,"menu","black") var iObj=3DCreateItem( mObj ) SetCMBorder( iObj, "threedhighlight","threedshadow" ) iObj.style.padding=3D2 CreateMenuItem( iObj,sNext,M_GoNextSld,M_True ) CreateMenuItem( iObj,sPrev,M_GoPrevSld,M_HasPrevSld ) =09 CreateSeparator( iObj ) CreateMenuItem( iObj,sEnd,M_End,M_True ) mObj.style.visibility=3D"visible" } function Cancel() { window.event.cancelBubble=3Dtrue; window.event.returnVa= lue=3Dfalse } function Highlight() { ChangeClr("activecaption","threedhighlight") } function Deselect() { ChangeClr("threedface","menutext") } function Perform() { e=3DPPTSld.event.srcElement if( e.type=3D=3D"menuitem" && e.IsActive() ) e.Action() else PPTSld.event.cancelBubble=3Dtrue } function ChangeClr( bg,clr ) { e=3DPPTSld.event.srcElement if( e.type=3D=3D"menuitem" && e.IsActive() ) { e.style.backgroundColor=3Dbg e.style.color=3Dclr } } function M_HasPrevSld() { return( parent.HasPrevSld() ) } function M_GoNextSld() { if( gIsEndShow ) M_End(); else GoToNextSld() } function M_GoPrevSld() { if( gIsEndShow ) { gIsEndShow=3D0; history.back();= PPTSld.event.cancelBubble=3Dtrue; } else GoToPrevSld() } function M_True() { return true } function M_End() { window.close( self ) } function CreateMenuItem( node,text,action,eval ) { var e=3DCreateItem( node ) e.type=3D"menuitem" e.Action=3Daction e.IsActive=3Deval e.innerHTML=3Dtext if( !e.IsActive() ) e.style.color=3D"threedshadow" e.onclick=3DPerform e.onmouseover=3DHighlight e.onmouseout=3DDeselect s=3De.style; 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charset="shift_jis" データ分布と予測　5．仮説検定 ------=_NextPart_01C71D49.FEF73360 Content-Location: file:///C:/4ECB5C15/06dist_5.files/outline.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="shift_jis"
 ノ= ート
スラ= Cド ショー
アウトライン
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