HW2_solutions

# HW2_solutions - STA 368 HW 2 SOLUTIONS FALL 2009 Part I:...

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Unformatted text preview: STA 368 HW 2 SOLUTIONS FALL 2009 Part I: This is more like a mini-project and the summary statistics reported will be different for each person, since each student collected his/her own data set. I will give an example: back to the first class, I collected information about the amount of money spent by the students for the last haircut. If we ignore people who had haircut in another country and who claimed having no haircut at all, here are the numbers I collected: 12, O, 20, O, 15, 16, 12, 15, 2, 5, 25, 70, 14, 12, 12, 0, 18, 25, 40, 30, 7.99, O, 15, 18, 14, 12, 0, 20, O, 15, 15, 32, O, 30, 17, 10, O, 30, 13, O, 20, 50, 15, 10, 18, 10, O, 15, 29, 26, 18, 30, 15, 24, 0, 10, O 2 [1565 773’ 660.5055 dun: €654 \ R code: X<—C(12, O, 20, 0, 15, 16, 12, 15, 2, S, 25, 70, 14, 12, 12, O, 18, 25, 40, 30, 7.99, O, 15, 18, 14, 12, O, 20, O, 15, 15, 32, O, 30, 17, 10, O, 30, 13, O, 20, 50, 15, 10, 18, 10, 0, 15, 29, 26, 18, 30, 15, 24, O, 10, O) mean(x) 5' [pfs 7L9? Curie median(x) var(x) quantile(x,0.05) quantile(x,0.78) R output: ******************************\$*****************\$\$******\$ > mean(x) [1] 15.47351 > median(x) [1] 15 >var(x) [1] 177.3993 > quantile(x,0.05) 5% > quantile(x,0.78) 78% 22.72 **********=l=********************************************** YZHAS‘ FWLX): (24; XP AXE *6/99 /97€id£cre,,iywwﬁ ‘ ’0 “ n y ‘ I ‘v.’ ”" ‘3— /- ... —-:"" Z M Y: I“ {:7 N ' l0 m X 222; T“ 7 = 6575 [<3 Liv) . ,~ Wr‘ 7' Libya‘LT) : I'OH ( \[L la . “if .. ’ Xe I” f” 1&7 L "W3 ” 2.29;) W, ‘ 2 Xd (’2 [lg/h.) (2.215) L LLAJS‘) I ML.— [3 SL “ 12/»; ) " 17 1,750» S/xJV/‘ﬂ )‘71 EA} Liz/“c mag.th V 1, p 573%? fav ﬂavor? I ‘f (aware ) (5577 "6'5 fﬂ (viva-Va??? Viv-Q ‘T/ Can/.3111? ...
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## This note was uploaded on 02/03/2010 for the course A a taught by Professor A during the Spring '10 term at Miami University.

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HW2_solutions - STA 368 HW 2 SOLUTIONS FALL 2009 Part I:...

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