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ุจุงุณู… ุงู„ู„ู‡ ุงู„ุฑุญู…ู† ุงู„ุฑุญูŠู… ุงู„ุญู…ุฏ ู„ู„ู‡ ุฑุจ ุงู„ุนุงู„ู…ูŠู†
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ูˆุงู„ุตู„ุงุฉ ูˆุงู„ุณู„ุงู… ุนู„ูŠ ุณูŠุฏู†ุง ู…ุญู…ุฏ ูˆุนู„ูŠ ุฃู‡ู„ูŠ ูˆุตุญุจู‡
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ูˆุณู„ู… ุฃุฌู…ุนูŠู† ููŠ ุงู„ุจุฏุงูŠุฉ ุจู†ุฑุญุจ ุจุฌู…ูŠุน ุงู„ุฅุฎูˆุฉ ูˆุงู„ุฃุฎูˆุงุช
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ูˆุงู„ุทุงู„ุจุงุช ููŠ ู…ู‚ุฑุฑ Business Statistics ููŠ ุงู„ูุตู„
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ุงู„ุฏุฑุงุณูŠ ุงู„ุซุงู†ูŠ ุงู„ู„ูŠ ุฅู† ุดุงุก ุงู„ู„ู‡ ู‡ู†ุชุนู„ู… ููŠู‡ ู‡ู†ุณุชุฎุฏู…
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.. ู‡ุฐุง ุงู„ูƒุชุงุจ Business Statistics ู…ูˆุฌูˆุฏ ููŠ ุงู„ู…ูƒุชุจุฉ
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ุงู„ุขู† ู‡ูŠ ู…ูƒุชุจุฉ ุงู‚ุฑุฃ ุงู„ู€ .. ุฒูŠ ู…ุง ุญูƒูŠุช ุงู„ู…ุฑุฉ ุงู„ูุงุชุชุฉ
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ุงู„ูƒุชุงุจ ููŠู‡ ุงู„ู€ Bar Point ุจุงู„ูƒุงู…ู„ุŒ seven chapters
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ู‡ู… ุซู„ุงุซุฉ ูˆุณุชุฉ ูˆุณุจุนุฉ ูˆุชุณุนุฉ ูˆุนุดุฑุฉ ุฃูˆ ุฃุญุฏ ุนุดุฑ ูˆ
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ุงุซู†ุง ุนุดุฑุŒ ู‡ุฐูˆู„ ุงู„ู€ seven chapters ู‡ู†ุงุฎุฏู‡ู… ุฒุงุฆุฏ ุญุทูŠุช ุงู„ู€
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practice ู„ูƒู„ chapter ู…ูˆุฌูˆุฏ ุฒุงุฆุฏ ุงู„ู€ previous exams
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ุญุทูŠุช ุฃุฑุจุนุฉ ุงู…ุชุญุงู†ุงุช ู„ู†ูุณ ุงู„ู€ course ู„ู†ูุณ ุงู„ูƒุชุงุจ ุทุจุนู‹ุง
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ููŠ ุงู…ุชุญุงู†ุงุช ุซุงู†ูŠุฉ ู‡ุญุทู‡ุง ุนู„ู‰ ุงู„ุตูุญุฉ ุฅู† ุดุงุก ุงู„ู„ู‡ ุจุฑุถู‡
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ู‡ุญุท ู„ูƒ PDF ูˆุงู„ู€ PowerPoint ูƒุงู…ู„ุฉ ู‡ุญุท ู„ูƒ ููŠู‡ุง
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PowerPoint file ุฒูŠ ุงู„ู€ PDF ู„ูˆ ุญุจูŠุช ุชู‚ุฑุฃ ู…ู†ู‡ุง ุนู„ู‰
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ุงู„ุฌูˆุงู„ ุนู„ู‰ ุงู„ู€ laptop ููŠ ุฃูŠ ู…ูƒุงู† ูŠูƒูˆู† ุนู†ุฏูƒ ุดุบู„ุชูŠู†
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hard copy ุฒูŠ ู‡ูŠูƒ ูƒูˆูŠุณ ูˆุงู„ู€ soft copy ุชูƒูˆู† ู…ูˆุฌูˆุฏุฉ
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ู…ุนูƒ ุทุจุนู‹ุง ุงู„ู€ soft copy ุฃู†ุง ุนุงูŠุฒู‡ุง ููŠ ุงู„ู…ุญุงุถุฑุฉ ู‡ู†ุง
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ุจุญูŠุซ ุฅู†ู‡ ูˆุฃู†ุง ุจุดุฑุญ ุญูŠู† ุชูƒุชุจ ุดูˆูŠุฉ ู…ู„ุงุญุธุงุช ูŠุนู†ูŠ
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ุจุชุนู…ู„ notes ุฅู„ูŠูƒ ุฒูŠุงุฏุฉ ู„ุฃู†ู‡ ุบุงู„ุจู‹ุง ุงู„ู€ notes ุงู„ู„ูŠ ููŠ
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ุงู„ู€ PowerPoint ู…ุด ูƒุงู…ู„ุฉุŒ ุจุชุญุท ุดูˆูŠุฉ ุดุบู„ุงุช ุนู„ูŠู‡ุง ุงู„ูŠูˆู…
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ุฅู† ุดุงุก ุงู„ู„ู‡ ู‡ุจุฏุฃ ู…ุจุงุดุฑุฉ ููŠ chapter ูˆุงุญุฏุŒ ุงู„ู€ chapter
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ุงู„ุฃูˆู„ ุนูŠู†ูŠู‡ ู‡ูˆ chapter ุฑู‚ู… ุซู„ุงุซุฉุŒ ุฅุฐุง ุงู„ู€ course
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ุชุจุนู†ุง ุงุณู…ู‡ Basic StatisticsุŒ ุฃูˆู„ chapter ุจู†ุณู…ูŠู‡
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Numerical Descriptive Measures ุงู„ู„ูŠ ู‡ูŠ ู…ู‚ุงูŠูŠุณ
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ุงู„ูˆุตููŠุฉ ุงู„ุฑู‚ู…ูŠุฉุŒ ุจุชุนุฑู ุงุญู†ุง ุงู„ู€ data in general has
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two types ุงู…ุง Numerical ู†ุณู…ูŠู‡ุง Numerical Data ุฃูˆ
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ู†ุณู…ูŠู‡ุง ุงู„ุซุงู†ูŠุฉ Categorical Data ุฅุฐุง ู†ุณู…ูŠู‡ุง
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Numerical Data ุฃูˆ ุงุญู†ุง ู†ุณู…ูŠู‡ุง Quantitative ุฃูˆ
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ู†ุณู…ูŠู‡ุง Qualitative
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ุงู„ุจูŠุงู†ุงุช ู„ุฏูŠู‡ุง ุฃุดูƒุงู„ ู…ุฎุชู„ูุฉ ุจุดูƒู„ ุนุงู…ุŒ ูˆุงุญุฏุฉ ุจู†ุณู…ูŠู‡ุง
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Numerical Data ุฃูˆ Quantitative Data ูˆุงู„ุซุงู†ูŠุฉ
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ุจู†ุณู…ูŠู‡ุง Qualitative Data ุฃูˆ Categorical Data ุนู„ู‰
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ุณุจูŠู„ ุงู„ู…ุซุงู„ ุนู†ุฏู…ุง ู†ุชุญุฏุซ ุนู† ุนู…ุฑุŒ ุนู…ุฑ ู‡ูˆ ู†ู…ุฑูŠุŒ ุฅุฐุง
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ุนู…ุฑูƒ 18 ุณู†ุฉุŒ 18 ู‡ูŠ ู‚ูŠู…ุฉ ู†ู…ุฑูŠุŒ ุฅุฐุง ูƒู†ุง ู†ุชุญุฏุซ ุนู† ุงู„ุถุบุท
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ุนู„ู‰ ุณุจูŠู„ ุงู„ู…ุซุงู„ุŒ ูƒู…ูŠุฉ ุนุงู…ุฉุŒ ู‡ุฐู‡ ุงู„ุฏุฑุงุณุฉ ู‡ูˆ 70 ูƒูŠู„ูˆ
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ุฌุฑุงู…ุŒ ู‡ุฐุง ู‡ูˆ ุงู„ู‚ูŠู…ุฉ ุงู„ู†ู…ูˆุฐุฌูŠุฉ ุนู†ุฏู…ุง ู†ุชูƒู„ู… ุนู†
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ุงู„ุจูŠุงู†ุงุช ุงู„ูƒุชูˆุฑูŠูƒูŠุฉ ุฃูˆ ุงู„ุจูŠุงู†ุงุช ุงู„ุชู‚ู„ูŠุฏูŠุฉุŒ ุนู„ู‰ ุณุจูŠู„
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ุงู„ู…ุซุงู„ ุงู„ุฌู†ุณ ุฅู…ุง ุงู„ู…ู„ุงูƒูŠู† ุฃูˆ ุงู„ุฅู†ุงุซุŒ ุฃูˆ ุงู„ู…ู„ุงูƒูŠู†
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ู‡ุฐุง
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ูŠุณู…ู‰ ุชู‚ู„ูŠุฏูŠุฉุŒ ุชู‚ู„ูŠุฏูŠุฉ ู…ุนู†ุงู‡ ู†ูˆุนูŠ
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Quantitative ูŠุนู†ูŠ ุฑู‚ู…ูŠุŒ This chapter focuses on
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Numerical Descriptive Measures ุจู†ุฑูƒุฒ ุนู„ู‰ ุงู„ู…ู‚ุงูŠูŠุณ
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ุงู„ูˆุตููŠุฉ ุงู„ุฑู‚ู…ูŠุฉุŒ So we are talking about something
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like scoresุŒ Now suppose your score is 90ุŒ 90 is
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numerical valueุŒ ุงู„ุขู† ูƒูŠู ู†ู‚ุฑุฑ ุงู„ู…ุนู„ูˆู…ุงุช ุฅุฐุง ูƒุงู†
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ู„ุฏูŠู†ุง ู‚ูŠู…ุฉ ู†ู…ูŠุฐูŠุฉุŸ ููŠ
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ู‡ุฐู‡ ุงู„ู‚ุตุฉ ู„ุฏูŠู†ุง ุฃุฑุจุนุฉ ุฃู‡ุฏุงูุŒ ุงู„ุฃูˆู„ู‰
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ุชุณู…ุญ ุจู€ Properties of Central Tendency ู„ุญุธุฉ ู„ุฅู† ููŠ
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ุนู†ุฏูŠ ุฃูˆู„ ุชุนุฑูŠู Central TendencyุŒ ุฅูŠุด
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ู…ุนู†ู‰ CentralุŸ ู…ุฑูƒุฒุŒ tendency ู†ุฒุนุฉุŒ ุจุงู„ุธุจุทุŒ ูู‡ูŠ ุจูŠุณู…ูŠู‡ุง
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ู†ุฒุนุฉ ุงู„ู…ุฑูƒุฒูŠุฉุŒ ุดูˆู ุฃู†ุง ู‡ุญุงูˆู„ ุงู„ู…ุตุทู„ุญุงุช ุชุญูƒูŠ ุนุฑุจูŠ
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ุงู†ุฌู„ูŠุฒูŠุŒ ูููŠ ุนู†ุฏูŠ Describe the Probabilities of
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Central Tendency ู…ุนู†ุงู‡ุง
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ุจุฏุฃ ุฃุดุฑุญ ุฃูˆ ุฃูˆุตู ุฎุตุงุฆุต ู†ุฒุนุฉ ุงู„ู…ุฑูƒุฒูŠุฉุŒ Variation ุฅูŠุด
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ูŠุนู†ูŠ Variation
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Variation ู…ุนู†ุงู‡ ุงุฎุชู„ุงู ุฃูˆ
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ุชุดุชุช ุฃูˆ ุชุจูŠู†ุŒ And Shape in Numerical Data ุดูƒู„
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ููŠ ู‡ุฐู‡ ุงู„ู…ู‚ุงู„ุฉ ุณู†ุชุญุฏุซ ุนู† ุซู„ุงุซ ุฃุณุฆู„ุฉ ุฑุฆูŠุณูŠุฉ
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ู„ู„ู…ู‚ุงู„ุงุช ุงู„ุฑุณู…ูŠุฉุŒ ุงู„ุฃูˆู„ู‰ ู‡ูŠ ุชู†ุฏู†ุณูŠุฉ ู…ุฑูƒุฒูŠุฉุŒ ุงู„ุงุฎุชู„ุงู
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ุฃูˆ ุชุดุชุชุŒ ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช
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ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ
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ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู
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ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช
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ุงู„ุงุฎุชู„ุงู ุฃูˆ
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ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู ุฃูˆ ุชุดุชุช ุงู„ุงุฎุชู„ุงู
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ุฃูˆ ุชุดุชุท
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Construct ู…ุนู†ุงู‡ุง ุจู†ุงุก
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ุฃูˆ ุฅู†ุดุงุก ุฃูˆ ุฅู†ุดุงุก ุฃูˆ ุฑุณู…ุŒ ุณู…ูŠู‡ุง Interpret ุชูุณูŠุฑ
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ุจุชูุณูŠุฑุŒ ุจูƒุณ ุจู„ุงุช ุญุฏ ูŠุณู…ูŠู‡ุง ุจูƒุณ ุจู„ุงุช ู‡ู†ุงุฎุฏู‡ุง
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ุจุงู„ุชูุณูŠุฑ ุจุนุฏูŠู† ุฅุฐุง ุจู†ุนู…ู„ ุจู†ุงุก ูˆุงู„ุชุนู„ูŠู‚ ุฃูˆ ุงู„ุชูุณูŠุฑ
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ุจูƒุณ ุจู„ุงุชุŒ Number three Compute Descriptive Summary
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Measures for a Population. In general, we have
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populationุŒ suppose we are talking about IUG
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studentsุŒ ุจุชูƒู„ู… ุนู„ู‰ all IUG studentsุŒ ูƒู„ ุทู„ุจุฉ
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ุงู„ุฌุงู…ุนุฉ ุงู„ุฅุณู„ุงู…ูŠุฉ ุจุญูƒูŠ ูƒู„ุŒ ุจุชูƒู„ู… ุนู† Population ุฅูŠุด
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ู…ุนู†ู‰ PopulationุŸ ู…ุฌุชู…ุนุŒ ู…ุฌุชู…ุน ูƒูƒู„ุŒ ู„ูˆ ุฃุฎุฏุช ู…ู†ู‡ Sample
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ุตุบูŠุฑุฉุŒ ู‡ูƒุฐุง ู†ูุชุฑุถ SampleุŒ ู‡ูƒุฐุง ุทุจุนู‹ุง ุงู„ู€ size ุชุจุน
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Population ู…ู…ูƒู† ูŠูƒูˆู† ู…ุซู„ู‹ุง ุณุชุฉ ุนุดุฑ ุฃู„ูุŒ sixty
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thousandุŒ ุงู„ู€ Sample ุฅูŠุด ู‡ุชูƒูˆู†ุŸ ุฌุฒุกุŒ ู…ู…ูƒู† ูŠุงุฎุฏ ู…ุงุฆุฉ
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ู…ู†ู‡ู…ุŒ ุนูŠู†ุฉุŒ Number that he talks aboutุŒ How can we
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Compute Descriptive Measures for a Population for
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the entire data for the entire data we have plus
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objective calculate the covariance and the
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coefficient of correlationุŒ Variance ู…ุนู†ุงู‡ ุฅูŠุดุŸ
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ุชุจุงูŠู†ุŒ ูˆCo .. ุฃูŠ ุญุงุฌุฉ Co ู…ุนู†ุงู‡ุง ู…ุดุชุฑูƒุŒ ุฅุฐุง ุจุฏู†ุง ู†ุญุณุจ
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ุงู„ุชุจุงูŠู† ุงู„ู…ุดุชุฑูƒ ุฃูˆ ุณู…ูŠู‡ุงุŒ ู‡ู†ุง ุงู„ุชุบูŠุฑ ู‡ุฐุง ููŠ ุขุฎุฑ
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ุงู„ุญู„ู‚ุฉ ุฅู† ุดุงุก ุงู„ู„ู‡ุŒ ุฅุฐุง ู†ุชูƒู„ู… ุนู† ุงู„ู€ Covariance
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ุชุบูŠุฑุŒ And
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the Coefficient of Correlation ุงู„ู„ูŠ ู‡ูˆ ุฅูŠุดุŸ ู…ุนุงู…ู„
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ุงู„ุงุฑุชุจุงุทุŒ ู‡ุฐูˆู„ four objectives ู„ุญุธุฉ ููŠ ุนู†ุฏูŠ ุดูˆูŠุฉ
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ู…ุตุทู„ุญุงุช ุฌุฏูŠุฏุฉุŒ ุฃู†ุง ุจู†ุตุญูƒ ุฎู„ู‘ูŠ ุนู†ุฏูƒ ุฏูุชุฑ ู„ุญุงู„ ูˆู‡ูŠูƒ
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ู„ู„ู€ .. ู„ู„ู…ุตุทู„ุญุงุช ู‡ุฐูˆู„ ุฒูŠ Center TendencyุŒ Variation
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ShapeุŒ InterpretุŒ CovarianceุŒ CorrelationุŒ ู‡ุฐูˆู„
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ู…ุตุทู„ุญุงุช ุฃู†ุง ุณุงุฎุฏูŠู†ู‡ุง ุจูƒุซุฑุฉุŒ ูุจุงู„ุชุงู„ูŠ ูƒูˆูŠุณ ูŠูƒูˆู† ุนู†ุฏูƒ
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ุชู„ุฎูŠุต ู„ู‡ู… ุงู„ู„ูŠ
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ุฃู†ุง ู‡ุชูƒู„ู… ุนู„ู‰ Summary Definitions ุจุนุถ ุงู„ุชุนุฑูŠูุงุชุŒ ูˆ
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ู‡ู†ุจุฏุฃ ุจุฃูˆู„ ูˆุงุญุฏ ุงู„ู€ Central Tendency ู…ุฑุฉ
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ุซุงู†ูŠุฉ ุงู„ู€ Central Tendency ู…ุนู†ุงู‡ุง ู†ุฒุนุฉ ู…ุฑูƒุฒูŠุฉ
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ุงู„ู„ูŠ ู„ูˆ ุณุฃู„ุช ูƒู„ ูˆุงุญุฏุฉ ููŠูƒูˆุง ุนู…ุฑู‡ุงุŒ ู…ู…ูƒู† ูˆุงุญุฏุฉ
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ุงู„ุณุจุนุฉ ุนุดุฑุŒ ูˆุงุญุฏุฉ ุซู…ุงู†ูŠุฉ ุนุดุฑุŒ ูˆุงุญุฏุฉ ุนุดุฑูŠู†ุŒ ูˆู‡ุงูƒุฐุงุŒ ู„ูˆ
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ุนุงูŠุฒ ุขุฎุฏ ุงู„ู€ Center ุชุจุนูƒู…ุŒ ู‡ุฐุง ุงู„ู€ Center ู…ุนู†ุงู‡
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ุงู„ู‚ูŠู… ุชุฌูŠ ุญูˆุงู„ูŠู† ุจุนุถู‡ู…ุŒ ู…ุชูˆุณุทุงุชู‡ู…ุŒ ูุงู„ู€ Center
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Tendency is the extent to which the valuesุŒ ุงู„ุนูŠู…ุง
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ุฏู‡ ุฃู†ู‡ ููŠ ุนู†ุฏู‡ ู‚ูŠู… of Numerical Variable Group
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00:09:53,360 --> 00:09:57,540
around a typical or central valueุŒ ูŠุนู†ูŠ ุงู„ู‚ูŠู…
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ุชุชู…ุฑูƒุฒ ูˆูŠู†ุŸ ุงู„ู„ูŠ ู‡ูŠ ุงู„ู…ุชูˆุณุทุŒ ูˆุงุญุฏุฉ ู…ู†ู‡ุง ุงู„ู…ุชูˆุณุทุŒ
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ู‡ู†ุงุฎุฏู‡ุง ุจุนุฏ ุดูˆูŠุฉุŒ ู„ุฐุง ุงู„ู€ Central ู…ุนู†ุงู‡ุง ุงู„ู‚ูŠู… ุชุชุฌู…ุน
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ุฃูˆ ุชุชู…ุฑูƒุฒ ุญูˆุงู„ูŠู† ู‚ูŠู…ุฉ ููŠ ุงู„ู†ุตูุŒ ุจู†ุณู…ูŠู‡ุง ุงู„ู€ Central
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ValueุŒ ุงู„ู€ Variation is the amount of dispersion
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ุงู†ุชุดุงุฑ ุฃูˆ ุชุดุชุชุŒ ู…ู‚ุฏุงุฑ ุงู„ุชุดุชุช or scattering awayุŒ ู…ุด
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scattering awayุŒ ุชู†ุชุดุฑ ุจุดูƒู„ ุจุนูŠุฏ ุนู† ุงู„ู€ Central
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ValueุŒ ูŠุนู†ูŠ ุงู„ู€ Variation ุจู‚ูŠุณ ูƒู…ูŠุฉ ุงู„ุชุดุชุชุŒ ูŠุนู†ูŠ ุฅุฐุง
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ุงู„ุชุดุชุช ุตุบูŠุฑุŒ ูƒุจูŠุฑ ุฃูˆ ู…ุชูˆุณุท that
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the values of a numerical variable shownุŒ ุฅุฐุง ุงู„ู€
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Variation ุจู‚ูŠุณ ู…ู‚ุฏุงุฑ ุงู„ุชุดุชุช ู„ู„ู‚ูŠู… ุนู† ุงู„ู…ุชูˆุณุท
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ุงู„ุญุณุงุจูŠุŒ ุทุจ ุงู„ู€ Shape ุงู„ุดูƒู„ is the pattern of the
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distribution patternุŒ Pattern ู…ุนู†ุงู‡ ู†ู…ุท ุงู„ุชูˆุฒูŠุน of values
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from the lowest value to the largestุŒ ูŠุนู†ูŠ ุดูƒู„
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ุงู„ุชูˆุฒูŠุน ู…ู† ุฃุตุบุฑ ู‚ูŠู…ุฉ ู„ุฃูƒุจุฑ ู‚ูŠู…ุฉ ุจู†ุณู…ูŠู‡ the Shape
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ุฅุฐุง ููŠ ุนู†ุฏ ุงู„ู€ Central ุงู„ู‚ูŠู… ู…ุฑูƒุฒูŠุฉ ุนู† ู‚ูŠู… ุนุงู…ุฉ ุฃูˆ
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ุจุนุถ ุงู„ุฃุญูŠุงู† ุงุณู…ู‡ุง ู‚ูŠู…ุฉ ู…ุฑูƒุฒูŠุฉุŒ ู‡ุฐุง ุงุณู…ู‡ุง ุชู†ุฏู†ุณูŠุฉ
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ู…ุฑูƒุฒูŠุฉ ู…ุฎุชู„ูุฉุŒ ู…ู‚ุฏุงุฑ ุงู„ุชุดุชุช ู…ู† ุงู„ู…ุฑูƒุฒ ูƒู… ุชุดุชุช ุนู„ู‰
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ุงู„ู…ุชูˆุณุท ุงู„ุญุณุงุจูŠุŒ ุงู„ุชุงู„ุช ุงู„ุดูƒู„ ู‡ูˆ ุทุฑูŠู‚ุฉ ุงู„ู…ุดุงุฑูƒุฉ ู…ู†
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ุฃุตุบุฑ ุฅู„ู‰ ุฃูƒุจุฑุŒ ู…ุง ู‡ูˆ ุฃุตุบุฑุŸ ุฃุตุบุฑุŒ ุฃูƒุจุฑ ู‚ูŠู…ุฉุŒ ู‡ุฐูˆู„ ุงู„ู€
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three definitions ู‡ู†ุงุฎุฏ ูƒู„ ูˆุงุญุฏ ุจุงู„ุชูุตูŠู„ุŒ The first
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one talks about Measures of Central TendencyุŒ ู†ุงุฎุฏ
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ู…ู‚ูŠุงุณ ู„ู‡ู…ุŒ ุฃูˆู„ ู…ู‚ูŠุงุณ is called the Mean ูƒู„ู†ุง ุจู†ุนุฑู
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ุงู„ู€ Mean
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ุงู„ู€ Mean ุนุจุงุฑุฉ ุนู† ุฅูŠุดุŸ ู…ุชูˆุณุท ุญุณุงุจูŠุŒ It's called the
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Arithmetic Mean ุฃูˆ ู„ุณู‡ ูˆู„ุง ุจู†ุญูƒูŠุŒ Often just called
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the Mean ุจุณ ุจุญูƒูŠ ุนู†ู‡ the MeanุŒ It's
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the most common measure of Central TendencyุŒ ุฅูŠุด
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ูŠุนู†ูŠ Most Common Measure of Central TendencyุŸ ุฃุดู‡ุฑ
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ู…ู‚ูŠุงุณ ุฃูˆ ุงู„ู…ู‚ูŠุงุณ ุงู„ุฃูƒุซุฑ ุดูŠูˆุนู‹ุง ุฃูˆ ุงู„ู…ู‚ูŠุงุณ ุงู„ุฃูƒุซุฑ
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ุงุณุชุฎุฏุงู…ู‹ุงุŒ ุฅุฐุง ุฃูƒุซุฑ ู…ู‚ูŠุงุณ ุณู†ุณุชุฎุฏู…ู‡ ุงู„ู€ MeanุŒ ุงู„ู€ Mean
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ู‡ูˆ ุฃูƒุซุฑ ู…ู‚ูŠุงุณ ุนุงู… ู„ู„ุชู†ุฏู†ุณูŠุฉ ุงู„ู…ุฑูƒุฒูŠุฉุŒ ุงู„ุขู† ุงู„ุณุคุงู„
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ู‡ูˆ ูƒูŠู ู†ุณุชุฎุฏู… ุงู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ
139
00:12:37,450 --> 00:12:40,150
ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ
140
00:12:40,150 --> 00:12:40,730
ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ
141
00:12:40,730 --> 00:12:42,880
ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ูŠุงุณ ู„ู„ู…ู‚ ุงุญู†ุง ู†ุฃุฎุฐ
142
00:12:42,880 --> 00:12:46,840
ู…ุฌู…ูˆุนุฉ ู…ุฎุชู„ูุฉ ุฃูˆ ู…ุฌู…ูˆุนุฉ ุตูุฑ ู†ุŒ ูŠุนู†ูŠ ุฃู†ู†ุง ู„ุฏูŠู†ุง ู†
143
00:12:46,840 --> 00:12:52,640
ุทู„ุงุจุŒ ู† ู…ุซู„ู‹ุง ุฃูˆ ู…ู„ุงุญุธุงุช ู† ุฃูˆ ู…ุฌู…ูˆุนุฉ ู†ุŒ ุงู„ู…ุฌู…ูˆุนุฉ
144
00:12:52,640 --> 00:12:55,800
ู…ุฎุชู„ูุฉุŒ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ
145
00:12:55,800 --> 00:12:56,040
ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ
146
00:12:56,040 --> 00:12:59,480
ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ
147
00:12:59,480 --> 00:12:59,540
ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ
148
00:12:59,540 --> 00:13:03,040
ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ ู…ู‚ุตูˆุฏุฉ
149
00:13:03,040 --> 00:13:07,300
ู…ู‚ุตูˆุฏุฉ ู…
150
00:13:10,740 --> 00:13:15,720
ู…ู…ูƒู† ุฃุณู…ูŠู‡ Y bar ู„ูƒู† ุบุงู„ุจู‹ุง ู†ุณุชุฎุฏู… X barุŒ ุฅุฐุง X bar
151
00:13:15,720 --> 00:13:20,640
it stands for the mean or the arithmetic meanุŒ X
152
00:13:20,640 --> 00:13:26,700
bar equals .. we have a new symbol hereุŒ this
153
00:13:26,700 --> 00:13:32,700
called summationุŒ Summation
154
00:13:32,700 --> 00:13:38,200
ูŠุนู†ูŠ ู…ุฌู…ูˆุนุŒ Summation
155
00:13:38,200 --> 00:13:40,140
of X I
156
00:13:48,720 --> 00:13:53,940
ุงู„ู‚ูŠู…ุฉ ุฑู‚ู… IุŒ ูŠุนู†ูŠ ุฅูŠุด ุงู„ู‚ูŠู…ุฉ ุฑู‚ู… IุŸ ุนู„ู‰ ุณุจูŠู„
157
00:13:53,940 --> 00:14:03,180
ุงู„ู…ุซุงู„ุŒ ุฅุฐุง ูƒุงู† ู„ุฏูŠู†ุง ู‡ุฐู‡ ุงู„ู‚ูŠู… 16ุŒ 20ุŒ 26ุŒ 30ุŒ 40ุŒ 50
158
00:14:03,180 --> 00:14:11,020
ูˆู…ุง ุฅู„ู‰ ุฐู„ูƒุŒ ุงู„ุขู† ุงู„ู‚ูŠู…ุฉ ุงู„ุฃูˆู„ู‰ 16 ู†ุณุชุฎุฏู… X1 ู„ู€ 16 ูู€ X1
159
00:14:11,020 --> 00:14:17,200
ู‡ูŠ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉ
160
00:14:17,200 --> 00:14:18,300
ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„
161
00:14:18,300 --> 00:14:18,760
ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉ
162
00:14:18,760 --> 00:14:19,440
ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„
163
00:14:19,440 --> 00:14:20,200
ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉ
164
00:14:20,200 --> 00:14:21,880
ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„
165
00:14:21,880 --> 00:14:22,720
ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉ
166
00:14:22,720 --> 00:14:34,500
ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ ุฃูˆู„
167
00:14:34,500 --> 00:14:41,090
ู‚ูŠู…ุฉุŒ ุฃูˆู„ ู‚ูŠู…ุฉุŒ 6ุŒ 1ุŒ 2ุŒ 3 ุฅู„ู‰ 6ุŒ ู„ุฐู„ูƒ ู†ุญู† ู„ุฏูŠู†ุง 6
168
00:14:41,090 --> 00:14:46,590
ู…ู„ุงุญุธุงุชุŒ ู„ุฐู„ูƒ ุตู…ู… ุงู„ู…ุฌู…ูˆุนุฉ ูŠู‚ู„ 6ุŒ ู„ุฐู„ูƒ ุตู…ู… XIุŒ I
169
00:14:46,590 --> 00:14:55,730
ูŠุชุฌู‡ ู…ู† 1 ุฅู„ู‰ 6ุŒ ูŠุนู†ูŠ X1 plus X2 ุฅู„ู‰ XNุŒ ุชู‚ู„ ู…ู† NุŒ
170
00:14:55,730 --> 00:15:06,290
ู…ุง ู‡ูˆ NุŸ N ู‡ูˆ ุตู…ู… ุงู„ู…ุฌู…ูˆุนุฉุŒ So the mean equals
171
00:15:06,290 --> 00:15:13,290
summation of XI divided by NุŒ Now once again X bar
172
00:15:13,290 --> 00:15:19,650
pronounced as X barุŒ This symbol is called
173
00:15:19,650 --> 00:15:25,930
summationุŒ ู‡ุฐุง ู…ุณู…ู‰ ุงู„ู…ุฌู…ูˆุนุŒ ุงู„ู€ Xุงุช ู‡ุฐูˆู„ ุนุจุงุฑุฉ ุนู† ุงู„ู€
174
00:15:25,930 --> 00:15:29,070
observed valuesุŒ ุงู„ู‚ูŠู… ุงู„ู…ุดุงู‡ุฏุฉุŒ ุฅูŠุด ุงู„ู€ Observed
175
00:15:29,070 --> 00:15:34,670
ุงู„ู„ูŠ ู‡ูˆ ู…ุฏุฑุณุฉ 16 ู‡ู‚ูˆู„ observedุŒ Observed ูŠุนู†ูŠ
176
00:15:34,670 --> 00:15:40,230
ุงู„ู…ู„ุงุญุธุฉุŒ ุงู„ู‚ูŠู… ุงู„ู…ุดุงู‡ุฏุฉ ุฃูˆ ุงู„ู…ู„ุงุญุธุฉุŒ ุฅู† ู‡ู…ุง ุนุดุฑูŠู†ุŒ
177
00:15:40,230 --> 00:15:42,150
ุณุชุฉ ูˆุนุดุฑูŠู†ุŒ ุซู„ุงุซูŠู† ูˆู…ุง ูƒุงู†ุŒ Similar Observed
178
00:15:42,150 --> 00:15:45,670
valuesุŒ ุฅุฐุง
179
00:15:45,6
216
00:19:30,040 --> 00:19:34,200
100 ู‡ูŠ ู‚ูŠู…ุฉ ุฃูƒุซุฑุŒ ู‚ูŠู…ุฉ ูƒุจูŠุฑุฉุŒ outlierุŒ ู‚ูŠู…ุฉ ุดุงุฐุฉ
217
00:19:34,200 --> 00:19:40,540
ู„ูˆ ุถูุช ุงู„ู…ุฆุฉ ุนู„ูŠู‡ู…ุŒ ุงู„ู€ new mean ู…ุด ู‡ูŠุณุงูˆูŠ 145ุŒ ุงู„ู€ sample size ู‡ูˆ 10 ู„ุฃู†ู†ุง ู‚ู…ู†ุง ุจุฅุถุงูุฉ ู‚ูŠู…ุฉ
218
00:19:40,540 --> 00:19:45,700
ูˆุงุญุฏุฉุŒ 14.5 ู„ุญุธุฉุŒ
219
00:19:45,700 --> 00:19:51,180
ุงู„ู‚ูŠู…ุฉ ุงู„ู‚ุฏูŠู…ุฉ ูƒุงู†ุช 5ุŒ ูˆ ุงู„ุขู† ุชุตุจุญ 14.5 ู‡ุฐุง ูŠุนู†ูŠ
220
00:19:51,180 --> 00:19:55,080
ุฃู† ุงู„ู‚ูŠู…ุฉ ุชุชุฃุซุฑ ู…ู† ู‡ุฐู‡ ุงู„ู‚ูŠู…ุฉ ุงู„ุฃูƒุซุฑุŒูˆุงุถุญ ุฃู†ู‡ ูŠุชุฃุซุฑ
221
00:19:55,080 --> 00:20:00,300
ุงู„ู‚ูŠู… ุงู„ูƒุจูŠุฑุฉุŒ ุชู„ุงุญุธ ุงู„ู‚ูŠู…ุฉ ูƒุงู†ุช ุฎู…ุณุฉ ุตุงุฑุช ุฃุฑุจุนุฉ ุนุดุฑ
222
00:20:00,300 --> 00:20:04,820
ูˆ ู†ุตู ุชู‚ุฑูŠุจุง ุซู„ุงุซุฉ ุถุนูุŒ ุนุดุงู† ูƒุฏู‡ ุจู†ุญูƒูŠ the mean is
223
00:20:04,820 --> 00:20:08,480
affected by extreme value ุฅุฐุง ุจุชุฃุซุฑ ุจุงู„ู‚ูŠู… ุงู„ุดุงุฐุฉ
224
00:20:08,480 --> 00:20:13,040
ู‡ูŠ
225
00:20:13,040 --> 00:20:16,500
ูŠุนู†ูŠ ู„ุฃู† ุจู‚ุฏุฑุด ุฃุฌูŠุจ ุนู„ูŠู‡ุง ุงู„ุณุคุงู„ุŒ ู‡ู†ุฎู„ูŠู‡ ู„ูุจุนุฏูŠู† ู„ู…ุง
226
00:20:16,500 --> 00:20:20,580
ู†ุงุฎุฏ ุญุงุฌุฉ ุงุณู…ู‡ุง ุงู„ู€ box plot ู„ูƒู† ู…ุจุฏุฆูŠุง ุงู„ู€ twenty
227
00:20:20,580 --> 00:20:25,500
ูŠุนู†ูŠ ุงู„ู„ูŠ ุชู„ุงุญุธูŠู‡ุŒ ุงู„ู€ 13 ู„ 14 ุงู„ูุฑู‚ ู…ุด ูƒุจูŠุฑ ุนุดุงู† ูƒุฏู‡
228
00:20:25,500 --> 00:20:31,620
ุงู„ู€ 20 ู…ู…ูƒู† ู…ุด extreme value ู„ูƒู† ู„ู…ุง ุญุทูŠู†ุง ุงู„ู…ูŠุฉ ู…ู†
229
00:20:31,620 --> 00:20:37,040
5 ู„ 14 ูˆ ู†ุตูุŒ ูˆุงุถุญ ุงู„ู…ุณุงูุฉ ูƒุจูŠุฑุฉ ุจูŠู†ู‡ู… ู„ูƒู† ู…ู‚ุฏุฑุด
230
00:20:37,040 --> 00:20:42,360
ุฃุญุฏุฏ ุงู„ุขู†ุŒ ู„ูƒู† ูˆุงุถุญ ุฃู†ู‡ ููŠ ุงู„ู€ data ุงู„ุฃูˆู„ู‰ ุงู„ู€ 20 is
231
00:20:42,360 --> 00:20:46,840
not that extreme value ู…ุด ูƒุชูŠุฑ ุจุนูŠุฏุฉ ุนุดุงู† ูƒุฏู‡ ุงู„ู€
232
00:20:46,840 --> 00:20:50,160
mean ูƒุงู† 13 ุตุงุฑ 14 ุงู„ูุฑู‚ ู…ุด ูƒุจูŠุฑุŒ ุณุคุงู„ูƒ ูƒูˆูŠุณ ุจุณ ุฃุฌุงูˆุจ
233
00:20:50,160 --> 00:20:56,740
ุนู„ูŠู‡ ุฅู† ุดุงุก ุงู„ู„ู‡ ุฎู„ุงู„ ุงู„ู„ู‚ุงุกุงุช ุงู„ู„ูŠ ุฌุงูŠุฉุŒ the
234
00:20:56,740 --> 00:21:01,940
next measure is called the medianุŒ ุงูŠุด medianุŸ ูˆุณูŠุท
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ุงู„ู€ median ู…ุนู†ุงู‡ ุงู„ูˆุณูŠุทุŒ ุชุนุฑู
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ุงู„ูˆุณูŠุทุŒ the value in the middleุŒ ุงู„ู‚ูŠู…ุฉ ููŠ ุงู„ูˆุณุท
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ุจุนุฏ ู…ุง ู†ุฑุชุจ ุงู„ู€ data ู…ู† smallest to largest
238
00:21:17,480 --> 00:21:20,520
ู„ู…ุง ุฃุฑุชุจ ุงู„ู‚ูŠู… ูŠุนู†ูŠ ุฅุฐุง ูƒุงู† ุนู†ุฏูƒ ุดูˆูŠุฉ ู‚ูŠู…
239
00:21:20,520 --> 00:21:23,500
ุจุชุฑุชุจูŠู‡ู… ู…ู† ุงู„ุตุบูŠุฑ ู„ู„ูƒุจูŠุฑ ุฃูˆ ุงู„ุนูƒุณุŒ ุงู„ู‚ูŠู… ุงู„ู„ูŠ ููŠ
240
00:21:23,500 --> 00:21:27,280
ุงู„ูˆุณุท ู‡ูŠ ุนุจุงุฑุฉ ุนู† ุงู„ู€ medianุŒ ู…ุนู†ุงู‡ ู‚ูŠู…ุฉ ููŠ ุงู„ูˆุณุท
241
00:21:27,280 --> 00:21:30,360
ูŠุนู†ูŠ ุงู„ู„ูŠ ุนู„ู‰ ุงู„ูŠู…ูŠู† ุจุชุณุงูˆูŠ ุงู„ู„ูŠ ุนู„ู‰ ุงู„ุดู…ุงู„ ูŠุนู†ูŠ
242
00:21:30,360 --> 00:21:33,140
ุนุฏุฏ ุงู„ู‚ูŠู… ุงู„ู„ูŠ ุนู„ู‰ ุงู„ูŠุณุงุฑ ุจุชุณุงูˆูŠ ุนุฏุฏ ุงู„ู‚ูŠู… ุงู„ู„ูŠ
243
00:21:33,140 --> 00:21:36,280
ุนู„ู‰ ุงู„ูŠู…ูŠู†ุŒ ู‡ุฐุง ู…ุนู†ุงู‡ in an ordered array ููŠ ู…ุตููˆูุฉ
244
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ู…ุฑุชุจุฉุŒ the median is the middle numberุŒ middle number
245
00:21:40,460 --> 00:21:47,550
ุงู„ู‚ูŠู…ุฉ ุงูŠุดุŸ ููŠ ุงู„ู…ู†ุชุตูุŒ ู…ุนู†ู‰ ุงู„ู‚ูŠู…ุฉ ููŠ ุงู„ู…ู†ุชุตู ูŠุนู†ูŠ
246
00:21:47,550 --> 00:21:52,490
ุฎู…ุณูŠู† ููŠ ุงู„ู…ูŠุฉ above ูˆุฎู…ุณูŠู† ููŠ ุงู„ู…ูŠุฉ below ู„ุฃู†
247
00:21:52,490 --> 00:21:59,010
ูˆูŠู† ุงู„ูˆุณุท ููŠ ุฃุตุงุจุนูƒุŸ ููŠ ุงู„ู†ุต ู…ุธุจูˆุทุŒ ุฅูŠุด ู…ุนู†ู‰ ููŠ
248
00:21:59,010 --> 00:22:02,970
ุงู„ู†ุตุŸ ูŠุนู†ูŠ ุงุซู†ูŠู† ุนู„ู‰ ุงู„ุดู…ุงู„ ูˆุงุซู†ูŠู† ุนู„ู‰ ุงู„ูŠู…ูŠู† ููŠ
249
00:22:02,970 --> 00:22:05,850
ุงู„ู€ middleุŒ and the value in the middle when we
250
00:22:05,850 --> 00:22:07,490
arrange the data from smallest to largest ุฃูˆ ู…ู†
251
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largest to smallestุŒ ุฃุฑุจุนุฉ ู‡ูˆ ู†ูุณ ุงู„ูƒู„ุจ ุงู„ุตุบูŠุฑ ุฃูŠู‡ุง
252
00:22:10,350 --> 00:22:15,190
ุจุชุญูƒูŠ .. ู„ูˆ ูƒุงู† ุฃุนุฏุงุฏู‡ู… ุฃุฑุจุนุฉ ู‡ุฌูŠุจ ู„ูƒ ุฃุณูˆุฃ ุจุนุฏ ุงู„ู€
253
00:22:15,190 --> 00:22:21,090
slide ู‡ุฐู‡ ุงู„ู„ูŠ ู‡ู†ุญูƒูŠ ุนู„ู‰ ุงู„ุดุบู„ ุงู„ุทุจูŠุนูŠ ู„ูˆ ูƒุงู†
254
00:22:21,090 --> 00:22:25,710
ู‡ุฐุง ุดูˆูŠุฉ ู‚ูŠู… ุงู„ู€ median ุงู„ู‚ูŠู…ุฉ ุงู„ู„ูŠ ููŠ ุงู„ู†ุต ุจุนุฏ
255
00:22:25,710 --> 00:22:27,990
ู…ุง ู†ุฑุชุจู‡ู… ูˆุนู„ู‰ ูŠู…ูŠู†ู‡ู… ุจุณูˆุก ุนู„ู‰ ุดู…ุงู„ู‡ู…ุŒ ุฎู„ูŠู†ุง ู†ุดูˆูู‡ุง
256
00:22:27,990 --> 0:22:32,810
ุจุนุฏ ุดูˆูŠุฉุŒ ู…ุง ู†ุณุชุนุฌู„ุด ูŠุนู†ูŠ ุฌุงูˆุจ ุนู„ู‰ ุณุคุงู„ูƒ ุจุนุฏ ุดูˆูŠุฉ
257
00:22:32,810 --> 00:22:35,730
ุชุทู„ุน ุนู„ู‰ ุงู„ู‚ูŠู… ู‡ุฐูˆู„ ู†ูุณ ุงู„ู‚ูŠู… ุงู„ู„ูŠ ูุงุชุช 11 .. 12 ..
258
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13 .. 14 .. 15 .. The median and the value in the
259
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middleุŒ ูˆู‡ุฏูˆู„ ูˆุงุถุญ ุฃู†ู‡ we arrange the dataุŒ ู…ุฑุชุจูŠู†
260
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ุงู„ู€ value in the middle ู‡ูŠ
261
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ุงู„ู€ median ู„ุญุธุฉ
262
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13 ู‡ุฐู‡ ุงู„ู‚ูŠู…ุฉ 13 ู‡ูŠ ุงู„ู‚ูŠู…ุฉ ุงู„ู…ุชูˆุณุทุฉ ู„ุฃู† ู‡ู†ุงูƒ
263
00:22:56,610 --> 00:23:01,880
ุงุซู†ูŠู† ุชุญุช 13 ูˆุงุซู†ูŠู† ููˆู‚ู‡ุงุŒ ุงุซู†ูŠู† ุฃู‚ู„ ูˆ
264
00:23:01,880 --> 00:23:06,060
ุงุซู†ูŠู† ุฃุนู„ู‰ ู„ุฐู„ูƒ 13 ู‡ูŠ ุงู„ู‚ูŠู…ุฉ ุงู„ู…ุชูˆุณุทุฉุŒ ู„ุญุธุฉ
265
00:23:06,060 --> 00:23:11,960
ุงู„ู‚ูŠู…ุฉ ุงู„ู…ุชูˆุณุทุฉ ูƒุงู†ุช 30 ุจุฑุถู‡ ุงู„ู‚ูŠู…ุฉ ุงู„ู…ุชูˆุณุทุฉ
266
00:23:11,960 --> 00:23:14,440
3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ
267
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3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ
268
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3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ
269
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3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ
270
00:23:18,700 --> 00:23:23,340
3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ 3ุŒ
271
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ุงู„ู‚ูŠู…ุฉ ุงู„ู€ median ู…ุง ุชุฃุซุฑุชุด ุจุงู„ู€ extreme value
272
00:23:28,710 --> 00:23:35,250
ู…ุธุจูˆุทุŸ ู‡ู†ุงูƒ ูƒุงู†ุช 14 ุชุฃุซุฑ ุงู„ู€ meanุŒ ุงู„ู€ median ู„ูƒู†
273
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ูˆุงุถุญ ุฅู† ุงู„ู€ median is not affected by largest
274
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value ูŠุนู†ูŠ ุงู„ู€ 15 ูŠุนู†ูŠ ู„ูˆ ุฃู†ุง ุบู…ุถุช ุนู„ูŠู‡ุง ูˆุญุทูŠุช ุจุฏู„ู‡ุง 200 ุชู…ุงู… ุงู„ู€ median ูƒุฏู‡ุŸ 13 ู…ุน ูƒุฏู‡ ุงู„ู€
275
00:23:41,630 --> 00:23:48,210
outliers ู…ุง ู„ู‡ุงุด ู‚ูŠู…ุฉ ู‡ู†ุง ูŠุนู†ูŠ ุงู„ู€ median is not
276
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affected by extreme outliers or outliers as the
277
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meanุŒ ุฅุฐุง ุงู„ู€ median is less sensitive ุฃู‚ู„ ุญุณุงุณูŠุฉ
278
00:23:58,790 --> 00:24:04,910
ู…ู† ุงู„ู€ median ู„ extreme valuesุŒ ู…ุน ูƒุฏู‡ ุงู„ู€ outlier
279
00:24:04,910 --> 00:24:09,710
ุจุชุฃุซุฑ ุนู„ู‰ ุงู„ู€ mean ุฃูƒุซุฑ ู…ู† ุงู„ู€ medianุŒ ุงู„ู€
280
00:24:09,710 --> 00:24:15,810
outlier ุจุชุฃุซุฑ ุนู„ู‰ ุงู„ู€ mean ุฃูƒุซุฑ ู…ู†ู‡ุง ุนู„ู‰ ุงู„ู€ median
281
00:24:15,810 --> 00:24:19,790
ุฅุฐุง ุงู„ู€ outliers ุจุชุฃุซุฑ ุนู„ู‰ ุงู„ู€ mean ุฃูƒุซุฑ ุนู„ู‰ ุงู„ู€ mean
282
00:24:19,790 --> 00:24:24,770
ุงู„ู€ mean ุงู„ู„ูŠ ูุงุช ู„ุญุธุฉ ูƒุงู† 13 ุตุงุฑ 14ุŒ ู‡ู†ุง
283
00:24:24,770 --> 00:24:31,790
ุงู„ู€ median ู…ุง ุฒุงู„ the same value ูŠุนู†ูŠ ุจุนุฏ ูƒุฏู‡ if we
284
00:24:31,790 --> 00:24:36,250
replace the largest value by any other value
285
00:24:36,250 --> 00:24:39,830
larger than that one then the median stay the same
286
00:24:39,830 --> 00:24:43,150
ุจุชุฃุซุฑุด ูˆู„ูˆ ุชุฃุซุฑุช ุชุฃุซูŠุฑู‡ุง ู…ุด ูƒุจูŠุฑุŒ ุชุทู„ุน ุงู„ู€ example
287
00:24:43,150 --> 00:24:47,870
ุงู„ู„ูŠ ูุงุช ู…ู† 1 ุฅู„ู‰ 9 ุญูƒูŠู†ุง ุงู„ู€ mean was 5
288
00:24:47,870 --> 00:24:51,570
ูˆู„ู…ุง ุถูู†ุง ุงู„ู…ุฆุฉ ุตุงุฑ ุงู„ู€ mean 14.5 ุทุจ ุทู„ุน ุงู„ู€ median
289
00:24:53,820 --> 00:25:01,200
ููŠ ุงู„ู€ data ุงู„ุฃูˆู„ู‰ ุฃูˆ ุงู„ู€ median ู…ุง ุชุฃุซุฑุด ู‡ูŠ ููŠ ุงู„ู†ุต
290
00:25:01,200 --> 00:25:08,100
ู…ุธุจูˆุทุŒ ููˆุงุถุญ ุงู„ู€ mean ูˆุงู„ู€ median ู…ุง ู„ู‡ู… ุฒูŠ ุจุนุถ ุฅู„ุง
291
00:25:08,100 --> 00:25:14,560
ู„ู…ุง ุถูุช ุงู„ู…ุฆุฉุŒ ู„ุญุธุฉ ู„ู…ุง ุถูุช ุงู„ู…ุฆุฉ ุนู„ูŠู‡ู…
292
00:25:14,560 --> 00:25:20,000
ุจุทู„ุช ุงู„ุฎู…ุณุฉ ุงู„ู€ median ู„ุฃู†
293
00:25:23,150 --> 00:25:27,930
ุงู„ุฎู…ุณุฉ ุนู„ู‰ ูŠุณุงุฑู‡ุง four values ูˆุนู„ู‰ ูŠู…ูŠู†ู‡ุง ุฎู…ุณุฉุŒ ู‡ุฐุง
294
00:25:27,930 --> 00:25:35,130
ูƒุงู† ุชุณุงูˆูŠ ุฒู…ุงู†ูƒ ูˆู„ูŠุด ู…ูŠุฉุŒ ุทุจ ูˆุงู„ุณุชุฉุŸ ุจุฑุถู‡ ุงู„ุณุชุฉ
295
00:25:35,130 --> 00:25:39,350
ู…ุด the median ู„ุฃู†ู‡ ุนู„ู‰ ูŠุณุงุฑู‡ุง ุฎู…ุณุฉ ูˆุนู„ู‰ ูŠู…ูŠู†ู‡ุง
296
00:25:39,350 --> 00:25:42,590
ุฃุฑุจุนุฉุŒ ุฅุฐุง ุงู„ู€ median ุนุจุงุฑุฉ ุนู† ุงูŠุดุŸ ุงู„ู€ average ู„ู„ู€
297
00:25:42,590 --> 00:25:49,550
middle pointsุŒ ุงู„ู€ average ู„ู‡ุฏูˆู„ ุงุซู†ูŠู†ุŒ ูุงู„ู€ average
298
00:25:49,550 --> 00:25:54,890
ุจุชุงุนู‡ู… ุฎู…ุณุฉ ุฒุงุฆุฏ ุณุชุฉ ุนู„ู‰ ุงุซู†ูŠู†ุŒ 5.5 ุฅุฐุง ู„ู…ุง
299
00:25:54,890 --> 00:26:02,510
ุฃูƒูˆู† ุนู†ุฏูŠ ู‡ุฏูˆู„ ูƒู… ูˆุงุญุฏุฉุŸ ุฃุนุฏู‘ู‡ู… ุนุดุฑุฉ ู…ุด ู‡ูŠูƒุŸ ู„ู…ุง
300
00:26:02,510 --> 00:26:08,910
ูŠูƒูˆู† even ูŠุนู†ูŠ ุนุฏุฏ ุฒูˆุฌูŠ ุจุชุงุฎุฏ ุงู„ู€ average ู„ู„ู€ two
301
00:26:08,910 --> 00:26:15,510
middle pointsุŒ five plus six ุนู„ู‰ ุงุซู†ูŠู† ู„ุญุธุฉุŒ ุงู„ู€
302
00:26:15,510 --> 00:26:19,470
median ูƒุงู† ุฎู…ุณุฉ
303
00:26:19,470 --> 00:26:20,690
ู„ู…ุง ุถูุช ุนู„ูŠู‡ ุงู„ู…ูŠุฉ ุตุงุฑ ุฌุฏูŠู‡ุด 5.5 ุงุชุบูŠุฑุช
304
00:26:23,680 --> 00:26:28,400
ู‚ูŠู…ุชู‡ ู…ู† ุฎู…ุณุฉ ู„ุฎู…ุณุฉ ูˆ ู†ุตูุŒ ุฅุฐุง ุงู„ู€ mean ูƒุงู† ุฎู…ุณุฉ ุตุงุฑุช
305
00:26:28,400 --> 00:26:34,460
14.5 ู„ูƒู† ุงู„ู€ median ูƒุงู†ุช ุฎู…ุณุฉ ุตุงุฑุช 5.5ุŒ ุงู„ู…ุนู†ู‰ ูƒุฏู‡ ู…ูŠู† ุงู„ู€ less sensitiveุŒ ุงู„ู€ mean ูˆู„ุง ุงู„ู€
306
00:26:34,460 --> 00:26:42,140
medianุŒ ุงู„ู€ median ุฃู‚ู„ ุญุณุงุณูŠุฉ ู‡ูˆ ุงุชุบูŠุฑ ู…ู† ุฎู…ุณุฉ ุตุญูŠุญ
307
00:26:42,140 --> 00:26:46,340
ู„ู€ 5.5 ุจุณ ุงู„ุชุบูŠุฑ ุจูŠุจู‚ู‰ ุฃู‚ู„ ู…ู† ุชุบูŠุฑ ุงู„ู€ meanุŒ ุงู„ู€
308
00:26:46,340 --> 00:26:51,050
mean ู…ู† ุฎู…ุณุฉ ู„ู€ 14.5 ูˆุงุถุญ ุฅู† ุงู„ู€ mean ุชุนุชุจุฑ
309
00:26:51,050 --> 00:26:55,210
extreme valueุŒ ุฅุฐุง in general the median is less
310
00:26:55,210 --> 00:26:59,150
sensitive than the mean to extreme valueุŒ ุฃู‚ู„
311
00:26:59,150 --> 00:27:07,450
ุญุณุงุณูŠุฉ
312
00:27:07,450 --> 00:27:10,130
than the mean to extreme value
313
00:27:10,130 --> 00:27:10,750
314
00:27:19,270 --> 00:27:24,230
ุงู„ู€ slide ู‡ุฐู‡ ุจุชุชูƒู„ู… ุนู† ู…ูˆู‚ุน ุงู„ู€ medianุŒ ูƒูŠู ูŠู…ูƒู†ู†ุง
315
00:27:24,230 --> 00:27:28,990
ุชุญุตูŠู„ ู…ูˆู‚ุน ุงู„ู€ medianุŸ ูŠุนู†ูŠ ูƒูŠู ู…ู…ูƒู† ู†ุนู…ู„ ุงู„ู…ูƒุงู†
316
00:27:28,990 --> 00:27:36,890
ุชุจุน ุงู„ู€ medianุŸ ู‡ู†ุงูƒ ุงุซู†ูŠู† ุญุงู„ุงุชุŒ ุฅุฐุง N ุบุฑูŠุจุŒ N
317
00:27:36,890 --> 00:27:43,450
ุงูŠุด ุบุฑูŠุจุŸ ุบุฑูŠุจ ู…ุนู†ุงู‡ ุนุฏุฏ ูุฑุฏูŠุŒ ูุฑุฏูŠ ูŠุนู†ูŠ 3ุŒ
318
00:27:43,450 --> 00:27:48,040
5ุŒ 7ุŒ 9 ูˆู‡ูƒุฐุงุŒ ููŠ ุงู„ุญุงู„ุฉ ุงู„ู€ location of
319
00:27:48,040 --> 00:27:51,260
the median when the values are in numerical order
320
00:27:51,260 --> 00:27:55,380
it means from smallest to largestุŒ the median
321
00:27:55,380 --> 00:28:02,720
position is n plus one over twoุŒ ู‡ูŠ ุงู„ู€ position so
322
00:28:02,720 --> 00:28:11,880
n plus one over twoุŒ for this example n was 5 so
323
00:28:11,880 --> 00:28:13,180
the position of the median
324
00:28:16,120 --> 00:28:22,520
equal 5 plus 1 over 2ุŒ 3ุŒ ุฅุฐุง ุงู„ู…ูƒุงู† ุชุจุน
325
00:28:22,520 --> 00:28:27,440
ุฑู‚ู… 3 ุจุนุฏ ู…ุง ู†ุฑุชุจุŒ ู„ุญุธุฉุŒ ู‡ุฐุง ุงู„ู€ first position
326
00:28:27,440 --> 00:28:33,720
ุงู„ู„ูŠ ู‡ูˆ ู‡ุฐุง ุฃูˆู„ ู…ูƒุงู† ูˆู‡ุฐุง ุงู„ุซุงู†ูŠ ูˆู‡ุฐุง ุงู„ุซุงู„ุซ ูˆู‡ุฐุง
327
00:28:33,720 --> 00:28:38,320
ุงู„ุฑุงุจุน ูˆุงู„ุฎุงู…ุณุŒ ุงู„ู€ median is in the third position
328
00:28:38,320 --> 00:28:41,200
ุงู„ู€ third positionุŒ ู…ูˆู‚ุน ุงู„ุซุงู„ุซ ุงู„ู„ูŠ ู‡ูˆ ุงู„ู€ 13
329
00:28:41,200 --> 00:28:43,820
ู„ุญุธุฉุŒ ุงู„ู€ 3 is not the median
330
00:28:47,860 --> 00:28:52,540
is not the medianุŒ ู‡ุฐุง ุนุจุงุฑุฉ ุนู† ุงู„ู€ position ุชุจุนู‡
331
00:28:52,540 --> 00:28:55,720
position of the medianุŒ ุฅูŠุด ุจูŠุทู„ุน ุฏุงุฆู…ุง ูุฑุฏูŠุŒ ุงู‡ ู„ูˆ
332
00:28:55,720 --> 00:29:01,040
ูƒุงู† ู‡ุฐุง ุงู„ู€ 6 ุนู„ู‰ 2 ูุฑุฏูŠุŒ ู„ูˆ 9ุŒ 9 ุฒูŠ 1
333
00:29:01,040 --> 00:29:07,940
2 ูุฑุฏูŠ ูˆูƒุฐุงุŒ ุทุจ ุงู„ู…ุซู„ุฉ ุนุฏุฏู‡ู… ูƒุงู…ุŸ 9ุŒ 9 ุฒูŠ
334
00:29:07,940 --> 00:29:12,630
1ุŒ 2ุŒ 5 ุงู„ู…ูƒุงู† ุฑู‚ู… 5 ู‡ู†ุง ุทู„ุน 5
335
00:29:12,630 --> 00:29:16,930
ุจุงู„ุตุฏูุฉุŒ ู…ุด ุจุงู„ุถุฑูˆุฑุฉ ูŠุทู„ุน 5 ู‡ูˆ 5ุŒ ู„ุญุธุฉ ู‡ู†ุง ุทู„ุน
336
00:29:16,930 --> 00:29:22,630
ุงู„ุซุงู„ุซ 13 ู…ุด ุจุงู„ุถุฑูˆุฑุฉุŒ ุฅุฐุง ุงู„ู€ median position n
337
00:29:22,630 --> 00:29:27,710
plus one over twoุŒ if the number of values is odd
338
00:29:27,710 --> 00:29:31,650
ุฅุฐุง ุนุฏุฏู‡ู… ูุฑุฏูŠุŒ the median is the middle number
339
00:29:31,650 --> 00:29:38,770
ุงู„ู„ูŠ ู‚ุจู„ ููŠ ุงู„ู†ุตุŒ if the number is evenุŒ ุฅุฐุง ูƒุงู† ุฒูˆุฌูŠ
340
00:29:38,770 --> 00:29:42,950
ุฒูŠ ู‡ูŠูƒ ู„ู…ุง ุถูู†ุง ุงู„ู…ูŠุฉุŒ ุชูˆุฅุฐุง ูƒุงู†ุช ุงู„ู…ู‚ุงู„ุฉ ู…ุฑุชุจุทุฉุŒ
341
00:29:42,950 --> 00:29:45,970
ูุฅู† ู…ู‚ุงู„ุฉ ุงู„ู€ median ู‡ูŠ ุนุงู…ู„ุฉ ุงู„ุงุซู†ูŠู† ุงู„ู…ู‚ุงู„ูŠู† ุฃูˆ
342
00:29:45,970 --> 00:29:49,430
ุงู„ุงุซู†ูŠู† ุงู„ู…ู‚ุงู„ูŠู†ุŒ ู„ุญุธุฉุŒ ู‡ู†ุง ุฃุฎุฐู†ุง ุนุงู…ู„ุฉ ุงู„ุงุซู†ูŠู†
343
00:29:49,430 --> 00:29:55,850
ุงู„ู…ู‚ุงู„ูŠู† ู„ู€ 5 ูˆ 6 ูˆ 2ุŒ ูˆุงุจู‚ู‰ ููŠ ุฐูƒุฑ ุฃู† N plus 1 over 2 ู„ูŠุณ
344
00:29:55,850 --> 00:30:01,450
ู…ู‚ุงู„ุฉ ุงู„ู€ median ูู‚ุท
345
00:30:01,450 --> 00:30:06,570
ู…ู‚ุงู„ุฉ ุงู„ู€ median ููŠ ุญุงู„ุฉ ุนุงู…ู„ุฉุŒ ุฅุฐุง ุงู„ู…ูƒุงู† ุชุจุนู‡ N plus
346
00:30:06,570 --> 00:30:09,450
1 over 2ุŒ ูŠุนู†ูŠ ู„ูˆ ูƒุงู† ู…ุฎุชุงุฑ ู…ุฑุชุจุทุŒ ุญูƒูŠู†ุง ุงูŠุด ุงู„ู€ position
347
00:30:11,720 --> 00:30:16,720
ุชุจุนู‡ุŒ ุงู„ู€ equation ุนุจุงุฑุฉ ุนู† n plus one over two ู‡ุฐุง
348
00:30:16,720 --> 00:30:21,460
ู„ูˆ ูƒุงู†ุช n is oddุŒ ุฅุฐุง ูƒุงู† even ุจู†ุงุฎุฏ ุงู„ู€ middle ุงู„ู€
349
00:30:21,460 --> 00:30:25,000
average ู„ู€ two middle pointsุŒ ุทุจุนุง ุงู„ู€ two middle
350
00:30:25,000 --> 00:30:37,620
points ุงู„ู„ูŠ ุทู„ุน ุนู„ูŠู‡ู… ู‡ู†ุงุŒ suppose
351
00:30:37,620 --> 00:30:42,820
we have this dataุŒ ุงู„ุขู† even ุฃูˆ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
352
00:30:42,820 --> 00:30:44,880
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
353
00:30:44,880 --> 00:30:45,380
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
354
00:30:45,380 --> 00:30:51,420
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
355
00:30:51,420 --> 00:30:53,600
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
356
00:30:53,600 --> 00:30:53,700
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
357
00:30:53,700 --> 00:30:53,740
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
358
00:30:53,740 --> 00:30:54,860
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
359
00:30:54,860 --> 00:30:56,060
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
360
00:30:56,060 --> 00:30:59,120
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
361
00:30:59,120 --> 00:31:05,200
ุบูŠุฑ ุบูŠุฑ ุบูŠุฑ
362
00:31:05,200 --> 00:31:08,360
ุบูŠุฑ ุบ
363
00:31:11,670 --> 00:31:20,710
ู‚ูŠู…ุฉ ุงู„ู€ x3 ุนุจุงุฑุฉ ุนู† 9ุŒ ูˆุงู„ุซุงู†ูŠุฉ ุนุจุงุฑุฉ ุนู† 2ุŒ 9 plus
364
00:31:20,710 --> 00:31:28,530
12 ุนุจุงุฑุฉ ุนู† 21 ูŠุนู†ูŠ 10.5 ุฒูŠ ุงู„ู€ median 10.5ุŒ ุทูŠุจ x
365
00:31:28,530 --> 00:31:33,170
3 ู‡ุฐู‡ ุนุจุงุฑุฉ ุนู† ู…ูˆุฌุฉ ุงู„ุซุงู„ุซุŒ x4 ู…ูˆุฌุฉ ุงู„ุฑุงุจุนุŒ ูƒูŠู
366
00:31:33,170 --> 00:31:41,950
ุทู„ุนู†ุง ุงู„ุซู„ุงุซุฉ ุงู„ุขู† 6 ู…ุธุจูˆุทุŒ ู n over 2 ุจุชู‚ุนุฏ x6 ุนู„ู‰
367
00:31:41,950 --> 00:31:45,410
2ุŒ ุงู„ุซู„ุงุซุฉ ูˆุงู„ู„ูŠ ุจุนุฏู‡ ุงู„ู„ูŠ ุจุนุฏู‡ ุงู„ู„ูŠ ู‡ูˆ x
368
00:31:45,410 --> 00:31:49,290
4 ุงู„ู„ูŠ ู‡ูˆ ุนุจุงุฑุฉ ุนู† ู…ูŠู†ุŸ xn over 2 ุฒุงุฆุฏ
369
00:31:49,290 --> 00:31:54,150
1ุŒ ูู„ู…ุง ุจูƒูˆู† ุนู†ุฏูŠ even numberุŒ ุงู„ู€ position ุจูƒูˆู†
370
00:31:54,150 --> 00:31:58,690
n over 2 ูˆุงู„ู„ูŠ ุจุนุฏู‡ุŒ n over 2 in the next
371
00:31:58,690 --> 00:32:06,110
numberุŒ ูŠุนู†ูŠ ู„ูˆ ู…ุซู„ุง ุฒูŠ ู‡ูŠูƒ ู…ู† 1 ู„ุบุงูŠุฉ 100 ูŠุนู†ูŠ
372
00:32:06,110 --> 00:32:09,610
n ุจู€ 17 ู…ุด ู‡ูŠูƒุŒ ุงู„ู€ median ุนุจุงุฑุฉ ุนู† ุฅูŠุด ุงู„ู€
373
00:32:09,610 --> 00:32:16,510
position ุชุจุนู‡ู… n over 2 ูˆุงู„ู„ูŠ ุจุนุฏู‡ุŒ ู…ูŠู† n over 2ุŸ ู‡ุงูŠ n
374
00:32:16,510 --> 00:32:23,350
over 2ุŒ 10 ุนู„ู‰ 2ุŒ 5 ูˆุงู„ู„ูŠ ุจุนุฏู‡ ุงู„ุณุงุฏุณุฉุŒ 5 ูˆุงู„ู€
375
00:32:23,350 --> 00:32:32,080
ุงู„ุณุงุฏุณุฉ ุฎู„ุงุตุŸ ุฅุฐุง the median is the averageุŒ ุงู„ู…ุนู†ู‰ ู‡ูŠ
376
00:32:32,080 --> 00:32:36,220
ุนุฏุฏ ุงู„ู…ู‚ุงูˆู…ุงุชุŒ ุงู„ู…ู‚ุงูˆู…ุฉ ุจู€ NุŒ ุงู„ู…ู‚ุงูˆู…ุฉ ู‡ูŠ ุงู„ู‚ูŠู…ุฉ
377
00:32:36,220 --> 00:32:38,980
ููŠ ุงู„ู…ู‚ุงูˆู…ุฉ ุจุนุฏ ุฃู†ู†ุง ู‚ู…ู†ุง ุจุชุฌู‡ูŠุฒ ุงู„ุจูŠุงู†ุงุช ู…ู† ุฃูƒุซุฑ
378
00:32:38,980 --> 00:32:44,920
ู„ุฃูƒุซุฑ ุฃูˆ ุฃูƒุซุฑ ุฅู„ู‰ ุฃูƒุซุฑุŒ ุฅุฐุง ูƒุงู†ุช N ุบูŠุฑ ู…ุญุฏูˆุฏุฉุŒ
379
00:32:44,920 --> 00:32:48,980
ูู…ู‚ุงูˆู…ุฉ ุงู„ู€ median ู‡ูŠ N plus one over twoุŒ ุฅู„ุง ุฅุฐุง
380
00:32:48,980 --> 00:32:52,080
ูƒุงู†ุช N ู…ุฑุชุจุทุฉุŒ ูู…ู‚ุงูˆู…ุฉ ุงู„ู€ N ู‡ูŠ ุนุฏุฏ ุงู„ู…ู‚ุงูˆู…ุฉ ุจูŠู†
381
00:32:52,080 --> 00:32:54,420
ุงู„ุงุซู†ูŠู† ู…ู‚ุงูˆู…ุฉุŒ ุงู„ู…ู‚ุงูˆู…ุฉ ุจูŠู† ุงู„ุงุซู†ูŠู† ู…ู‚ุงูˆู…ุฉ
382
00:32:54,420 --> 00:33:03,830
ุงู„ู…ู‚ุงูˆู…ุฉ ููŠ ุงู„ู…ูˆู‚ุน xn2 ูˆุงู„ุชุงู„ูŠ xn2 plus 1ุŒ ู…ุซู„ุง ู…ุฑุฉ
383
00:33:03,830 --> 00:33:10,390
ุฃุฎุฑู‰ุŒ ูุฅู† ุงู„ู€ n ู‡ูˆ 20ุŒ ูู…ุงุฐุง
384
00:33:10,390 --> 00:33:15,070
ู‡ูŠ ุงู„ู…ู‚ุงูˆู…ุฉ ุงู„ู…ุชูˆุณุทุฉุŸ
385
00:33:15,070 --> 00:33:22,730
ุงู„ู€ n 20 ูŠุนู†ูŠ ุฃู† ู‡ู†ุงูƒ ู…ู‚ุงูˆู…ุฉ ู…ุฎุชู„ูุฉ ุงู„ู„ูŠ ู‡ูˆ ู…ูŠู†ุŸ n
386
00:33:22,730 --> 00:33:27,650
ุนู„ู‰ 2 ูˆุงู„ู„ูŠ ุจุนุฏู‡ุŒ N ุนู„ู‰ 2 ูŠุนู†ูŠ 10 ูˆุงู„ู„ูŠ ุจุนุฏู‡ 11
387
00:33:27,
431
00:37:25,290 --> 00:37:31,050
ุงู„ุฃุญูŠุงู† ู…ู…ูƒู† ูŠูƒูˆู† ุนู†ุฏูƒ ุฃูƒุซุฑ ู…ู† ู…ูˆุถูˆุน ุฅุฐุง ุงู„ู…ูˆุถูˆุน
432
00:37:31,050 --> 00:37:39,110
ุฃูƒุซุฑ ุงุณุชู…ุฑุงุฑุง ุฃูˆ ุฃูƒุซุฑ ุญุฏูˆุซุง ู‚ูŠู…ุฉ ุงู„ุฃูƒุซุฑ ุธู‡ูˆุฑุง ุฃูˆ ุฃูƒุซุฑ
433
00:37:39,110 --> 00:37:43,310
ุชูƒุฑุงุฑุง ุฃูˆ ุฃูƒุซุฑ ุญุฏูˆุซุง ู„ูˆ ุทู„ุนุช ุนู„ู‰ ุงู„ data ุงู„ู„ูŠ ู‡ู†ุง
434
00:37:43,310 --> 00:37:47,450
ู†ุญู†
435
00:37:47,450 --> 00:37:53,140
ู„ุง ู„ุฏูŠู†ุง ู†ู‚ุทุฉ ูˆุงุญุฏุฉ ุฃูƒุซุฑ ู…ุฑุฉ 3 ู…ุฑุงุชุŒ 5 ู…ุฑุงุช ู…ุฑุชูŠู†ุŒ 8
436
00:37:53,140 --> 00:37:57,440
ู…ุฑุฉ ู…ุฑุชูŠู†ุŒ 10 ู…ุฑุงุช ู…ุฑุชูŠู†ุŒ 12 ู…ุฑุฉ ู…ุฑุชูŠู†ุŒ 13 ู…ุฑุฉ
437
00:37:57,440 --> 00:38:02,280
ู…ุฑุชูŠู† ูˆ 14 ู…ุฑุฉ ู…ุฑุชูŠู† ุงู„ุขู† ู…ุงู‡ูŠ ุฃูƒุซุฑ ู‚ูŠู…ุฉ ู…ุนู„ูˆู…ุฉ
438
00:38:02,280 --> 00:38:04,320
ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ
439
00:38:04,320 --> 00:38:07,320
ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ
440
00:38:07,320 --> 00:38:07,460
ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ
441
00:38:07,460 --> 00:38:08,520
ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ
442
00:38:08,520 --> 00:38:18,560
ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…ุฉ ู…ุนู„ูˆู…
443
00:38:20,330 --> 00:38:30,930
ู…ุซู„ ู‡ุฐุง ุงู„ู…ุซุงู„ ู‡ู†ุง ู†ุญู† ู„ุฏูŠู†ุง 1 3 4 2 5 3 9 10 12
444
00:38:30,930 --> 00:38:39,470
12 13 ูˆ 14 9 ู…ู…ูƒู† 3 ู…ุฑุงุช ูุงู„ุนุฏุฏ 9 ูููŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ
445
00:38:39,470 --> 00:38:48,350
ูู‡ู†ุงูƒ ูู‚ุท ุนุฏุฏ ูˆุงุญุฏ ูุงู„ุนุฏุฏ 9 ู„ู„ู…ุซุงู„
446
00:38:48,350 --> 00:38:57,790
ุงู„ุขุฎุฑ ู†ุญู† ู„ุฏูŠู†ุง 0ุŒ 1ุŒ 2ุŒ 3ุŒ 5 ูˆ 6 ููŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ ูƒู„
447
00:38:57,790 --> 00:39:03,330
ู‚ูŠู…ุฉ ุชุญุฏุซ ู…ุฑุฉ ูˆุงุญุฏุฉ ู‡ุฐุง ูŠุนู†ูŠ ููŠ ู‡ุฐู‡ ุงู„ุญุงู„ุฉ ู„ูŠุณ
448
00:39:03,330 --> 00:39:12,370
ู‡ู†ุงูƒ ู…ูˆุถูˆุน ุทุจ ู„ูˆ ุฒูˆุฏุช ูˆุงุญุฏุฉ ู‡ู†ุง
449
00:39:12,370 --> 00:39:15,550
ู…ุน
450
00:39:15,550 --> 00:39:21,620
ูƒุฏู‡ two modes ุงู„ู„ูŠ ู‡ูˆ ุงู„ุฎู…ุณุฉ ูˆุงู„ุชุณุนุฉ five ูˆ nine ุทุจ
451
00:39:21,620 --> 00:39:27,060
ู„ูˆ ุฌุฆุช ู‡ู†ุง ุฒูˆุฏุช ูˆุงุญุฏุฉ ู„ู„ุณุชุฉ ุจุตูŠุฑ ุงู„ุณุชุฉ ู‡ูŠ ุงู„ mode
452
00:39:27,060 --> 00:39:33,740
ู…ุตุจูˆุฑุงุŸ ู„ุฃู† ุงู„ุณุชุฉ ู‡ูŠ ุงู„ุฃูƒุซุฑ ุชูƒุฑุงุฑุง ู…ุฑุชูŠู† ุทุจ ู„ูˆ ูƒุฑุฑุช
453
00:39:33,740 --> 00:39:40,800
ู‡ูŠูƒ ุตุงุฑ ุงู„ุงุซู†ูŠู† ูˆุงู„ุซู„ุงุซุฉ ูˆุงู„ุณุชุฉ ู‡ู…ุง ุงู„ modes ุฅุฐุง
454
00:39:40,800 --> 00:39:45,280
ู…ู…ูƒู† ูŠูƒูˆู† there is only one mode or sometimes the
455
00:39:45,280 --> 00:39:48,340
mode does not exist ุฃูˆ there are
456
00:39:51,720 --> 00:39:57,480
ู…ู…ูƒู† ูŠูƒูˆู† ู…ูˆุฌูˆุฏ ุฃูˆ ุบูŠุฑ ู…ูˆุฌูˆุฏ ู…ู…ูƒู†
457
00:39:57,480 --> 00:40:02,000
ูŠูƒูˆู† ู…ูˆุฌูˆุฏ ุฃูˆ ุบูŠุฑ ู…ูˆุฌูˆุฏ ู…ู…ูƒู† ูŠูƒูˆู† ู…ูˆุฌูˆุฏ ุฃูˆ ุบูŠุฑ
458
00:40:02,000 --> 00:40:06,440
ู…ูˆุฌูˆุฏ ุฏุนูˆู†ุง
459
00:40:06,440 --> 00:40:08,860
ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง
460
00:40:08,860 --> 00:40:09,360
ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ
461
00:40:09,360 --> 00:40:09,640
ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„
462
00:40:09,640 --> 00:40:12,700
ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰
463
00:40:12,700 --> 00:40:12,760
ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ
464
00:40:12,760 --> 00:40:13,400
ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„
465
00:40:13,400 --> 00:40:15,800
ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰ ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุนูˆู†ุง ู†ู„ู‚ูŠ ู†ุธุฑุฉ ุนู„ู‰
466
00:40:15,800 --> 00:40:19,640
ู‡ุฐุง ุงู„ู…ุซุงู„ ุฏุน
467
00:40:19,720 --> 00:40:25,640
100 ูˆ 100 ูˆ ุฏุนูˆู†ุง ู†ุฑู‰ ูƒูŠู ู†ุณุชุฎุฏู… ุงู„ุงู†ุชุงุฌ ุงู„ุงู†ุชุงุฌ
468
00:40:25,640 --> 00:40:29,020
ุงู„ุงู†ุชุงุฌ
469
00:40:29,020 --> 00:40:35,600
ู‡ูˆ ุฅุถุงูุฉ ู‡ุฐู‡ ุงู„ู‚ูŠู… ุซู… ู†ู‚ู„ ู…ู† ุนุฏุฏ ุงู„ู…ู†ุฒู„ ุงู„ุงู†ุชุงุฌ
470
00:40:35,600 --> 00:40:44,320
ุชุจุนู‡ู… ุนู„ู‰ ุนุฏุฏู‡ู… ูˆุงุถุญ ู…ุฌู…ูˆุนู‡ู… 3 ู…ู„ูŠูˆู† ู†ู‚ู„ ู…ู† 5 ูŠุนู†ูŠ
471
00:40:44,320 --> 00:40:51,320
600000 ุฅุฐุง ุงู„ุงู†ุชุงุฌ ุชุจุนู‡ู… 600000 ุงู„ูˆุณุท ูŠุฌุจ ุฃู†
472
00:40:51,320 --> 00:40:53,820
ู†ุฎู„ู‚ู‡ ู…ู† ุฃูƒุจุฑ ุฅู„ู‰ ุฃูƒุจุฑ ุฃูˆ ุฃูƒุจุฑ ุฅู„ู‰ ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ
473
00:40:53,820 --> 00:40:56,540
ุฅู„ู‰ ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ
474
00:40:56,540 --> 00:40:57,880
ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู†
475
00:40:57,880 --> 00:40:59,820
ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู†
476
00:40:59,820 --> 00:41:03,880
ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู†
477
00:41:03,880 --> 00:41:06,180
ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู†
478
00:41:06,180 --> 00:41:06,500
ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู†
479
00:41:06,500 --> 00:41:16,000
ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒุจุฑ ู…ู† ุฃูƒ
480
00:41:17,180 --> 00:41:20,660
ุงู„ู€ mean ู„ุฃู†ู‡ ุฃุฎุฐ ูƒู„ ุงู„ู€ values ูุชุฃุซุฑ ุจุงู„ู€ mean
481
00:41:20,660 --> 00:41:24,700
ุจุงู„ู€ extreme ุจุงู„ู€ 200 ุฃู„ู ูˆ ุจุงู„ู€ 2 ู…ู„ูŠูˆู† ูˆ ุชุฃุซุฑ
482
00:41:24,700 --> 00:41:27,980
ุจุงู„ู€ 100 ุฃู„ู ุงู„ู„ูŠ ุชุญุช ู„ุฃู†ู‡ ุชุนุชุจุฑ 100 ุจุนูŠุฏุฉ ุนู† ุงู„ู€
483
00:41:27,980 --> 00:41:30,400
2 ู…ู„ูŠูˆู† ูˆ ุงู„ู€ 2 ู…ู„ูŠูˆู† ุจุนูŠุฏุฉ ุนู† ุงู„ูƒู„ ุจุงู„ุชุงู„ูŠ ู‡ูˆ
484
00:41:30,400 --> 00:41:35,620
ุชุฃุซุฑ ุจุงู„ู€ 2 ู…ู„ูŠูˆู† ุฃูƒุซุฑ ูุงู„ู€ median ุทู„ุน 300 ุฃู„ู ุทุจ
485
00:41:35,620 --> 00:41:39,160
ุงู„ูˆุถุน is the most frequent value ุงู„ู‚ูŠู…ุฉ ุงู„ุฃูƒุซุฑ
486
00:41:39,160 --> 00:41:43,880
ุชูƒุฑุงุฑุง ุฃูƒุซุฑ ูˆุงุญุฏุฉ ูƒุฑุฑุช 100 ุฃู„ู ู„ุญุธุฉ ุฃู† ุงู„ุขู† three
487
00:41:43,880 --> 00:41:47,760
different measures for center tendency main,
488
00:41:48,060 --> 00:41:54,300
median, mode ุงู„ุขู† ุงู„ุณุคุงู„ ู‡ูˆ ุฃูŠ ุงู„ู…ู‚ูŠุงุณ ุงู„ุฐูŠ ู„ุงุฒู…
489
00:41:54,300 --> 00:41:59,320
ุฃุณุชุฎุฏู…ู‡ ู‡ู„ ู‡ูˆ ุงู„ main ูˆ ู„ุง ุงู„ median ูˆ ู„ุง ุงู„ mode
490
00:41:59,320 --> 00:42:03,800
ุฅู† ุดุงุก ุงู„ู„ู‡ for next time ุฅุฐุง ุงู„ู…ุฑุฉ ุงู„ู‚ุงุฏู…ุฉ ู‡ุชูƒู„ู…
491
00:42:03,800 --> 00:42:10,660
ุนู„ู‰ ู…ู† ุฃูุถู„ ู…ู‚ูŠุงุณ ููŠ ู‡ุฏูˆู„ ูˆุจุนุฏูŠู† ุจู†ูƒู…ู„ ุฎู„ุงุต
492
00:42:10,660 --> 00:42:15,920
ุนู†ุฏู†ุง two slides ุจุณ ู…ูˆุฌูˆุฏุงุช ูˆุจุนุฏูŠู† ู†ุจุฏุฃ ููŠ ุงู„
493
00:42:15,920 --> 00:42:16,900
measures of variation
494
00:42:20,030 --> 00:42:22,550
Any questionุŸ ุงู„ู„ู‡ ุฃูƒุจุฑ