9.1 Multinomial

# 9.1 Multinomial - 2mm Howvwmr com mum RR,im*f,8m~i

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Unformatted text preview: 2mm Howvwmr com mum: RR),im*f,8m~i,<i,\00i imam) Section 9.1 Categorical Data and the Multinomial Experiment Categorical data — categories: Male, Female M, T, W, Th, F f” ‘ u inomia x erimen: ldfnllWTl ”Wylie. “filtroﬁﬁllEbFI’e outigm‘iggwgpggghunles oi mesa ouiLomes (PU?) H it) are com aim or emmiilml. . '(EH (ounii (Huh).-hr) m1€ih€ ttﬂ 0b§.lh (mth Oi K-(AmsSBL 1, 2 - thlGIll ll Section 9.2 One Way Tables Multinomial experiment with one qualitative variable Re uiredcondiionzm \ no \ ex ﬁllmﬁm WI rmndum gmmi’le mime enmtighs gcnuni‘pigmggh 5,125 ewemd Loom/frequency M “d, ““um?!‘ @QQmNEIﬁ‘ ‘9‘)“ ._ _ 2 Test statistic: X2 = 2’: [fl—i]— ,_1 E: Ei=expected cell count = npi . Rejection region: REJEUI no If X42) X1206 ic-l Qualitative DGIIOI‘Ch-Ol DJLM lciF Ex: Reports have shown that 25% of American people know they are going to vote Republican, 25% know they are going to vote Democrat, and 50% don’t know how they will vote. In a recent random sample of American people, 78 said they will vote Republican, 50 said they will vote Democrat, and 182 said they did n’t know. Can you conclude at the 5% significance level that the reports are inaccurate? ,9 M 9.225 PQ’QS [735.50 (thiGGddWl) v rm: m lCOlii one P. is net as SiCLliiEd l I 2: 3" “ meet no if X3>Xl-Ob,3‘l x1> 5mm n: 18 To: x2:E(“3’“'-’1 nuoolm m . 2 him . (18'9”: 1 WWW) , oat-win 6.: 3)0(-)s)-6b 60 so M 31:31009’5" )C = .05 t 5 1 3.015 63531069460 X2. 8.01? . ”\$96 idiom??? BMW“ it conclude ihc terms excev DDXL, tablet, gioodncss 0i ﬁtgomICQom (marrow ' Tmloie mm 3 WM RBSV ...
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