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ุจุณู… ุงู„ู„ู‡ ุงู„ุฑุญู…ู† ุงู„ุฑุญูŠู… ุฅู† ุดุงุก ุงู„ู„ู‡ ู†ุณุชู…ุฑ ููŠ ุงู„ุญู„ู‚ุฉ
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ุงู„ุชุงุณุนุฉ 9 ุณุฃุจุฏุฃ ู…ุน ู…ูˆุถูˆุน ุงู„ุงุฎุชุตุงุฑุงุช ุงู„ุณูŠุงุณูŠุฉ
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ูˆุงู„ู‚ูŠู… ุงู„ุฎุงุตุฉ ููŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ ุณูŠูƒูˆู† ู‡ู†ุงูƒ ุฃุดูŠุงุก ูƒุซูŠุฑุฉ
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ูƒูŠู ู†ุณุชุฎุฏู… ู‚ูŠู… ุงู„ุงุฎุชุตุงุฑุงุช ุงู„ุณูŠุงุณูŠุฉ ุจุงู„ุฅุถุงูุฉ ุฅู„ู‰
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ูƒูŠู ู†ุณุชุฎุฏู… ุงู„ู‚ูŠู… ุงู„ุฎุงุตุฉ
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ุงู„ุขู† ุฅุฐุง ูƒุงู†ุช ุงู„ู…ูŠุฒุฉ ุงู„ุนุงู…ู„ุฉ ู‚ุฑูŠุจุฉ ู…ู† ู…ูŠุฒุฉ ุงู„ู…ุฌุชู…ุน
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ุงู„ู…ุตุทู„ุญุŒ ูู„ูŠุณ ุงู„ู…ูŠุฒุฉ ุงู„ุญู‚ูŠู‚ูŠุฉ ู…ูุชุฑุถุฉ ุฅุฐุง ุชุฐูƒุฑุŒ
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ู„ู„ู…ูŠุฒุฉ ุงู„ุญู‚ูŠู‚ูŠุฉ ู…ูŠุฒุฉ
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ุชู‚ูˆู„ ุฅุฐุง ูƒุงู†ุช ุงู„ู…ุนุงู…ู„ุฉ ู‚ุฑูŠุจุฉ
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ุจู…ุง ููŠู‡ ุงู„ูƒูุงุกุฉ ูƒุงููŠุฉ ู„ู„ู…ุนุงู…ู„ุฉ
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ุฐุง ู‡ุฐุง ูŠุนู†ูŠ ุฃู†ู‡ ุฅุฐุง ูƒุงู† ู‚ูŠู…ุฉ ุงู„ู…ูŠุฒุงู†ูŠุฉ ู‚ุฑูŠุจุฉ ุฌุฏู‹ุง
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ู…ู† ู…ูŠุฒุงู†ูŠุฉ ุงู„ุญูŠูˆุงู†ุงุชุŒ ูู„ู† ู†ู†ุฌุญ ู…ู† ู†ุงู„ ุงู„ุญูŠูˆุงู†ุงุช
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ุนู„ู‰ ุงู„ุงุชุตุงู„ ุงู„ุขุฎุฑุŒ ุฅุฐุง ูƒุงู†ุช ู…ูŠุฒุงู†ูŠุฉ ุงู„ุญูŠูˆุงู†ุงุช
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ุจุนูŠุฏุฉ ู…ู† ู…ูŠุฒุงู†ูŠุฉ ุงู„ุญูŠูˆุงู†ุงุช ุงู„ู…ุตุทู„ุญุฉุŒ ูู„ู† ู†ู†ุฌุญ ู…ู†
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ู†ุงู„ ุงู„ุญูŠูˆุงู†ุงุชุŒ ูู„ูˆ ูƒุงู†ุช ุจุนูŠุฏุฉ ุนู†ู‡ุŒ ูŠุนู†ูŠ ุนู„ู‰ ุณุจูŠู„
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ุงู„ู…ุซุงู„ ุฅุฐุง X ุจุงุฑ ูƒู…ุง ุฐูƒุฑู†ุง 4ุŒ ูุฅุฐุง X ุจุงุฑ ูƒุงู† 10 ู‡ู†ุง
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ูŠูˆุฌุฏ ูุฑู‚ ูƒุจูŠุฑ ุจูŠู† ู…ุตุฏุฑ ุงู„ูˆุซูŠู‚ุฉ ูˆ 30 ููŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ
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ู†ู†ู‚ุฐ ุงู„ู€ Hypothesis ุฏู„ุงู„ุฉ ุงู„ู€ Hypothesis
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is far enough to rejected the zero ูƒุฏู‡ ูŠูƒูˆู† ุงู„ูุฑู‚ ู…ุง
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ุจูŠู† ุงู„ู€ mean ู„ู„ู€ sample ูˆ ุงู„ู€ population ูŠุนู†ูŠ ูƒุฏู‡
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ูŠูƒูˆู† ุงู„ูุฑู‚ ู…ุง ุจูŠู†ู‡ู… ูƒุจูŠุฑ and we can reject null of
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it ูŠุนู†ูŠ ูƒุฏู‡ ูŠูƒูˆู† ุงู„ู…ุณุงูุฉ ุจูŠู†ู‡ู… ูƒุจูŠุฑุฉ ุนุดุงู† ุฃู‚ุฏุฑ ุฃู†
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ุฃุฑูุถ ุงู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ is how far is far enough ู‡ุฐุง
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ุงู„ู„ูŠ ุฅุญู†ุง ุจู†ุดูˆู ุนู„ูŠู‡ ู…ู† ุฎู„ุงู„ ุญุงุฌุฉ ุงุณู…ู‡ุง critical
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values ุงู„ู€ ุนู†ูˆุงู† ุงู„ุงุตุทู†ุงุนูŠ ู„ุชุฌุงุฑุจ
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ู…ุซู„ู‹ุงุŒ ู†ุญู† ู†ุชุญุฏุซ ุนู† ู…ุฌู…ูˆุนุฉ ุนุงู…ุฉุŒ ู‡ู†ุงูƒ ุงุชุฌุงู‡ุงุช
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ู…ุฎุชู„ูุฉุŒ ูˆุงุญุฏุฉ ุชุณู…ู‰ ู…ุฌู…ูˆุนุฉ ุงุชุฌุงู‡ุงุช ู„ุง ุงุชุฌุงู‡
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ูˆุงู„ุซุงู†ูŠุฉ ู…ุฌู…ูˆุนุฉ ุงุชุฌุงู‡ุงุช ู„ุง ุงุชุฌุงู‡
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ุชูƒูˆู† ู‡ู†ุงูƒ ุฃู…ุงู…ูŠู†
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ู…ุน ุฐู„ูƒ ูŠู…ูƒู† ุฃู† ูŠูƒูˆู†
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ุงู„ู„ุญุธุฉ ู‡ูŠ ุงู„ู€ mean ู…ุธุจูˆุท ุงู„ู€ region ู‡ุฏูˆู„ ู…ุง ู„ู‡ู… ุฃุจุนุงุฏ ุนู†
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population ุงู„ู€ mean ูุฅุฐุง ูƒุงู† ุฃู†ุง ู…ูˆุฌูˆุฏ ููŠ ุงู„ู€ .. ููŠ
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these regions ููŠ ุงู„ู€ rejection region then we
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reject the null hypothesis so suppose we are in
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these regions then we reject the null hypothesis
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now the question is how can we determine this
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region and the other one ู‡ุฐู‡ ุงู„ุณุคุงู„ ู„ู„ู…ุฌู„ุฏ ุงู„ูŠูˆู…
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ู‚ุจู„ ุฐู„ูƒ ุงุจุญุซ ุนู† ุงุชูุงู‚ุงุช ู…ุฎุชู„ูุฉ ุงุณู…ู‡ุง risk in
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decision making using hypothesis testing ู‡ู†ุงูƒ
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ุงุชูุงู‚ุงุช ู…ุฎุชู„ูุฉ ุฃูˆู„ ุงุชูุงู‚ุงุช ู…ุฎุชู„ูุฉ ุงุณู…ู‡ุง type one
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type
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one error ูŠุนู†ูŠ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„ ุงู„ู€ definition
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ุชุจุนู‡ ู„ู€ type one reject true null hypothesis type
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one reject h0 when it is true ุฅุฐุง
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ู‡ูŠ ุฃูˆู„ ุชุนุฑูŠู ูŠุฌุจ ุฃู† ุฃุนุฑูู‡ ุงู„ู„ูŠ ู‡ูˆ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน
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ุงู„ุฃูˆู„ ุงู„ู„ูŠ ู‡ูˆ ุนุจุงุฑุฉ ุนู† ุฑูุถ h0 ูˆู‡ูˆ ู…ุง ู‚ุงู„ู‡ ู‡ูˆ ุตุญูŠุญ
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ุฅุฐุง reject h0 when it is true it is type one
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error
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ุงู„ู€ type 1 error is a false alarm ูŠุทู„ู‚ ุนู„ูŠู‡ false
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alarm ูŠุนู†ูŠ ุชู†ุจูŠู‡ ุฃูˆ ุชุนุฐูŠุฑ ุฃู† ููŠ ุนู†ุฏูŠ ุฎุทุฃ ูุงู„ุฎุทุฃ
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ุนุจุงุฑุฉ ุนู† reject h0 when it's zero is true I mean when
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it is true I mean when it's zero is true ุฅุฐุง type
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one error it means rejection h0 when in fact
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it's h0 is true ุฅุฐุง type ุงู„ุฎุทุฃ ู…ู† ู†ูˆุน ุงู„ุฃูˆู„
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ู…ุนู†ุงู‡ ุฑูุถ ุงู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ ูˆู‡ูŠ ุฅูŠุด ูˆู‡ูŠ ุตุญูŠุญุฉ ุฅุฐุง
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ุฃู†ุง ุฏูŠ ุฃุจู‚ู‰ ุฑูุถ h0 ูˆู‡ูŠ ุตุญูŠุญุฉ ุฃู†ุง ุจุฑูุถ ุดูŠุก
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ุตุญ ู…ุน ูƒุฏู‡ we commit type one error ุงู„ู„ูŠ ุจุฑูุถ ุดูŠุก
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ุตุญ ู…ุน ูƒุฏู‡ ููŠ ุนู†ุฏู‡ ุฎุทุฃ ู…ุด ู‡ูŠูƒ ู†ุณู…ูŠู‡ type one error
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ุงู„ุนู†ูˆุงู† ุงู„ูˆุงู‚ุนูŠ ู„ู„ุฎุทุฃ ุงู„ูˆุงุญุฏ ู‡ูˆ Alpha ุงู„ูˆุงู‚ุนูŠ
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ู„ู„ุฎุทุฃ
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ุงู„ูˆุงุญุฏ ูŠุนู†ูŠ ุงุญุชู…ุงู„ ุงู„ูˆู‚ูˆุน ููŠ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„
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ู‡ุฐุง ุจู†ุณู…ูŠู‡ alpha ู‡ุฐุง pronounced as alpha ู‡ุฐุง
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Greek letter alpha ุฒูŠ ู…ูŠูˆ ูˆ ุฒูŠ ุณูŠุฌู…ุง Greek letter this
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alpha is called level
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of significance of the test
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ุงู„ูƒุจูŠุฑ ู…ุซู„ู‹ุง ู‡ู†ุง ู…ุณุชูˆู‰ ุงู„ู…ุนู†ูˆูŠุฉ ุฃูˆ ู…ุณุชูˆู‰ ุงู„ุฃู‡ู…ูŠุฉ
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ู†ุณู…ูŠู‡ุง alpha is level of significance ู‡ูŠ
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ู…ุณุชูˆู‰ ุงู„ู…ุนู†ูˆูŠุฉ this
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alpha is set by researcher in advance ุงู„ู„ูŠ ุจูŠุญุทู‡ุง
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ู„ู†ูุณุฉ ู…ู† ุงู„ุจุฏุงูŠุฉ ู„ุฐุง ุฃู†ุง ููŠ ุนูŠู†ูŠ ุชุนุฑูŠู ู…ู‡ู… ูˆู‡ุฐุง
101
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ุญุงุฌุฉ ุบุฑูŠุจุฉ ุดูƒู„ ูƒุจูŠุฑ it's called type one error ุงู„ู„ูŠ
102
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ู‡ูˆ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„ ุชุนุฑูŠูู‡ reject true null
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hypothesis it means we reject the null hypothesis
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00:08:28,440 --> 00:08:31,860
when in fact it is true ูŠุนู†ูŠ ุจุฑูุถู‡ ูˆููŠ ุงู„ูˆุงู‚ุน
105
00:08:31,860 --> 00:08:36,420
ู…ุนู‡ ุตุญ ู„ูˆ ุจุฑูุถ ุดูŠุก ุตุญ ู…ุน ูƒุฏู‡ ูุนู†ุฏูŠ ุฎุทุฃ ู‡ุฐุง ุฎุทุฃ
106
00:08:36,420 --> 00:08:42,820
ุจุณู…ูŠู‡ ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„ type one error ุงู„ุณุคุงู„
107
00:08:42,820 --> 00:08:45,580
ุงู„ุซุงู†ูŠ ู‡ูˆ ุงุญุชู…ุงู„ ุงู„ูˆู‚ูˆุน ููŠ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„
108
00:08:45,580 --> 00:08:49,800
ุจุงุณู…ู‡ Alpha ุฅุฐุง ุงุญุชู…ุงู„ ู‡ุฐุง ุงู„ุฎุทุฃ ู‡ูˆ ุงุญุชู…ุงู„ ุงู„ูˆู‚ูˆุน
109
00:08:49,800 --> 00:08:52,840
ููŠ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„ ุจุงุณู…ู‡ Alpha ุฅุฐุง Alpha
110
00:08:52,840 --> 00:09:01,700
ุนุจุงุฑุฉ ุนู† ุงุญุชู…ุงู„ ุงู„ูˆู‚ูˆุน ููŠ ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„
111
00:09:01,700 --> 00:09:05,700
ู…ุงู‡ูˆ ู‚ูŠู…ุฉ AlphaุŸ
112
00:09:10,610 --> 00:09:14,630
ุงู„ู‚ูŠู…ุฉ Alpha ุจูŠุญุทู‡ุง ุงู„ุจุงุญุซ ููŠ ุงู„ุจุฏุงูŠุฉ Do you think
113
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Alpha is large or smallุŸ ุฃุชูˆู‚ุน Alpha ุชูƒูˆู† ุตุบูŠุฑุฉ ูˆู„ุง
114
00:09:19,050 --> 00:09:22,550
ูƒุจูŠุฑุฉุŸ ู„ุงุฒู… ุชูƒูˆู† ุตุบูŠุฑุฉ ู„ุฅูŠุดุŸ ู„ุฅู† ุฅุญู†ุง we reject
115
00:09:22,550 --> 00:09:27,290
true null ุจุฑูุถ ุดูŠุก ุตุญ ู…ุง ุจู‚ู‰ ูƒุฏู‡ ุจุชุฎู„ูŠ ุฎุทุฃ
116
00:09:27,290 --> 00:09:32,390
ุฃุนู…ุงู„ู‡ ุตุบูŠุฑุฉ ูุจุงู„ุชุงู„ูŠ Alpha should be small the
117
00:09:32,390 --> 00:09:34,230
other error is called type 2 error
118
00:09:40,130 --> 00:09:44,430
ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุซุงู†ูŠ ุงู„ู€ complement ุชุจุน type 1 error
119
00:09:44,430 --> 00:09:48,210
ุงู„ู€ ู…ูƒู…ู„ ุฅูŠู‡ ู„ู‡ุŸ ุฅูŠุด ุงู„ู€ type 1 errorุŸ reject
120
00:09:48,210 --> 00:09:52,190
true null hypothesis ุงู„ุซุงู†ูŠ ุฅูŠุด ู…ูƒุชูˆุจ ุนู„ูŠู‡ุŸ
121
00:09:52,190 --> 00:09:55,850
failure to reject false null hypothesis ุงู„ู„ุญุธุฉ ุนูƒุณู‡
122
00:09:55,850 --> 00:09:59,850
ุชู…ุงู…ู‹ุง ู‡ู†ุง ุจู†ุญูƒูŠ reject ุงู„ุซุงู†ูŠ ุฅูŠุด ู…ูˆุฌูˆุฏุŸ failure
123
00:09:59,850 --> 00:10:03,090
to .. ุฅูŠุด ู…ุนู†ุงู‡ failure to rejectุŸ ูุดู„ุŒ ุนุฏู… ุฑูุถ
124
00:10:05,790 --> 00:10:10,210
failure to reject ู‡ู†ุง ุฅูŠุด ูƒุงู† true ุฅูŠุด ุตุงุฑ false
125
00:10:10,210 --> 00:10:15,670
ุฅุฐุง ุงู„ุงุซู†ูŠู† ู…ูƒู…ู„ุงุช ู„ุจุนุถ ุฅุฐุง failure to reject
126
00:10:15,670 --> 00:10:22,670
false ู†ู„ุนุจ false ู†ุณู…ูŠู‡ type two error ุฅุฐุง ุงู„ุนูƒุณ
127
00:10:22,670 --> 00:10:24,930
ุงู„ู„ูŠ ู‡ู†ุง ุจุฏู„ ู…ุง ุฃุญูƒูŠ reject ุฃุญูƒูŠู‡ุงุด failure
128
00:10:24,930 --> 00:10:34,580
failure to reject h0 ูŠุนู†ูŠ you can say just
129
00:10:34,580 --> 00:10:38,520
accept but it's better to say failure to reject so
130
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we are usually we prefer to say failure to reject
131
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or don't reject don't say accept ุฒูŠ ู…ุง ุจู†ุญูƒูŠ ุฏุงุฆู…ู‹ุง
132
00:10:46,720 --> 00:10:51,020
ุนุฏู… ุฑูุถ ู…ุง ุจู†ุญูƒูŠุด ู‚ุจูˆู„ ุฅุฐุง failure to reject is
133
00:10:51,020 --> 00:10:57,320
h0 when it is false when it's h0 is false ูŠุนู†ูŠ
134
00:10:57,320 --> 00:11:03,970
ู…ุด ู…ุนู†ุงู‡ ุนุฏู… ู…ุด ู„ุงุญุธ ู‡ู†ุง ู…ุด ู…ูˆุฌูˆุฏ ุฑูุถ ุฅูŠุด ุจูŠุตูŠุฑ ุนุฏู…
135
00:11:03,970 --> 00:11:11,590
ุฑูุถู‡ ุนุฏู… ุฑูุถ ุงู„ู€ h0 ูˆู‡ูŠ ุฎุงุทุฆุฉ ุฃู†ุง ุจุฑูุถุด ุดูŠุก ุบู„ุท
136
00:11:11,590 --> 00:11:17,770
ุจุฑูุถุด ูŠุนู†ูŠ ุจู‚ุจู„ ุดูŠุก ุฎุทุฃ ู…ุน ูƒู„ ูุนู„ ุฏู‡ ุบู„ุท ุฅุฐุง when
137
00:11:17,770 --> 00:11:19,930
we don't reject the null hypothesis when the fact
138
00:11:19,930 --> 00:11:24,690
is false it means we commit type 2 error ูˆุงุถุญ ู„ู…ุง
139
00:11:24,690 --> 00:11:31,690
ุจุฑูุถุด ุดูŠุก ุบู„ุท ูˆู‚ุนุช ุฎุทุฃ this error is called type 2
140
00:11:31,690 --> 00:11:37,620
error ู‡ูŠ ุฃุณูˆุฃ ู…ู† ุงู„ุฏู…ุงุบ ุงู„ู€ type 1ุŸ ู‡ู…ุง ุงู„ุงุซู†ูŠู† ุนูƒุณ
141
00:11:37,620 --> 00:11:42,460
ุจุนุถ ุฅุญู†ุง ู‡ู†ุฑูƒุฒ ุนู„ู‰ ูˆุงุญุฏ ู…ู†ู‡ู… ุจุนุฏ ุดูˆูŠุฉ ุงู„ู€
142
00:11:42,460 --> 00:11:46,800
probability of type two error is beta
143
00:11:46,800 --> 00:11:56,400
ูŠู†ุทู‚ beta ู…ุด beta ุงู„ู€ probability ุงู„ู€ probability
144
00:11:56,400 --> 00:12:08,750
of type two error ู‡ู†ุง ูƒู†ุง ู†ุณู…ูŠู‡ุง alpha ู‡ูŠ ุชูƒุชุจ beta
145
00:12:08,750 --> 00:12:16,310
ุจุณ ุชูƒุชุจ beta ู‡ูŠูƒ ุจุณ ูŠู†ุทู‚ beta ู…ุง ููŠุด ุญุงุฌุฉ ุงุณู…ู‡ุง
146
00:12:16,310 --> 00:12:21,270
beta ููŠ ุงู„ู€ curriculum beta, theta and so on ุฅุฐุง
147
00:12:21,270 --> 00:12:24,090
there are two types of error one is called type
148
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one type one it means we reject true null
149
00:12:29,170 --> 00:12:33,910
hypothesis ู†ุฑูุถ ุงู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ ุตุญ ุจุงู„ู†ุณุจุฉ ู„ู„ู€
150
00:12:33,910 --> 00:12:36,050
Probability ุชุจุน ุงู„ู€ Type I Error ุชุณู…ู‰ Alpha ูˆ
151
00:12:36,050 --> 00:12:39,050
Alpha ุชุณู…ู‰ Level of Significance ุงู„ู€ Type II Error
152
00:12:39,050 --> 00:12:43,290
ูŠุนู†ูŠ ุฃู†ู†ุง ู„ุง ู†ุฑูุถ false null hypothesis ูˆ
153
00:12:43,290 --> 00:12:48,690
Probability ู†ุณู…ูŠู‡ุง Beta ู‡ุฐูˆู„ ุงู„ู€ Two Types Of Error
154
00:12:48,690 --> 00:12:57,270
ุงู„ุขู† ู‡ุฐุง ุงู„ูƒู„ุงู… ูŠู…ุซู„ ุญุงู„ุฉ ุงู„ุชุฑุฌู…ุฉ ุฃูˆ ู„ุง ุชุฑุฌู…ุฉ ุงู„ุขู†
155
00:12:57,270 --> 00:13:07,290
ู‚ุฑุงุฑ ุชุจุนู†ุง either don't reject ุฃูˆ reject ุงู„ูˆุถุน
156
00:13:07,290 --> 00:13:13,990
ุงู„ุญู‚ูŠู‚ูŠ ุฅู…ุง H0 ู‡ูˆ ุตุญ ุฃูˆ H0 ู‡ูˆ ุฎุงุทุฆ ุฅุฐุง H0 ูƒุงู†ุช ุตุญ
157
00:13:13,990 --> 00:13:23,330
ุฃูˆ ุฎุงุทุฆุฉ ู‚ุฑุงุฑูŠ ุฅู…ุง ุนุฏู… ุฑูุถ ุฃูˆ ุฑูุถ ู†ู…ุณูƒ
158
00:13:23,330 --> 00:13:27,690
ูˆุงุญุฏ ูˆุงุญุฏ ู„ูˆ ุญูƒูŠุช don't reject h0 when it is
159
00:13:27,690 --> 00:13:34,630
true ุจุฑูุถุด ุดูŠุก ุตุญูŠุญ ูŠุนู†ูŠ ุจู‚ุจู„ ุดูŠุก ุตุญูŠุญ ู…ุนู†ุงู‡ ุฅูŠุดุŸ no
160
00:13:34,630 --> 00:13:40,070
error ุฅุฐุง ู‡ุฐุง correct decision ุฅุฐุง ู‡ุฐุง correct
161
00:13:40,070 --> 00:13:49,310
ูŠุนู†ูŠ ู‚ุฑุงุฑ ู…ุง ู‡ูˆ ุตุญูŠุญ ุฅุฐุง don't reject h0 when
162
00:13:49,310 --> 00:13:53,770
fact it is true it means correct decision ู‚ุฑุงุฑ
163
00:13:53,770 --> 00:14:02,340
ุตุญูŠุญ ุฎู„ุงุต ุจุฑุถู‡ ู„ู…ุง ุจุญูƒูŠ rejected h0 when it is
164
00:14:02,340 --> 00:14:09,940
false ุจุฑูุถ ุดูŠุก ุฎุทุฃ ุฃู†ุง ุจุฑูุถ ุดูŠุก ุบู„ุท ู‚ุฑุงุฑ ุตุญ ูˆู„ุง ..
165
00:14:09,940 --> 00:14:17,240
ูˆู„ุง .. ุฅุฐุง ู‡ุฐุง ุตุญ ุฅุฐุง ู‡ุฐุง correct decision ุฅุฐุง
166
00:14:17,240 --> 00:14:23,200
ุงู„ู‚ุฑุงุฑ ุณู„ูŠู… ุจูŠุฌูŠ ููŠ ุญุงู„ุชูŠู† ุฅู…ุง ุนุฏู… ุฑูุถ ุดูŠุก ุตุญูŠุญ ุฃูˆ
167
00:14:23,200 --> 00:14:27,580
ุฑูุถ ุดูŠุก ุฎุงุทุฆ ู…ุธุจูˆุท ู‡ุฏูˆู„ ุงุซู†ูŠู† correct decision ุนูƒุณ
168
00:14:27,580 --> 00:14:31,100
ุงู„ู„ูŠ ูุงุชูˆุง ู„ุฃู† ุงู„ู€ type one error ุจูŠุฌูŠ ู…ู† ูˆูŠู† ู†ู‚ุฑุฃ
169
00:14:31,100 --> 00:14:35,300
ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ
170
00:14:35,300 --> 00:14:37,660
ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ
171
00:14:37,660 --> 00:14:37,740
ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ
172
00:14:37,740 --> 00:14:37,940
ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ
173
00:14:37,940 --> 00:14:38,620
ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ
174
00:14:38,620 --> 00:14:53,720
ู†ู‚ุฑุฃ ู…ู† ู‡ู†ุงูƒ ู†ู‚ุฑุฃ ู…ู†
175
00:14:53,720 --> 00:14:57,310
ู‡ู†ุงูƒ ู‡ุฐูˆู„ ุงุซู†ูŠู† complement ุฅุฐุง ู‡ุฐู‡ alpha ุฅูŠุด ุจุชูƒูˆู†
176
00:14:57,310 --> 00:15:02,030
ุงู„ูˆุงุญุฏ ู†ุงู‚ุต alpha ุฅุฐุง ู‡ุฐู‡ beta ุงู„ุซุงู†ูŠุฉ ูˆุงุญุฏ ู†ุงู‚ุต
177
00:15:02,030 --> 00:15:06,150
beta ุชู…ุงู… ุฃุญุณู† ูˆุงุญุฏุฉ ููŠู‡ู… ูŠุนู†ูŠ ุงู„ู€ power ู„ู„ู€ test
178
00:15:06,150 --> 00:15:11,490
ุจุชูƒูˆู† ู…ู† ุฌุงูŠุฉ ู„ู…ุง we reject ุดูŠุก ุฎุทุฃ ู…ุธุจูˆุท ู„ู…ุง ุจุฑูุถ
179
00:15:11,490 --> 00:15:15,470
ุดูŠุก ุบู„ุท ู…ุน ูƒุฏู‡ ููŠ ุนู†ุฏูŠ ู‚ูˆุฉ ุฅุฐุง probability h0
180
00:15:15,470 --> 00:15:21,090
when we reject h0 when it is false it's called
181
00:15:22,520 --> 00:15:26,500
ุงู„ู€ Power ุงู„ู€ Power ู„ู„ุชุณุช ุนุจุงุฑุฉ ุนู† 1-ฮฒ ู‚ูˆุฉ
182
00:15:26,500 --> 00:15:30,660
ุงู„ุงุฎุชุจุงุฑ ุจุชูŠุฌูŠ ู…ู† ุฎู„ุงู„ ุฑูุถูƒ ู„ู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ ูˆู‡ูŠ
183
00:15:30,660 --> 00:15:43,440
ุฅูŠุด ุงู„ู€ power ู…ุนู†ุงู‡ุง reject h0 when it is
184
00:15:43,440 --> 00:15:51,060
false ุงู„ู€ probability ุงู„ู„ูŠ ู‡ูŠ 1-ฮฒ ู‡ูŠ ุจุชุณู…ูŠู‡ุง ุงู„ู€
185
00:15:51,060 --> 00:15:55,370
power ู„ู„ุชุณุช ุฅุฐุง ุงู„ู€ power ู„ู„ู€ test ุนุจุงุฑุฉ ุนู† one minus
186
00:15:55,370 --> 00:16:01,390
beta ุฅูŠุด betaุŸ ู‡ูŠ beta ุงู„ู„ูŠ ู‡ูŠ probability of type
187
00:16:01,390 --> 00:16:04,210
two error type two error ุนุจุงุฑุฉ ุนู† failure to
188
00:16:04,210 --> 00:16:08,750
reject h0 when it is false ุฎู„ุงุต ุฅุฐุง ุฏูˆู„
189
00:16:08,750 --> 00:16:13,750
ุงู„ุฃุฑุจุน ุญุงุฌุงุช ู„ุงุฒู… ุฃุนุฑูู‡ู… ููŠ ุนู†ุฏูŠ correct decision
190
00:16:13,750 --> 00:16:16,490
either don't reject h0 when it is true or
191
00:16:16,490 --> 00:16:20,070
reject h0 when it is false Type 1 Error ูŠุนู†ูŠ
192
00:16:20,070 --> 00:16:24,290
ุฅู†ู‡ ู…ุฌุฑุฏ ุฅ
216
00:17:54,330 --> 00:18:00,310
alpha equal five percent ุงู„
217
00:18:00,310 --> 00:18:05,530
one minus alpha ุฅูŠุด ู‡ุชุณุงูˆูŠ 95% ุงู„ู„ูŠ ู‡ูŠ ูˆุงุญุฏ ู†ุงู‚ุต
218
00:18:05,530 --> 00:18:07,550
ุฎู…ุณุฉ ููŠ ุงู„ู…ูŠุฉ ุงู„ู„ูŠ ู‡ูŠ ุงู„ู€ complement ุงู„ู„ูŠ ู‡ูŠ
219
00:18:07,550 --> 00:18:10,150
probability of not rejecting zero when it is true
220
00:18:10,150 --> 00:18:14,210
The confidence level of a hypothesis test is one
221
00:18:14,210 --> 00:18:17,250
minus alpha times one hundred percent ู„ูˆ ุฃุทู„ุน ู†ุณุจุฉ
222
00:18:17,250 --> 00:18:22,960
ุงู„ู…ุฆูˆูŠุฉ ุฅูŠุด ุจุฃุนู…ู„ุŸ ุจุงุฌูŠ ู‡ุฐู‡ ู…ุงุฐุง ุจุนู…ู„ ููŠู‡ุงุŸ ุจุถุฑุจู‡ุง
223
00:18:22,960 --> 00:18:27,100
ููŠ 100 ูุชุทู„ุน ู…ุนุงูŠุง ุฅูŠุดุŸ ุฅุฐุง ุจุญูƒูŠ point nine five
224
00:18:27,100 --> 00:18:32,760
ูƒูŠู ุชุทู„ุน ู†ุณุจุงู„ูŠ ุงู„ู…ุฆูˆูŠุฉุŸ ุชุถุฑุจูŠู‡ุง ููŠ 100 ูู‡ุฐุง ุญุณุงุจ
225
00:18:32,760 --> 00:18:37,960
95% ู‡ุฐู‡ ุจู†ุณู…ูŠู‡ุง the confidence level ูŠุนู†ูŠ ุฅูŠุดุŸ
226
00:18:37,960 --> 00:18:44,380
ู…ุณุชูˆู‰ ุงู„ุซู‚ุฉ ุฅุฐุง ุฅุฐุง ูƒุงู† ุงู„ุฎุทุฃ 5% ุงู„ุซู‚ุฉ ุฅูŠุด ุจุชูƒูˆู†ุŸ
227
00:18:44,380 --> 00:18:50,200
95 ู‡ูŠ ุงู„ู€ complement ุจุชุงุนุชู‡ุง ุฅุฐุง ุฅุฐุง Alpha ุงู„ู„ูŠ ู‡ูŠ
228
00:18:50,200 --> 00:18:54,680
ุชุนุฑูŠูู‡ุง ู…ุฑุฉ ุซุงู†ูŠุฉ Alpha probability of type one
229
00:18:54,680 --> 00:18:57,900
error ูŠุนู†ูŠ Alpha ุนุจุงุฑุฉ ุนู† probability of rejecting
230
00:18:57,900 --> 00:19:01,260
zero when it is true ูุงู„ู€ one minus Alpha ุนุจุงุฑุฉ ุนู†
231
00:19:01,260 --> 00:19:03,640
probability of not rejecting zero when it is true
232
00:19:03,640 --> 00:19:08,420
ุงู„ู€ one minus Alpha is called confidence level
233
00:19:08,420 --> 00:19:11,860
ู…ุณุชูˆู‰ ุงู„ุซู‚ุฉ ูู„ูˆ Alpha is one percent it means one
234
00:19:11,860 --> 00:19:15,680
minus Alpha is nine nine percent and so on the
235
00:19:15,680 --> 00:19:19,700
power of a statistical power ุงู„ู‚ูˆุฉ ุงู„ุงุฎุชุจุงุฑ ุงู„ู„ูŠ
236
00:19:19,700 --> 00:19:23,180
ุญูƒูŠุช ุนู„ูŠู‡ุง ุนุจุงุฑุฉ ุนู† ู…ูŠู† one minus beta is a
237
00:19:23,180 --> 00:19:26,140
probability of rejecting a zero when it is false
238
00:19:26,140 --> 00:19:30,320
ุงู„ู„ูŠ ูƒุงู†ุช ุฃุฎุฑ ุญุฏุซ ููŠ ุงู„ุฌุฏูˆู„ ู„ูŠู‡ุง ุฏูŠ rejected zero
239
00:19:30,320 --> 00:19:33,260
when it is false is called the power of the test
240
00:19:33,260 --> 00:19:36,780
ุฅุฐุง ุงู„ู€ power ุนุจุงุฑุฉ ุนู† rejected zero when in fact
241
00:19:36,780 --> 00:19:41,340
it is false ุจุฑูุถ ุดูŠุก ุบู„ุท ู‡ุฐุง ุนุจุงุฑุฉ ุนู† ู‚ูˆุฉ ุงู„ุงุฎุชุจุงุฑ
242
00:19:41,340 --> 00:19:46,990
ู‡ุฏูˆู„ definitions ุงู„ู„ูŠ ุฃุนุฑููŠู‡ู… ุงู„ุขู† ู‡ู†ุนุทูŠ ููŠ two
243
00:19:46,990 --> 00:19:50,470
slides ุงู„ู€ relationship between type 1 and type 2
244
00:19:50,470 --> 00:19:53,830
errors ุงู„ุนู„ุงู‚ุฉ ู…ุง ุจูŠู† ุงู„ุฎุทุฃ ู…ู† ุงู„ู†ูˆุน ุงู„ุฃูˆู„ ูˆ ุงู„ุฎุทุฃ ู…ู†
245
00:19:53,830 --> 00:19:54,750
ุงู„ู†ูˆุน ุงู„ุซุงู†ูŠ
246
00:20:14,190 --> 00:20:17,270
ุงู„ู€ type 1 ูˆ ุงู„ู€ type 2 ู„ุง ูŠู…ูƒู† ุฃู† ูŠุญุฏุซูˆุง ููŠ ู†ูุณ
247
00:20:17,270 --> 00:20:21,250
ุงู„ูˆู‚ุช ุงู„ุงุซู†ูŠู† ู„ุง ูŠุญุฏุซูˆุง ู…ุน ุจุนุถ ุงู„ุณุจุจ ู„ูˆ ุทู„ุนุช ุนู„ู‰
248
00:20:21,250 --> 00:20:26,390
ุงู„ู€ definitions ุงู„ู€ type 1 error ู„ุง ุชู†ุฌุญ ููŠ ุงู„ู€
249
00:20:26,390 --> 00:20:30,770
zero ูˆ ุงู„ู€ true ุงู„ู€ type 2 error ุฅุฐุง ู‡ูŠ ุงู„ู€ type 1
250
00:20:30,770 --> 00:20:35,150
ุชู†ุฌุญ ููŠ ุงู„ู€ zero ูˆ ุงู„ู€ true ุงู„ู€
251
00:20:35,150 --> 00:20:39,450
type 2 ุนูƒุณู‡ ู„ุญุธุฉ ุจู†ุญูƒูŠ ุชู†ุฌุญ ููŠ ุงู„ู€ zero ูˆ ุงู„ู€ true
252
00:20:39,450 --> 00:20:43,580
ุงู„ุซุงู†ูŠ ุนุจุงุฑุฉ ุนู† ุฅูŠุดุŸ don't reject a zero when it is
253
00:20:43,580 --> 00:20:47,360
false ุฅุฐุง ู‡ุฐูˆู„ ุงุซู†ูŠู† ู…ุง ูŠุญุฏุซูˆุด ู…ุน ุจุนุถ ุฅุฐุง type one
254
00:20:47,360 --> 00:20:53,820
and type two errors ู†ุนู… ู…ุด ุตุญูŠุญ ูŠุนู†ูŠ ู…ู…ูƒู†ุด ุฃุฑูุถ ูˆ
255
00:20:53,820 --> 00:20:59,180
ุฃู‚ุจู„ ููŠ ู†ูุณ ุงู„ู„ุญุธุฉ ู…ุธุจูˆุท
256
00:20:59,180 --> 00:21:02,420
ู‡ูŠูƒ ุฅุฐุง type one and type two errors cannot happen
257
00:21:02,420 --> 00:21:08,090
at the same time ุงู„ุณุจุจ ุฒูŠ ุฒู…ูŠู„ุชูƒ ุจุญูƒุช type 1 error
258
00:21:08,090 --> 00:21:12,930
can only occur if its 0 is true ู…ุธุจูˆุท type 1
259
00:21:12,930 --> 00:21:17,950
rejects 0 when it is true type 2 can only occur if
260
00:21:17,950 --> 00:21:21,930
its 0 is false ุงู„ู„ูŠ ู‡ูŠ we don't reject its 0 when
261
00:21:21,930 --> 00:21:26,050
it is false for this reason type 1 and 2 error
262
00:21:26,050 --> 00:21:31,750
cannot happen at the same time ู„ุฃู† ููŠ ูˆุงุญุฏ ุจูŠุญุฏุซ
263
00:21:31,750 --> 00:21:35,670
ู„ู…ุง H0 ุชูƒูˆู† ุตุญูŠุญุฉ ูˆ ุงู„ุซุงู†ูŠ ุจูŠุญุฏุซ ุฅุฐุง ูƒุงู†ุช ุงู„ู€ 0 ุฎุงุทุฆุฉ
264
00:21:35,670 --> 00:21:39,790
ูˆุจุงู„ุชุงู„ูŠ ุญุฏูˆุซู‡ู… ู…ุน ุจุนุถ ุจูŠูƒูˆู† conflict of interest
265
00:21:39,790 --> 00:21:43,190
ู…ูˆุฌูˆุฏุด ู…ุน ุจุนุถ ูุจุงู„ุชุงู„ูŠ ู…ุด ู…ู…ูƒู† ูŠุญุฏุซ ุฃู† ุงู„ู€ type I ุฃูˆ
266
00:21:43,190 --> 00:21:45,470
ุงู„ู€ type II error happened at the same time
267
00:21:45,470 --> 00:21:49,990
furthermore if type I error probability ฮฑ
268
00:21:49,990 --> 00:21:53,950
increases ุฅุฐุง Alpha ุฒุงุฏุช ุงู„ู€ type II error
269
00:21:53,950 --> 00:21:59,150
probability decreases ูŠุนู†ูŠ ุฅุฐุง type I error ุฒุงุฏ ุงู„ู€
270
00:21:59,150 --> 00:22:03,630
1- ฮฒ ุงู„ู€ Beta ู†ูุณู‡ุง ู…ุงู„ู‡ุง ุจุชู‚ู„ ูŠุนู†ูŠ ููŠ ุนู„ุงู‚ุฉ ุนูƒุณูŠุฉ
271
00:22:03,630 --> 00:22:06,230
ู…ุง ุจูŠู† ุงู„ุงุซู†ูŠู† ุฅุฐุงู‹ there is inverse relationship
272
00:22:06,230 --> 00:22:08,810
between type 1 and type 2 here ุฅุฐุงู‹ if Alpha
273
00:22:08,810 --> 00:22:13,770
increases Beta ู…ุงู„ู‡ุง decreases ุทุจ ุฃุญูƒูŠ Alpha
274
00:22:13,770 --> 00:22:23,370
ุจุงู„ุฒูŠุงุฏุฉ ุงู„ู€ Beta ู…ุงู„ู‡ุง ุจุชู‚ู„ ุทุจ ุงู„ู€ 1-Beta ู„ู…ุง ุจุญูƒูŠ
275
00:22:23,370 --> 00:22:32,020
Beta ู†ู‚ุตุชุงู„ู‡ุง ูˆุงุญุฏ ู†ุงู‚ุต ุจูŠุชุง ู…ุงู„ู‡ ุจูŠุฒูŠุฏ ุทุจุนุง ู…ุด ุนู†ุฏูƒ
276
00:22:32,020 --> 00:22:35,140
ูˆุงุญุฏ ู†ุงู‚ุต ุจูŠุชุง ูŠุนู†ูŠ ุชุฎูŠู„ูŠ ุจูŠุชุง ุจุชุณุงูˆูŠ ุงุซู†ูŠู† ู…ู†
277
00:22:35,140 --> 00:22:40,600
ุงู„ู…ูŠุฉ ุฅูŠุด ูˆุงุญุฏ ู†ุงู‚ุต ุจูŠุชุง ุฃูŠ ุจูŠุชุง one minus ุจูŠุชุง ู„ูˆ
278
00:22:40,600 --> 00:22:46,540
ู‡ุงุฏ ุจุงุซู†ูŠู† ุฅูŠุด ู‡ุชูƒูˆู† ู„ูˆ ู‡ุงุฏ ุจุชู„ุงุชุฉ ู„ูˆ ู‡ุงุฏ ุจู‚ู‰
279
00:22:46,540 --> 00:22:52,310
ุฃุฑุจุนุฉ ู…ุง ุนูƒุฏุง ูƒู„ beta ู…ุง ุจูŠุฒูŠุฏ ุงู„ู€ one minus beta
280
00:22:52,310 --> 00:22:56,450
ู…ุงู„ู‡ ุจูŠู‚ู„ ุนู„ุงู‚ุฉ ุนูƒุณูŠุฉ ุจูŠู†ู‡ู… ูุงู„ู€ beta ุงู„ู„ูŠ ู…ุง ุจุชู‚ู„
281
00:22:56,450 --> 00:23:00,930
ุงู„ู€ one minus beta ู…ุงู„ู‡ุง ุจูŠุฒูŠุฏ ุฅุฐุง alpha ุจูŠุฒูŠุฏ ูˆ
282
00:23:00,930 --> 00:23:07,930
beta ู…ุงู„ู‡ุง ุจุชู‚ู„ ู‡ุฐุง ูˆุงุญุฏ all else equal beta
283
00:23:07,930 --> 00:23:12,930
decreases ูˆูƒุชุด ุงู„ู€ beta ุจูŠุฒูŠุฏ ุฅูŠุด ุงู„ู€ beta ุงู„ู„ูŠ ู‡ูŠ
284
00:23:12,930 --> 00:23:18,070
don't reject zero when .. ุฎู„ูŠู†ูŠ ุฃูƒุชุจ ุจุชุงุนุชู‡ุง ู‡ูŠ ุงู„ู€
285
00:23:18,070 --> 00:23:29,870
beta fail or failure to reject its zero when it is
286
00:23:29,870 --> 00:23:34,650
false failure to reject when it is false ุจุญูƒูŠ beta
287
00:23:34,650 --> 00:23:40,390
increases ูŠุนู†ูŠ ุนุฏู… ุฑูุถูƒ ู„ู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ ูˆ ู‡ูŠ ุบู„ุท
288
00:23:41,780 --> 00:23:46,540
ู‡ุฐุง ุจูŠุฒูŠุฏ ุงุญุชู…ุงู„ ุนุฏู… ุฑูุถูƒ ู„ุดูŠุก ุฎุงุทุฆ ุจูŠุฒูŠุฏ ู‡ุฐุง ุจูŠุญุฏุซ
289
00:23:46,540 --> 00:23:49,540
ููŠ ุขู† when the difference between the hypothesized
290
00:23:49,540 --> 00:23:53,880
parameter and true parameter decreases ู„ู…ุง ูŠูƒูˆู†
291
00:23:53,880 --> 00:23:59,560
ุงู„ูุฑู‚ ู…ุง ุจูŠู† beta ุจูŠุฒูŠุฏ ุงู„ุฎุทุฃ ู‡ุฐุง ุจูŠุฒูŠุฏ ุงู„ู„ูŠ ู‡ูˆ ุฑูุถูƒ
292
00:23:59,560 --> 00:24:02,620
ุนุฏู… ุฑูุถูƒ ู„ู„ูุฑุถูŠุฉ ุงู„ุตูุฑูŠุฉ ูˆู‡ูŠ ููŠ ุงู„ูˆุงู‚ุน ุฎุงุทุฆุฉ ู‡ุฐุง
293
00:24:02,620 --> 00:24:05,800
ุจูŠุฒูŠุฏ ู„ู…ุง ุงู„ูุฑู‚ between ุงู„ู€ hypothesized parameter
294
00:24:05,800 --> 00:24:10,640
and true value decreases ูŠุนู†ูŠ ูƒูŠู ุชุฐูƒุฑ ุญูƒูŠู†ุง mu
295
00:24:10,640 --> 00:24:18,160
equal to 30 ู‡ุฐู‡ ู†ุณู…ูŠู‡ุง 30 hypothesized parameter ู‡ุฐู‡
296
00:24:18,160 --> 00:24:23,420
ู†ุณู…ูŠู‡ุง hypothesized parameter
297
00:24:23,420 --> 00:24:27,780
ูˆุงู„ู€
298
00:24:27,780 --> 00:24:35,060
x bar equal for example is 26 ุจู†ุณู…ูŠู‡ุง ุงู„ู€ true
299
00:24:35,060 --> 00:24:37,080
value ู‡ุฐู‡ ู†ุณู…ูŠู‡ุง ุงู„ู€ sample mean
300
00:24:41,220 --> 00:24:42,920
ู‡ูˆ ุจูŠุญูƒูŠ where is the difference between a
301
00:24:42,920 --> 00:24:48,400
hypothesized parameter ู‡ุฐุง ุฃู†ุง ุจูุชุฑุถู‡ุง ููŠ ุนู†ุฏูŠ ุงู„ู€
302
00:24:48,400 --> 00:24:53,420
true parameter ู‡ุฐุง ุงู„ู€ true parameter ู„ู…ุง
303
00:24:53,420 --> 00:24:55,780
ูŠูƒูˆู† ุงู„ูุฑู‚ ู…ุง ุจูŠู† ุงู„ุงุซู†ูŠู† ู‡ุฏูˆู„ ุงู„ู€ hypothesized
304
00:24:55,780 --> 00:24:59,020
ุงู„ุซู„ุงุซูŠู† ูˆ ุงู„ู€ true parameter decreases ุงู„ู€ beta
305
00:24:59,020 --> 00:25:03,340
ู…ุงู„ู‡ุง ุจุชุฒูŠุฏ ุฅุฐุง ูƒู„ ู…ุง ูƒุงู† ุงู„ูุฑู‚ ู…ุง ุจูŠู† ุงู„ู‚ูŠู…ุฉ
306
00:25:03,340 --> 00:25:07,400
ุงู„ุงูุชุฑุงุถูŠุฉ ู‡ู†ุง ูˆ ุงู„ู€ population ูŠุนู†ูŠ ู†ูุณ ุงู„ู€ true
307
00:25:07,400 --> 00:25:12,640
parameter ูƒู„ ู…ุง ุตุบุฑ ุงู„ู€ beta ู…ุงู„ู‡ุง ุจุชุฒูŠุฏ ุงู„ุจุนุฏุฉ beta
308
00:25:12,640 --> 00:25:16,280
decreases ู…ู† alpha ุฒูŠ ู…ุง ุญูƒูŠู†ุง ุดูˆูŠุฉ decrease ูŠุนู†ูŠ
309
00:25:16,280 --> 00:25:19,920
beta ุจุงู„ุฒูŠุงุฏุฉ ู„ู…ุง ุงุซู†ูŠู† ุนูƒุณ ุจุนุถ alpha ุจุชู‚ู„ beta
310
00:25:19,920 --> 00:25:23,520
ุจุงู„ุฒูŠุงุฏุฉ ู„ู…ุง ุณูŠุฌู…ุง ุจุงู„ุฒูŠุงุฏุฉ ูŠุนู†ูŠ ูƒู„ ู…ุง ุงู„ุงู†ุญุฑุงู ุงู„ู…ุนูŠุงุฑูŠ ุฒุงุฏ
311
00:25:23,520 --> 00:25:30,800
beta ู…ุง ู„ู‡ุง ุจุชุฒูŠุฏ ุงู„ุฃุฎูŠุฑุฉ beta ุจุงู„ุฒูŠุงุฏุฉ ู„ู…ุง n ู…ุง ู„ู‡ุง
312
00:25:30,800 --> 00:25:35,720
decreases ู…ุนู†ุงู‡ ูƒุฏู‡ ููŠ inverse relationship
313
00:25:35,720 --> 00:25:36,820
between beta ูˆู…ูŠู†
314
00:25:40,350 --> 00:25:43,370
ุงู„ุงุฎุชู„ุงู ุจูŠู† ุงู„ู€ hypothes and true value ุฏูŠ ูˆุงุญุฏุฉ
315
00:25:43,370 --> 00:25:48,670
ูˆ ุงู„ุซุงู†ูŠุฉุŸ Beta ูˆ Alpha ูˆ ุงู„ุซุงู„ุซุฉ Beta ูˆ ุฃู†ุง ู‡ุฐูˆู„
316
00:25:48,670 --> 00:25:54,230
ูƒู„ู‡ู… ุนู„ุงู‚ุฉ ู…ุงู„ู‡ุง ุนูƒุณูŠุฉ ุทุจ ู‡ุชุฑุจุทูŠู‡ุง ู…ุน ู…ูŠู†ุŸ ุจุณ ู…ุน
317
00:25:54,230 --> 00:25:59,250
Sigma ุฎู„ุงุตุŸ so there is direct relationship
318
00:25:59,250 --> 00:26:06,010
between Beta and Sigma Beta is .. ุฅูŠุด ุณู…ูŠู†ุง BetaุŸ
319
00:26:16,370 --> 00:26:24,870
ุงู„ุนู„ุงู‚ุฉ ุจูŠู† n ูˆุงู„ุฃู„ูุง
320
00:26:24,870 --> 00:26:34,830
ู‡ูˆ ุงู„ู€ hypothesized parameter ูˆู‚ูŠู…ุชู‡ ุงู„ุญู‚ูŠู‚ูŠุฉ ุงู„ุชุงู„ูŠุฉ
321
00:26:34,830 --> 00:26:39,930
ู‡ูŠ level of significance Alpha ูˆุงู„ู…ู†ุทู‚ุฉ ุงู„ุงู†ุชู‚ุงู„ูŠุฉ
322
00:26:39,930 --> 00:26:45,570
ูƒูŠู ูŠู…ูƒู†ู†ุง ุฃู† ู†ุชุฃูƒุฏ ู…ู† ุงู„ู‚ูŠู… ุงู„ุญุฑุฌุฉ ูˆูƒุฐู„ูƒ ู…ู†
323
00:26:45,570 --> 00:26:47,670
ุงู„ู…ู†ุทู‚ุฉ ุงู„ุญุฑุฌุฉ ุฏุนูˆู†ุง ู†ุฑู‰
324
00:27:06,290 --> 00:27:12,550
ุงู„ุขู† ุฅุฐุง ูƒู†ุง ู…ู‡ุชู…ูŠู† ุจู…ู‚ุงุฑู†ุฉ ฮผ equal ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ
325
00:27:12,550 --> 00:27:18,750
ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ
326
00:27:18,750 --> 00:27:21,710
ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง
327
00:27:21,710 --> 00:27:27,950
ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง
328
00:27:27,950 --> 00:27:30,050
ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง
329
00:27:30,050 --> 00:27:32,530
ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง
330
00:27:32,530 --> 00:27:35,130
ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง ูŠู‚ู„ ุซู„ุงุซุฉ ู…ู‚ุงุฑู†ุฉ ฮผ ู„ุง
331
00:27:38,150 --> 00:27:44,350
ู‡ูŠูŠุทู„ุน ุนู†ุฏูŠ two rejection regions ูˆุงุญุฏุฉ ุนู„ู‰ ุงู„ู€ left
332
00:27:44,350 --> 00:27:47,650
ูˆุงุญุฏุฉ ุนู„ู‰ ุงู„ู€ right ู‡ุฐู‡ ุงู„ู†ู‚ุงุท represent ู„
333
00:27:47,650 --> 00:27:53,590
critical values ุฅุฐุง ุงู„ู†ู‚ุงุท ู‡ุฏูˆู„ critical values
334
00:27:53,590 --> 00:27:58,150
critical values
335
00:27:58,150 --> 00:28:05,030
ุฎู„ูŠู†ูŠ ุฃุณู…ูŠู‡ุง critical value
336
00:28:06,740 --> 00:28:10,240
ุงู„ู„ูŠ ุจูŠุณู…ูŠู‡ุง ู†ู‚ุทุฉ ุงู„ุญุฑุฌุฉ ูˆู‡ู†ุง ูƒู…ุงู† ููŠ ูˆุงุญุฏุฉ ูˆู‡ูŠ
337
00:28:10,240 --> 00:28:15,260
critical value ุซุงู†ูŠุฉ ุฅุฐุง in case of two-tailed
338
00:28:15,260 --> 00:28:24,780
test ู‡ุฐุง ู‡ูˆ ุงู„ูˆุงุญุฏุฉ two-tailed test ูŠุนู†ูŠ ุงุฎุชุจุงุฑ ู…ู†
339
00:28:24,780 --> 00:28:32,980
ุทุฑููŠู† ุงู„ู€ 30 against 30 is not 30 ุงุฎุชุจุงุฑ
340
00:28:32,980 --> 00:28:33,560
ู…ู† ุทุฑููŠู†
341
00:28:36,150 --> 00:28:40,830
ุงู„ู€ test ู…ุนู†ุงู‡ุง ุงุฎุชุจุงุฑ ุงู„ู€ two ู…ุนู†ุงู‡ุง ุงุซู†ูŠู† ุฃูƒุซุฑ
342
00:28:40,830 --> 00:28:46,370
ู…ุนู†ุงู‡ุง ุทุฑู ุชุทู„ุน ุงุฎุชุจุงุฑ ู…ู† ุงู„ุทุฑููŠู† ู…ุธุจูˆุท ุงู„ู€ mean
343
00:28:46,370 --> 00:28:52,390
ุทุจุนุง ุงู„ู€ value in the center now
344
00:28:52,390 --> 00:28:54,510
the question is how can we determine these
345
00:28:54,510 --> 00:28:58,110
critical values one to the right and other to the
346
00:28:58,110 --> 00:29:04,010
left now we have level of significance alpha ุฃู„ูุง
347
00:29:04,010 --> 00:29:07,970
ู…ุฑุฉ ุฃุฎุฑู‰ ู‡ูŠ ู…ุตุทู„ุญ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ุนู†ุฏู…ุง ูŠู†ุชู‚ู„ ุฅู„ู‰
348
00:29:07,970 --> 00:29:11,550
ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„
349
00:29:11,550 --> 00:29:12,130
ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„
350
00:29:12,130 --> 00:29:14,750
ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰
351
00:29:14,750 --> 00:29:19,150
ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„
352
00:29:19,150 --> 00:29:25,030
ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„ ูŠู†ู‚ู„ ุฅู„ู‰ ู†ุฒู„
353
00:29:25,030 --> 00:29:28,170
ูŠู†ู‚ู„
354
00:29:32,600 --> 00:29:39,560
ุงู„ุจูŠุงู†ุงุช ู„ู† ุชูƒูˆู† 95% ู„ูƒู† ู…ู…ูƒู† ุชุทู„ุน ุงู„ู€ value ู‡ุฐุง ูˆ
355
00:29:39,560 --> 00:29:47,540
ุงู„ุซุงู†ูŠุฉ ุชุทู„ุน ุงู„ู€ value ู‡ุฐุง ูˆ ุงู„ุซุงู†ูŠุฉ ุชุทู„ุน
356
00:29:47,540 --> 00:29:51,300
ุงู„ู€ value ู‡ุฐุง ูˆ
357
00:29:51,300 --> 00:30:00,620
ุงู„ุซุงู†ูŠุฉ ุชุทู„ุน ุงู„ู€
358
00:30:01,540 --> 00:30:08,340
ุงู„ู„ูŠ ุนู„ู‰ ูŠู…ูŠู†ู‡ุง 2.5% ูŠุนู†ูŠ ุนู„ู‰ ูŠุณุงุฑู‡ุง ูƒุฏู‡ ุฅุฐุง ุนู„ู‰
359
00:30:08,340 --> 00:30:13,460
ูŠู…ูŠู†ู‡ุง 2.5% ุฅูŠุด ุจูŠูƒูˆู† ุนู„ู‰ ุงู„ูŠุณุงุฑ 97.5% ุฃูˆ ุฃุทู„ุน
360
00:30:13,460 --> 00:30:16,420
ุงู„ูƒุชุงุจุฉ ุงู„ู€ value ุงู„ู„ูŠ ู‡ู†ุง ุงู„ู„ูŠ ุนู„ู‰ ูŠุณุงุฑู‡ุง 2.5%
361
00:30:16,420 --> 00:30:20,780
ุทุจุนุง ู„ุณู‡ ู‡ุทู„ุน ุญุงุฏุฉ ู…ุจุงุดุฑุฉ ู…ู† ุงู„ุฌุฏูˆู„ ู…ุธุจูˆุท ุฃุทู„ุน
362
00:30:20,780 --> 00:30:24,540
ุงู„ุฌุฏูˆู„ ุนู„ู‰ 2.5% 0.25 ุฅูŠุด ุงู„ู‚ูŠู…ุฉ ุจุชุณุงูˆูŠ
363
00:30:35,840 --> 00:30:41,680
ุฃุทู„ุน ุนู„ู‰ ุงู„ู€ table ุนู„ู‰ IZ
364
00:30:41,680 --> 00:30:52,260
table ุฃู†ุง ุจุฏูˆุฑ ุนู„ู‰ 025 ุฃุทู„ุน
365
00:30:52,260 --> 00:30:57,960
in the body of the table ุนู„ู‰ 025 ูˆูŠู† ู…ูˆุฌูˆุฏุฉุŸ
366
00:31:00,870 --> 00:31:06,170
ู…ุด ู‡ูŠ ุงู„ู‚ูŠู…ุฉ ุฅุฐุง
367
00:31:06,170 --> 00:31:12,090
ุณุงู„ุจ one point nine under six ุฅุฐุง ุงู„ู‚ูŠู…ุฉ ุงู„ู„ูŠ ู‡ู†ุง
368
00:31:12,090 --> 00:31:19,110
ุณุงู„ุจ ู‡ูŠ negative one point nine six ู…ุธุจูˆุท ุฅุฐุง ู‡ูŠ
369
00:31:19,110 --> 00:31:24,050
ุงู„ู€ table ู…ุฏูˆุฑุฉ zero to five ูˆุงุถุญ ุฅู† ุชุญุช ุณุงู„ุจ one
370
00:31:24,050 --> 00:31:31,330
nine under six ุงู„ู…ูุฑูˆุถ ุงู„ุซุงู†ูŠุฉ ู„ุฃู† ูŠู…ูŠู†ู‡ุง 0.25 ูˆ
371
00:31:31,330 --> 00:31:35,630
ุฏุง ูŠุณุงุฑู‡ุง 0.25 the same value ุจุณ ุจุฅุดุงุฑุฉ ู…ุฎุชู„ูุฉ
372
00:31:35,630 --> 00:31:41,030
ู‡ุฐุง negative 196 ุฅุฐุง ุฃู†ุง should be positive ู‡ุฏูˆู„
373
00:31:41,030 --> 00:31:45,170
ุจุชุณู…ูŠู‡ู… critical values ู„ุฐุง ุงู„ู€ critical values
374
00:31:45,170 --> 00:31:48,450
ุจุชุทู„ุน ู…ู† ูˆูŠู†ุŸ ู…ู† ุงู„ู€ z table ูˆ ุงู„ู€ z table ุฃุฎุฐู†ุง
375
00:31:48,450 --> 00:31:55,310
ูˆูŠู†ุŸ ุดุฑุทุฉ 6 ูˆ ุจุนุฏ ูƒุฏู‡ ุดุฑุทุฉ 6 ู…ู‡ู… ููŠ ุดุฑุทุฉ 9 ู…ุธุจูˆุทุŸ
376
00:31:55,310 --> 00:32:01,460
ููŠ ุฃูŠ ุณุคุงู„ุŸ ุฅูŠุด ู„ุนุจู‡ุง ูƒุฏู‡ ุฃูู‡ู… ู…ุง ู…ุนู†ุงู‡ุงุŸ ู…ุง ููŠุด
377
00:32:01,460 --> 00:32:06,140
ุณุคุงู„ ุทุจ ุงู„ุญู…ุฏ ู„ู„ู‡ ู‡ุฐุง ูุถู„ ู…ู† ุฑุจู†ุง ุฃู†ุง ู…ุด ูุงู‡ู… ู‡ูˆ
378
00:32:06,140 --> 00:32:11,380
ู…ุนู†ุงู‡ ูƒุฏู‡ ุฅูŠู‡ ุงู„ู„ูŠ ู…ุนู†ุงู‡ ู‡ู… ุฃู†ุง ู…ุด ูุงู‡ู… ุฃูˆ ู…ุงุดูŠ
379
00:32:11,380 --> 00:32:17,580
ุนู„ูŠู‡ ุจุนุฏู‡ุง ุงู„ู„ูŠ ุฃู†ุง ุญูƒูŠุช ุนู„ูŠู‡ ู‡ุฐุง two-tailed ุงู„ู„ูŠ
380
00:32:17,580 --> 00:32:20,660
ู‚ุงู„ ุงู„ูƒุชุงุจ ูˆุงู‚ู ู„ุบุงูŠุฉ ู‡ู†ุง ูˆ ุจุนุฏูŠู† ู…ุง ุฃุนุทู‰ example
381
00:32:20,660 --> 00:32:28,580
ุฃู†ุง ู…ุด ู‡ุนู…ู„ ุฒูŠู‡ ุฃู†ุง ู‡ูƒู…ู„ ู‡ุนุทูŠูƒูŠ one-tailed right ุฃูˆ
382
00:32:28,580 --> 00:32:34,500
left ุฅุฐุง
383
00:32:34,500 --> 00:32:38,560
ุฑู‚ู…
384
00:32:38,560 --> 00:32:49,260
ุงุซู†ูŠู† ู‡ุงุฎุฏ upper tail ุฅูŠุด upper tail ุงู„ุทุฑู
385
00:32:49,260 --> 00:32:53,420
ุงู„ุฃุนู„ู‰ ู‡ุฐุง ุงู„ู€ lower tail ู„ุญุธุฉ ฮผ dose not equal
386
00:32:53,420 --> 00:32:58,040
ุซู„ุงุซุฉ ููŠ ุงู„ู€ upper tail ุฅูŠุด ู‡ูŠูƒูˆู† ู‡ูŠูƒูˆู† ู‡ูŠูƒูˆู† ฮผ
387
00:32:58,040 --> 00:33:07,420
equal ุซู„ุงุซุฉ ูˆ ุงู„ู€ H1 ุชูƒูˆู† ุฃูƒุจุฑ ูŠุนู†ูŠ ุฅูŠุด ุฃูƒุจุฑ ู…ุนู†ุงู‡
388
00:33:07,420 --> 00:33:10,660
ูƒุฏู‡ ุงู„ู€ rejection region ู‡ุชูƒูˆู† ูˆุงุญุฏุฉ ูˆู„ุง ุงุซู†ุชูŠู†
389
00:33:10,660 --> 00:33:12,800
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
390
00:33:12,800 --> 00:33:13,180
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
391
00:33:13,180 --> 00:33:13,220
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
392
00:33:13,220 --> 00:33:13,320
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
393
00:33:13,320 --> 00:33:17,160
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
394
00:33:17,160 --> 00:33:20,520
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
395
00:33:20,520 --> 00:33:23,940
ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ ูˆุงุญุฏุฉ
396
00:33:26,390 --> 00:33:29,170
ุฎู„ู‘ูˆุง ุจุงู„ูƒู… ุฃู†ุง ุจุญูƒูŠ level of significance alpha
397
00:33
431
00:36:46,500 --> 00:36:50,640
five ูŠุนู†ูŠ ู…ุฒูŠุฏ ุฎู…ุณุฉ ูˆุงู„ุซุงู†ูŠุฉ four zero four nine
432
00:36:50,640 --> 00:36:53,980
five ุชู‚ู„ ุฎู…ุณุฉ ููŠ ุงู„ average ุจูŠู† ุงู„ุงุซู†ูŠู† ุจุชูˆุน ู†ูุณ
433
00:36:53,980 --> 00:36:57,440
ุงู„ู‚ุตุฉ negative one is point six four five ุฅุฐุง ุงู„
434
00:36:57,440 --> 00:37:02,000
critical values can be determined for two tail
435
00:37:02,000 --> 00:37:06,080
test upper tail and lower tail it depends on the
436
00:37:06,080 --> 00:37:10,060
question ุจุชุนุชู…ุฏ ุนู„ู‰ ุงู„ุณุคุงู„ ู„ุฃู† ุงู„ areas ู‡ุฏูˆู„ ุงู„ู„ูŠ
437
00:37:10,060 --> 00:37:12,820
ุฃู†ุง ู…ุนู„ู‚ ุนู„ูŠู‡ู… ุจุงู„ุฃุณูˆุฏ ู‡ุฏูˆู„ ุจู†ุณู…ูŠู‡ู…
438
00:37:16,220 --> 00:37:19,440
rejection region ู‡ู†ุนุฑู ุจุนุฏ ุดูˆูŠุฉ ุฅูŠุด ุจูŠู‚ุตุฏ
439
00:37:19,440 --> 00:37:23,580
rejection region ุฅุฐุง ู‡ู†ุง ููŠ ุงู„ two-tailed ูƒุงู…
440
00:37:23,580 --> 00:37:28,420
rejection region ู…ูˆุฌูˆุฏุชูŠู† ูˆุงุญุฏุฉ ุฃูƒุจุฑ ู…ู† 1.96
441
00:37:28,420 --> 00:37:32,350
ูˆุงุญุฏุฉ ุฃู‚ู„ ู…ู† negative ูˆููŠ ุงู„ upper tail ููŠ one
442
00:37:32,350 --> 00:37:37,010
rejection region ุงู„ู„ูŠ ุฃูƒุจุฑ ู…ู† 1.645 ูˆููŠ ุงู„ lower ููŠ
443
00:37:37,010 --> 00:37:41,930
ูˆุงุญุฏุฉ ุงู„ู„ูŠ ุฃู‚ู„ ู…ู† minus 1.645 ู‡ุฐุง ูƒู„ุงู… ุตุญูŠุญ ู„ูˆ
444
00:37:41,930 --> 00:37:45,950
ูƒุงู†ุช Alpha ุดูˆ ุจุชุณุงูˆูŠ ุฎู…ุณุฉ ุงุญู†ุง ุบุงู„ุจุง ุจู†ุงุฎุฏ ุฎู…ุณุฉ
445
00:37:45,950 --> 00:37:50,170
ุบุงู„ุจุง ู„ูƒู† ุฃุญูŠุงู†ุง ู„ูˆ ุฃุฎุฐู†ุง ุบูŠุฑ ูƒุฏู‡ ุจู†ุณุชุฎุฏู… ุงู„ุฌุฏูˆู„
446
00:37:50,170 --> 00:37:55,130
ูุฃู†ุช ุญุงูุธูŠู‡ุง ุฅุฐุง Alpha 5% ู…ู† ุบูŠุฑ ู…ุง ู†ุณุชุฎุฏู… ุงู„
447
00:37:55,130 --> 00:38:04,150
table ุฅุฐุง ูƒุงู† two-tailed 1.96 negative ูˆ plus ุฅุฐุง
448
00:38:04,150 --> 00:38:09,450
ูƒุงู† upper tail ุจุชูƒูˆู† plus 1.645 ุฅุฐุง lower tail
449
00:38:09,450 --> 00:38:13,150
ุจุชูƒูˆู† negative 1.645 ุงุญูุธูŠู‡ุง ูˆุฎู„ุงุต ู…ู† ุบูŠุฑ ู…ุง
450
00:38:13,150 --> 00:38:18,270
ู†ุณุชุฎุฏู… ุงู„ table ุฅุฐุง ุจู†ุณุฃู„ ุงู„ 5% ู‡ุฏูˆู„ ู‡ุชู‚ุจู„ู‘ูŠู‡ู… ุฒูŠ
451
00:38:18,270 --> 00:38:30,510
ุงู„ empirical rule 68 95 99.7 questions ุฃูŠ ุณุคุงู„ุŸ ููŠ
452
00:38:30,510 --> 00:38:38,920
ุฃูŠ ุณุคุงู„ุŸ ุทูŠุจ ู†ูƒู…ู„ ุงู„ุขู† ู‡ู†ุจุฏุฃ ุฃูˆู„ ู†ู‚ุทุฉ ู…ู‡ู…ุฉ ุชุฐูƒุฑ
453
00:38:38,920 --> 00:38:42,600
ุญูƒูŠู†ุง ููŠ ุงู„ objectives ู†ุฑุฌุน ุซุงู†ูŠ ู„ู„ objectives
454
00:38:42,600 --> 00:38:47,800
ุงู„ุชุงุจุนุฉ ู„ู„ chapter ุชุณุนุฉ ุงู„ู„ูŠ ุญูƒูŠู†ุง ุนู„ูŠู‡ู… ุงู„ู„ูŠ ู‚ู„ู†ุง
455
00:38:47,800 --> 00:38:51,540
ุงู„ู„ูŠ ูุงุช ุญูƒูŠู†ุง ุฃูˆู„ ูˆุงุญุฏ the basic principles of
456
00:38:51,540 --> 00:38:56,060
hypothesis testing ุงู„ู„ูŠ ุงุญู†ุง ุฎู„ุตู†ุงู‡ ู„ุฃู† ูŠุนู†ูŠ ู„ุบุงูŠุฉ
457
00:38:56,060 --> 00:38:59,300
ุงู„ูŠูˆู… ุฃู†ุง ุจุณู…ูŠู‡ basic principles ู…ุจุงุฏุฆ ุฃุณุงุณูŠุฉ
458
00:38:59,300 --> 00:39:04,020
ู„ุงุฎุชุจุงุฑ ุงู„ูุฑุถูŠุฉ ุงู„ุขู† ู‡ู†ุจุฏุฃ how to use hypothesis
459
00:39:04,020 --> 00:39:10,240
testing ูƒูŠู ู†ุณุชุฎุฏู…ู‡ุง to test ุฃู…ูŠู† ูˆุงุญุฏ ูˆุงู„ู„ู‚ุงุก
460
00:39:10,240 --> 00:39:13,720
ุงู„ุฌุงูŠ ุงู„ู„ูŠ ู‡ูŠูƒูˆู† ูŠูˆู… ุขุฎุฑ ุจูƒุฑุฉ ุงู„ู„ู‚ุงุก ุงู„ุฌุงูŠ or a
461
00:39:13,720 --> 00:39:17,940
proportion ูŠุนู†ูŠ ุงู„ู„ู‚ุงุก ู‡ูŠูƒูˆู† ุฑุงุจุนุฉ ู…ุด ู‡ูŠ ูŠุนู†ูŠ ุฃู†ู†ุง
462
00:39:17,940 --> 00:39:22,140
ุงู„ุฃุซู†ูŠู† ูˆุงู„ุฃุฑุจุนุฉ ุจู†ุฎู„ุต chapter ุชุณุนุฉ
463
00:39:44,100 --> 00:39:49,460
ุฅุฐุง ุงู„ุนู†ูˆุงู† ุชุจุนู†ุง ุงู„ุฌุฏูŠุฏ ู‡ุฐุง ุนุจุงุฑุฉ ุนู† objective ุฑู‚ู…
464
00:39:49,460 --> 00:39:51,920
ุงุซู†ูŠู† ุงู„ู„ูŠ ู‡ูˆ hypothesis
465
00:39:59,210 --> 00:40:08,030
testing ุฃูˆู„ ูˆุงุญุฏุฉ ู‡ุงุฎุฏู‡ุง ุฅูŠู‡ for the mean ู„ู„ูˆุณุท
466
00:40:08,030 --> 00:40:11,930
ุฃู†
467
00:40:11,930 --> 00:40:18,430
ุฃู†ุง ู‡ุฃุทู„ุน ุฅู† ุฎู„ุงู„ ุงู„ุดุฑุญ ูƒู„ ุญูƒูŠ 90% ู…ูƒุฑุฑ ุฃุฎุฐู†ุงู‡ุง
468
00:40:18,430 --> 00:40:25,830
ููŠ 6 ูˆ7 ูˆุงู„ุจุงู‚ูŠ ุฌุฏูŠุฏ chapter ุชุณุนุฉ ูˆุฃุฎุฐู†ุง ู…ู†ู‡ ุฌุฒุก ููŠ
469
00:40:25,830 --> 00:40:29,390
ุงู„ basic principles ุฃู…ุณ ูˆุงู„ูŠูˆู… ู‡ุฃูƒูˆู† ู„ุฃู†
470
00:40:29,390 --> 00:40:33,850
ููŠ ุดุบู„ุฉ ุฌุฏูŠุฏุฉ ุจุณ ู‡ู†ุชุนุฑู ุนู„ูŠู‡ุง ู…ุน ุจุนุถ ุงู„ hypothesis
471
00:40:33,850 --> 00:40:38,890
is for ฮผูŠูˆ ู…ูŠู† ูŠุนู†ูŠ ุงู„ู…ูŠูˆ ูˆุฏุงุฆู…ุง ุฒูŠ ู…ุง ุญูƒูŠุช ู…ุฑุฉ
472
00:40:38,890 --> 00:40:42,390
ูุงุช ุจุนู…ู„ testing about population parameter ุงุฎุชุจุงุฑ
473
00:40:42,390 --> 00:40:45,570
ุญูˆู„ ุงู„ population ู†ูุณู‡ ุณูˆุงุก ุงู„ mean ุชุจุน ุงู„
474
00:40:45,570 --> 00:40:50,810
population ุฃูˆ ุงู„ู„ู‚ุงุกุงุช ุงู„ุฌุงูŠุฉ ู„ู„ proportion ู„ุฃู†
475
00:40:50,810 --> 00:40:54,410
ู‡ู†ุฌูŠุจ ุงู„ุฌุฒุฆูŠู† hypothesis for mu there are two
476
00:40:54,410 --> 00:40:57,690
scenarios when sigma is known I mean when sigma is
477
00:40:57,690 --> 00:41:05,070
given sigma is called what's the sigma no it's not
478
00:41:05,070 --> 00:41:12,890
standard deviation ูˆู„ุง standard ูˆู„ุง variance ุงู„
479
00:41:12,890 --> 00:41:16,670
sigma ุนุจุงุฑุฉ ุนู† ุฅูŠุด population standard deviation
480
00:41:16,670 --> 00:41:19,430
ุฃู…ูŠู‘ุฒ ุงู„ sigma ู‡ุฐู‡
481
00:41:22,630 --> 00:41:25,950
population standard deviation ู„ู…ุง ููŠ ุนู†ุฏ ุงู„ sample
482
00:41:25,950 --> 00:41:29,330
standard deviation ุงู„ู„ูŠ ู‡ูŠ ุงู„ S ุฃู†ุง ุจุชูƒู„ู… ุนู† ุงู„
483
00:41:29,330 --> 00:41:34,130
sigma ุงู„ู„ูŠ ู‡ูŠ population standard deviation ุฅุฐุง
484
00:41:34,130 --> 00:41:37,930
when sigma is known the test is called z test
485
00:41:37,930 --> 00:41:41,690
ุงู„ุงุฎุชุจุงุฑ ุงุณู…ู‡ z ุงู„ู„ูŠ ู‡ูŠ ุงุฒุงูŠ ุงู„ z score ุงู„ู„ูŠ
486
00:41:41,690 --> 00:41:46,510
ุฃุฎุฐู†ุงู‡ุง ููŠ chapter 7 ู…ุด 6 ู„ูŠุดุŸ ู„ู…ุง ุฃุชูƒู„ู… ุนู„ู‰ ุงู„
487
00:41:46,510 --> 00:41:51,050
mean ูˆ ุงู„ mean ูƒุงู†ุช ููŠ chapter ุณุจุนุฉ ุจุฐูƒุฑ ูƒุงู† ุงู„ z ุฃู‚ู„
488
00:41:51,050 --> 00:41:55,670
ุนู† x bar minus mu divided by sigma over root n ู‡ุฐุง
489
00:41:55,670 --> 00:42:00,230
chapter ุณุจุนุฉ ุงู„ุญุงุฌุฉ ุงู„ุซุงู†ูŠุฉ when sigma is unknown
490
00:42:00,230 --> 00:42:05,650
ูŠุนู†ูŠ sigma ู…ุด ู…ุนู„ูˆู…ุฉ ู‡ู†ุงุฎุฏ ุงู„ new test is called t
491
00:42:05,650 --> 00:42:09,590
test for next time ุฅู† ุดุงุก ุงู„ู„ู‡ next time ุงู„ู„ู‡ ุฃุนู„ู…
492
00:42:10,560 --> 00:42:14,320
ู…ุด ุดุฑุท ุจูƒุฑุฉ ู…ู…ูƒู† ูŠูƒูˆู†ูˆุง ู…ู† ุงู„ุฃุฑุจุนุงุก ุงู„ู‚ุงุฏู…ุฉ ุฃูˆ ูˆู„ุง
493
00:42:14,320 --> 00:42:21,260
ุญุณุจ ู„ูƒู† ุนู„ู‰ ุงู„ุฃู‚ู„ ู‡ุฃุจุฏุฃ when sigma is known ุฅุฐุง ุฃู†ุง
494
00:42:21,260 --> 00:42:27,960
ุฃุชูƒู„ู… ุนู† ุงู„ test for the mean ููŠ ุดุบู„ุชูŠู† ุฅูŠู‡ ูˆุงุญุฏุฉ sigma is
495
00:42:27,960 --> 00:42:33,180
known ุฅูŠุด ู…ุนู†ู‰ known ูŠุนู†ูŠ ุงู„ sigma ุฃู†ุง ุนุงุฑู
496
00:42:33,180 --> 00:42:37,420
ุจุงู„ุนุฑุจูŠ ู…ุนู†ุงู‡ sigma is given ู…ุนุทู‰ ู…ุนุงู‡ ูŠุนู†ูŠ sigma
497
00:42:37,420 --> 00:42:43,790
ู…ุนุฑูˆูุฉ ููŠ ุงู„ู…ุซุงู„ ูƒู„ ุงู„ู„ูŠ ู‡ุฃุนู…ู„ู‡ step number one convert
498
00:42:43,790 --> 00:42:49,210
sample statistic x bar to z statistic ุณู‡ู„ ุฃูˆ ู„ุง
499
00:42:49,210 --> 00:42:57,550
ูŠุนู†ูŠ ูƒู„ ุงู„ู„ูŠ ุจุนู…ู„ู‡ ุจุทู„ู‚ ุนู„ูŠู‡ z statistic ู‡ุฐุง z stat means
500
00:42:57,550 --> 00:43:02,650
for z statistic z stat ูŠุนู†ูŠ z test statistic
501
00:43:02,650 --> 00:43:09,030
ู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ู…ุด ุจุงู„ุณุงูˆูŠ ุฃุฎุฐู†ุงู‡ุง ู‚ุจู„ ูƒุฏู‡ ุชุฐูƒุฑ X bar
502
00:43:09,030 --> 00:43:13,650
minus ุงู„ mean ู‡ุฐุง
503
00:43:13,650 --> 00:43:18,130
ู…ู† ุฃูŠ chapterุŸ chapter 7 ุฅุฐุง chapter 7 ุฏุฎู„ ู…ุนุงูŠุง
504
00:43:18,130 --> 00:43:21,950
ุนู„ู‰ ุญุณุงุจ ุชุณู…ูŠุฉ test statistic
505
00:43:27,880 --> 00:43:30,180
ุฅุฐุง ุฃุฎุจุฑุชูƒ ุฃู†ูƒ ุชุญุณุจ ุงู„ test statistic ู‚ูŠู…ุฉ
506
00:43:30,180 --> 00:43:36,720
ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ
507
00:43:36,720 --> 00:43:40,460
ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ
508
00:43:40,460 --> 00:43:47,580
ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ุจู‚ูŠู…ุฉ
509
00:43:47,580 --> 00:43:48,460
ุงู„ุงุฎุชุจุงุฑ
510
00:43:54,340 --> 00:43:57,400
ูŠุนู†ูŠ for two-tailed test for the mean sigma known
511
00:43:57,400 --> 00:44:01,600
-convert x bar to z statistic ุฎู„ุตู†ุง step 2
512
00:44:01,600 --> 00:44:05,840
determine the critical z values ุญุฏุฏ ุงู„ critical
513
00:44:05,840 --> 00:44:08,900
values ุงู„ู„ูŠ ุทู„ุนู†ุงู‡ู… ู…ู† ุดูˆูŠุฉ ุงู„ู„ูŠ ู‡ู… ู„ู…ุง ุงู„ alpha
514
00:44:08,900 --> 00:44:16,000
ูƒุงู†ุช 5% ุฅูŠุด ูƒุงู†ูˆุง ุจูŠุณุงูˆูˆุง plus or minus 1.96 ู‡ุฏูˆู„
515
00:44:16,000 --> 00:44:20,760
ุงู„ critical values step 1 step 2 ุฃุทู„ุน ุงู„ critical
516
00:44:20,760 --> 00:44:22,840
values
517
00:44:25,720 --> 00:44:30,040
ูˆู‡ุฏูˆู„ ุฒูŠ ู…ุง ุญูƒูŠุช ุจูŠุทู„ุนูˆุง ุจูŠุชุญู…ู„ูˆุง ู…ู† ู…ู† ุงู„ table
518
00:44:30,040 --> 00:44:35,780
ุทุจุนุง for specified level of significance alpha ุญุณุจ
519
00:44:35,780 --> 00:44:37,620
ู‚ูŠู…ุฉ ุงู„ alpha ุงุญู†ุง ุฃุฎุฐู†ุง ุงู„ alpha ุฎู…ุณุฉ ููŠ ุงู„ู…ูŠุฉ
520
00:44:37,620 --> 00:44:42,160
from ุงู„ table ุฃุฎุฐู†ุง ุงู„ table ุชุนุฒูŠุฒูŠ ุงู„ table or
521
00:44:42,160 --> 00:44:46,260
using computer software ู…ุงู†ุนุด ููŠู‡ุง ูŠุนู†ูŠ ุจุงู„ Excel
522
00:44:46,260 --> 00:44:51,180
ู…ู…ูƒู† ุฃูˆ ุฃูŠ ุญุณุงุจ ุฃูˆ ุฃูŠ ุจุฑู†ุงู…ุฌ ูŠุญุตู„ ุฅุฐุง step ุฑู‚ู… 2
523
00:44:51,180 --> 00:44:58,140
ุณู‡ู„ ู‡ุฐุง ุฃุฐูƒุฑูƒ ููŠู‡ ุนุงู„ู‡ู…ุด ู„ูˆ ูƒุงู†ุช Alpha ุจ 5% ูˆูƒุงู†
524
00:44:58,140 --> 00:45:01,740
ููŠู‡ two-tailed ุฅูŠุด ู‡ุชุทู„ุน ุงู„ุฌูˆุงุจ plus or
525
00:45:01,740 --> 00:45:07,540
minusุŸ ู…ุธุจูˆุท ูˆุงุญุฏุฉ ุนู„ู‰ ุงู„ูŠู…ูŠู† 1.96 ูˆุงู„ุซุงู†ูŠุฉ ุนู„ู‰ ุงู„ุดู…ุงู„
526
00:45:07,540 --> 00:45:15,560
negative 1.96 ูˆู„ูˆ ูƒุงู† one-tailed ุญุณุจ ู‡ุชูƒูˆู† 1.645
527
00:45:15,560 --> 00:45:20,500
ุฅุฐุง ูƒุงู†ุช ุนู„ู‰ ุงู„ right ูŠุนู†ูŠ ุงู„ upper ู…ุธุจูˆุท
528
00:45:22,760 --> 00:45:27,760
ุฃูˆ negative 1.645 ุฅุฐุง ูƒุงู†ุช ุฃุณูู„ ุฃุนุชู‚ุฏ ูƒุฏู‡ ุณู‡ู„ุฉ ุณู‡ู„ุฉ
529
00:45:27,760 --> 00:45:35,980
ู‡ุฐุง ุงู„ second step ุทูŠุจ ู„ุงุญุธ ู…ู† ุฃูŠ chapter ุงุณุชุฎุฏุงู…
530
00:45:35,980 --> 00:45:39,920
ุงู„ Z-table ู…ู† chapter 6 ู…ุธุจูˆุท ุฅุฐุง ูˆุงุถุญ step 1 ูˆ 2
531
00:45:39,920 --> 00:45:44,300
ู…ู† where ู…ู† ุงู„ previous chapters ู…ู† 6 ูˆ 7 ุจุชุชู… ุนู†ุฏ
532
00:45:44,300 --> 00:45:50,020
chapter 9 ูƒู„ู…ุฉ ุตุบูŠุฑุฉ ุชุญุช ุงู„ู„ูŠ ู‡ูŠ step 3 ุงู„ู„ูŠ ู‡ูˆ
533
00:45:50,020 --> 00:45:55,690
decision rule ุงู„ู‚ุฑุงุฑ ุชุจุนู†ุง ูŠุนู†ูŠ ูƒู„ ุดุบู„ู†ุง ุนู„ู‰ ุงู„
534
00:45:55,690 --> 00:46:02,250
decision rule ููŠ chapter 9 ุจูŠุญูƒูŠ ุงู„ู‚ุงุนุฏุฉ ุงู„ู„ูŠ ู‡ูŠ rule
535
00:46:02,250 --> 00:46:08,070
of thumb if the test statistic ุฅุฐุง ู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ
536
00:46:08,070 --> 00:46:13,230
falls in the rejection region ุงู„ rejection ุจู‚ูˆู„ ู„ูƒ
537
00:46:13,230 --> 00:46:16,750
ู‡ูŠ ู‡ู… ุงู„ุฃุณูˆุฏ ุงู„ุนุงู„ู…ูŠู† ูˆุงู„ุดู…ุงู„ ููŠ ุงู„ two tail ุงู„ู„ูŠ
538
00:46:16,750 --> 00:46:24,090
ู‡ู… ู‡ุฏูˆู„ ู‡ู†ุง ูƒุงู†ุช ู‡ุฏูˆู„ ุงู„ุงุซู†ูŠู† ุจู†ุณู…ูŠู‡ู… rejection
539
00:46:24,090 --> 00:46:27,950
region ูˆ
540
00:46:27,950 --> 00:46:31,870
ุงู„ upper tail ูŠูƒูˆู†ูˆุง
541
00:46:31,870 --> 00:46:36,290
ุนู„ู‰ ุงู„ูŠู…ูŠู† ูˆุงู„ lower tail ูˆูŠู†ุŸ ุนู„ู‰ ุงู„ุดู…ุงู„ ู‡ุฏูˆู„
542
00:46:36,290 --> 00:46:42,270
ุจู†ุณู…ูŠู‡ู… rejection regions ุจูŠุญูƒูŠ ุทุจุนุง ุฃูŠ ู…ุซุงู„ ุจุชูƒูˆู†
543
00:46:42,270 --> 00:46:46,610
ุฅู…ุง two tail ุฃูˆ one tail ุฃูˆ upper tail lower tail
544
00:46:46,610 --> 00:46:49,530
ุฃูˆ upper tail ู…ุง ุจูŠูƒูˆู†ุด ุชู„ุงุชุฉ ู…ุน ุจุนุถ ูˆุงุญุฏุฉ ู…ู†ู‡ู… ุจุณ
545
00:46:50,530 --> 00:46:55,610
ูุจูŠุทู„ุน ุงู„ rejection region ุงู„ู‚ุฑุงุฑ if the test
546
00:46:55,610 --> 00:46:58,870
statistic ู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ุงู„ู„ูŠ ูˆูŠู† ุทู„ุน ุญุณุจุชู‡ step
547
00:46:58,870 --> 00:47:02,770
ูˆุงุญุฏ if the test falls in the rejection region
548
00:47:02,770 --> 00:47:12,590
ุจูŠู‚ุน ุฌูˆุง then we reject H zero is an if the test
549
00:47:12,590 --> 00:47:19,150
statistic ุฎู„ูŠู†ุง ู†ุญูƒูŠู‡ุง ุจุตูˆุฑุฉ ุฃุฏู‚ if the value ู‚ูŠู…ุฉ
550
00:47:19,150 --> 00:47:22,830
ุฅุฐุง ู‚ูŠู…ุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ
551
00:47:22,830 --> 00:47:28,390
ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ
552
00:47:28,390 --> 00:47:29,750
ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ
553
00:47:29,750 --> 00:47:29,770
ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ
554
00:47:29,770 --> 00:47:32,830
ูƒู…ูŠุฉ
555
00:47:32,830 --> 00:47:38,870
ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ
556
00:47:38,870 --> 00:47:43,670
ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ
557
00:47:43,670 --> 00:47:44,750
ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ
558
00:47:44,750 --> 00:47:44,770
ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ
559
00:47:44,770 --> 00:47:47,460
ุงู„ุงุฎุชุจุงุฑ ูƒู…ูŠุฉ ูˆู‚ุน ุฌูˆุง ูŠุนู†ูŠ ุฅูŠุดุŸ ูŠุนู†ูŠ ู„ูˆ ูƒุงู†ุช two
560
00:47:47,460 --> 00:47:49,980
-tailed ู„ุฃ ู„ูˆ ุฃูƒุจุฑ ู…ู† ู‡ุฐู‡ ุฃูˆ ุฃู‚ู„ ู…ู† ุงู„ู†ุงุญูŠุฉ ุงู„
561
00:47:49,980 --> 00:47:54,620
negative ู…ุง ุฃู†ุง ูˆู‚ุน ููŠู‡ุงุŒ ูŠุนู†ูŠ ุชุฎูŠู„ ู…ุนุงูŠุง ุฃุฎุฐ
562
00:47:54,620 --> 00:48:00,760
example ุจุชูƒู„ู… ุนู„ู‰ 1.96 ู„ู„ critical values ุงู„
563
00:48:00,760 --> 00:48:05,960
rejection region ู…ูˆุฌูˆุฏ ุนู„ู‰ ุงู„ูŠู…ูŠู† ู‡ู†ุงุŒ ู…ุธุจูˆุท ุฃูˆ
564
00:48:05,960 --> 00:48:11,680
ุนู„ู‰ ุงู„ุดู…ุงู„ ุงู„ุขู† ุจุชุนุทูŠูƒ for example suppose Z equal
565
00:48:11,680 --> 00:48:19,360
3.5 ู‡ุฐุง ุฒูŠ ู‚ูŠู…ุฉ ุฒูŠ stat ู‡ุฐุง ุงู„ test ุงู„
566
00:48:19,360 --> 00:48:23,060
statistic ุฃุณุฃู„ ู†ูุณูƒ does this value fall in the
567
00:48:23,060 --> 00:48:27,580
rejection region ูŠุนู†ูŠ ุฅู…ุง ุชูƒูˆู† ุฃูƒุจุฑ ู…ู† 1.96 ุฃูˆ ุฃู‚ู„
568
00:48:27,580 --> 00:48:33,280
ู…ู† negative ููˆุงุถุญ ู‡ุฐู‡ ู‡ู†ุง ุฅุฐุง we reject the null
569
00:48:33,280 --> 00:48:37,660
hypothesis ุทูŠุจ ู„ูˆ ูƒุงู†ุช for example z equal
570
00:48:37,660 --> 00:48:41,700
negative one ุฃู†ุง ุฃุชูƒู„ู…ุช
571
00:48:49,770 --> 00:48:55,290
ู…ุด ูƒู„ ุณุงู„ุจ ุจูŠ reject ูˆู„ุง ูƒู„ ู…ูˆุฌุจ ุจูŠ reject ู‡ู†ุง
572
00:48:55,290 --> 00:49:00,470
ุจุชูƒู„ู… ุนู† two-tailed negative 1.4 ุงู„
573
00:49:00,470 --> 00:49:08,030
rejection ุฑ ุฑ ู†ุชุนูˆุฏ ุนู„ูŠู‡ุง ุฑ ุฑ ูŠุนู†ูŠ ุฅูŠุด rejection
574
00:49:08,030 --> 00:49:13,390
region ู‡ุชูƒูˆู† ุฃูƒุจุฑ ู…ู† 1.96 ุฃูˆ ุฃู‚ู„ ู…ู† ู…ู†
575
00:49:13,390 --> 00:49:15,150
ุณุงู„ุจ
576
00:49:16,600 --> 00:49:20,840
ุชุณุฃู„ ู†ูุณูƒ ุงู„ negative 1.4 ู‡ู„ ู‡ูŠ ุฃู‚ู„ ู…ู† ู†ุงู‚ุต 1.9ุŸ
577
00:49:20,840 --> 00:49:26,380
ู„ุฃุŒ ู…ูˆุฌูˆุฏุฉ ู‡ู†ุงุŒ ู…ุธุจูˆุทุŸ ู‡ู†ุง ู‡ุฐู‡ ุงู„ area ุงู„ุจูŠุถุงุกุŒ
578
00:49:26,380 --> 00:49:30,480
ุจู†ุณู…ูŠู‡ุง non rejection areaุŒ ู…ู† ุงู„ู…ู†ุทู‚ุฉ ุงู„ุจูŠุถุงุก
579
00:49:30,480 --> 00:49:34,800
ุงู„ู„ูŠ ุจูŠู† ุงู„ุงุซู†ูŠู†ุŒ ุจุณ ููŠู‡ุง ู…ู†ุทู‚ุฉ ุนุฏู… ุงู„ุฑูุถ ุทูŠุจุŒ
580
00:49:34,800 --> 00:49:39,120
ุฃุนุทูŠู†ูŠ example ููŠู‡ุง reject ู„ู„ู…ุซุงู„ ู‡ุฐุงุŒ ุฃุนุทูŠู†ูŠ ุงู„ z
581
00:49:39,120 --> 00:49:46,640
ูŠูƒูˆู† ููŠู‡ุง reject 2.5 ู„ูˆ ูˆู‚ุน ู‡ู†ุง ุงู„ุซุงู†ูŠ ุจุงู„ุงุซู†ูŠู†
582
00:49:46,640 --> 00:49:50,520
ูˆุงู‚ุน ู‡ู†ุง ููŠ ุงู„ region of rejection ุฃุนุทูŠู†ูŠ ุญุงู„ุฉ ู„ู„
583
00:49:50,520 --> 00:49:56,500
.. don't reject 1 .. 1 ู‡ู†ุง ุงู„ุซุงู†ูŠ 1 2
584
00:49:56,500 --> 00:50:01,620
ู‡ู†ุง 1.4 ู‡ู†ุง ูˆู‡ูƒุฐุง 1.4 ูŠุนู†ูŠ ุฃูŠ
585
00:50:01,620 --> 00:50:04,360
ุญุงุฌุฉ between negative 1.96 and 1.
586
00:50:04,360 --> 00:50:08,940
96 non rejection region ุฃุนุทูŠูƒูŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ
587
00:50:08,940 --> 00:50:12,900
ู„ู…ูŠู†ุŸ ู„ู„ two tailed ู†ุงุฎุฐ one tailed ุฅุฐุง ู…ุฑุฉ ุซุงู†ูŠุฉ
588
00:50:12,900 --> 00:50:17,920
three steps Compute the test statistic ู…ู† Chapter 7
589
00:50:17,920 --> 00:50:23,980
ุงุญุณุจ ุงู„ Critical values ู…ู† Chapter 6 Chapter 9 ุจุณ
590
00:50:23,980 --> 00:50:28,920
ุดุบู„ ุตุบูŠุฑุฉ ุงู„ู„ูŠ ู‡ูŠ ุงู„ decision rule We reject the
591
00:50:28,920 --> 00:50:33,220
null if the statistic value falls in the rejection
592
00:50:33,220 --> 00:50:37,220
region Now for two-tailed test, the rejection
593
00:50:37,220 --> 00:50:41,620
region is in the lower tail and upper tail But on
594
00:50:41,620 --> 00:50:44,780
the other hand, if we are talking about one-tailed
595
00:50:44,780 --> 00:50:52,730
test 1 tail ุฏุฎู„ู†ุง ู†ุฑุณู…ู‡ุง ุชุญุช ู‡ู†ุง ู‡ูŠ ุงู„ right
596
00:50:52,730 --> 00:50:56,690
suppose we are talking about right tail and alpha
597
00:50:56,690 --> 00:51:00,870
is five percent so this value equals ุฅูŠุด ุงู„ู‚ูŠู…ุฉ
598
00:51:00,870 --> 00:51:08,590
ุจุชุณุงูˆูŠ ุงุญูุธู†ูŠ ูŠุงู‡ุง 1.645 ู…ุธุจูˆุท ุทุจ ู„ูˆ ุงุฒุงูŠ ุงู„
599
00:51:08,590 --> 00:51:16,090
statistic ุณูˆู‰ 1.5 ูˆุงู‚ุน ู‡ู†ุง ููŠ ุงู„ rejection
600
00:51:16,090 --> 00:51:20,750
ุฅุฐุง ุงู„ rejection ุชูƒูˆู† ุงู„ z stat ู…ุงู„ู‡ุง ุฃูƒุจุฑ
601
00:51:20,750 --> 00:51:30,910
ู…ู† 1.645 ู‡ู†ุง ุฅูŠุด ูƒุงู†ุช ุฃูƒุจุฑ ุฃูˆ ุฃู‚ู„ ู…ุธุจูˆุท ู‡ู†ุง ุจุณ
602
00:51:30,910 --> 00:51:33,970
ุฃูƒุจุฑ ู„ูŠุดุŸ ู„ุฃู† ุนู†ุฏูŠ upper tail ูŠุนู†ูŠ ู„ูˆ ุจุฎุชุจุฑ ู…ูŠูˆ
603
00:51:33,970 --> 00:51:39,730
ุฃูƒุจุฑ ู…ู† 30 ู‡ู†ุง ุจุฎุชุจุฑ ู…ูŠูˆ ุจุชุณุงูˆูŠุด 30 ุทุจ ุฃุนุทูŠู†ูŠ ุญุงุฌุฉ
604
00:51:39,730 --> 00:51:47,940
reject ุฃูŠ ุญุงุฌุฉ ุฃูƒุจุฑ ู…ู† 1.645 1.7 2 ุฃูŠ ุญุงุฌุฉ ุฌูˆุง
605
00:51:47,940 --> 00:51:53,980
4 5 6 ุฃูŠ ุญุงุฌุฉ ุฌูˆุง ุทุจ ู‡ุฐุง upper tail ู†ุงุฎุฐ
606
00:51:53,980 --> 00:52:00,220
lower tail lower tail the area to the left ุงู„ู„ูŠ ู‡ูŠ
607
00:52:00,220 --> 00:52:06,100
negative 1.645 ุทุจ ุฃ reject ุฅุฐุง ูƒุงู†ุช ุงู„ z-stat ู…ุงู„ู‡ุง
608
00:52:06,100 --> 00:52:12,620
ุฃู‚ู„ ู…ู† negative ุทุจ ู„ูˆ ุณูˆู‰ ุงู„ z-stat negative 1
609
00:52:14,830 --> 00:52:17,090
ุงู„ negative 1 ููŠ ุงู„ non-rejection region ู„ุฐุง
610
00:52:17,090 --> 00:52:24,290
ู„ุง ู†ู†ุฌุญ ุฅุฐุง ุณูˆู‰ negative 2 ู„ุง ู†ู†ุฌุญ ู„ุง ู†ู†ุฌุญ ู„ุง
611
00:52:24,290 --> 00:52:30,450
ู†ู†ุฌุญ ูˆู‡ู†ุง ู†ู†ุฌุญ ูˆุงุถุญุŸ ู…ุนู†ุงู‡ ูƒุฏู‡ ุฅู†ูƒ ุชุญู„ูŠ ุงู„ู…ุซุงู„