L11Binomial - MGT 2250 _ Lesson 11 Discrete Probability...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Background image of page 2
Background image of page 3
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: MGT 2250 _ Lesson 11 Discrete Probability Distributions: Binomial Distribution J 11119 21, 2011 Development of the binomial distribution: Wattm fl 9mg} 42;: A Pogmmif 2: u”; ’Pumzmgggm EUCCMCSJ LIB Pfsiag Na Pofinwéfg-m flqufléftfl raw? $Ct’g??? fiappfiflf r out: fl?” Wfifir j‘wfmgmME r1 6 V5 55 (35% :33 ’3“ W} K ‘V’i‘? V 33??!)a; mgiééfiflfl gfigfimg m w” xérgjm/M‘ {3’45}; (étjflufix {La/f gig/:33”; 93%? g («1 ’5 g #3 W} C} ? M? 2 iv. 6;”: a: fig: {:3 a, f {3: ,__, f < The binomial distributian has the feilowing feur essential characteristics: i) 566546,} <13 [i 324.,“ :QéI/W'YC my T;}Lifl“€j ‘2) E; “L 53W“? Q {Q‘Qfifjgpfi’ mfiammgg 1%? @Mfi flaw-L 3.. S’u-CCHS (5/) {iflwwofif fiwa 3) ?C# F Fri/Lle if} T@: @afi apo£?fifl@i&wx f The bincmiai formuia: {um/134% amt; ¢%flfiffl%f Th Trig/2:6» .«W _, r _ , _ x h f.” , ; gm 2’: @523; gm” ma; 3: g ’3? 55/ m. r"; I”; “"3? "PM? a W » r* < r m A. f M Raj” “ ,,- If» ' :“Ygg '1‘ «5M 3 % v‘ " «a. w ’ 2: :1 f ‘ ‘“ m g g { My w Lia ; ' ("a " 07%;: "m; ,1/ r“- ; "«" “W: 0"“? (M (2} 42% L 5 awn-9 " ’3 M . , a: M; a ‘ ":3 «gig/£25; w “5‘54 W" N ‘ < f M "3‘ *3 sh w? a (a; «,2, fig, M} 5/3“ {:3} ,_ N} g f ‘1\ if g [i 'w ' .r m,“ / NE a, 11:; . 4+ W 4‘! tr ' s * EL” if 5‘ «1: E if f if g ’° "3 " “l “‘5’ was w , m; aw niémr& W x W»? m? If . it.» c": f! . ' we I it} ‘ ’ g ‘ u” i ' Mi _ t A géiwfiggf a» z W». m a , “E. fay/J" gyg; {I} it”, A W5 1" 15!; Mi... {W é” fig" y I if“ if Egg; 9 fit; {2 E“? I f . LIV”) I; > / M (r f - a affix, *«WV V M.” V x at, M g NW“ A: s. 1}“ (rm f" i i . y 9 Jiff if _ wwwwww ,. 3 1‘ WWW“ y f w; { w A; mm ‘ // #5: J F j d K5 K” r it?) HMS fitth 06% W?“ M? fig “2;. 63 W: “h i 3%“ Md * “if? (L @722 my; x“? f Example: An electronics store has determined that on average 40% of customers entering the store will make a purchase. Given this: Lg? w r w... %?if k t ’L 2- i Q a) What is the probability that 2 of the next 5 customers entering the % store will make a purchase? l, s“ t 3 3963? “ (5%} ? (in) (it!) {GIL} ) .3 c/ré E. ’fl '1“ ‘ f g 99/ f ; fez . L s v , ‘ b) What is the probability that all 5 of the next 5 customers entering ,1?” the store will make a purchase? C} o t 5" (r (6“? fix 3a.,Wwf” Q l:>(1 (3‘ §F(E:?)£ \E;nget What is the probability that 0 of the next 5 customers ent {rmg‘tmhe store will make a purchase? . r; mx’K 33 f @3t k i “with” f‘hi UZ<§W¢fir #- 6) d) What is the grahability that 1 or more of the next 5 custom *rs entering the store Wili make a purchase? “2‘ Viewihgffleee a», Man... e} “Hist is the expected value et'this distribution. mew—N WM‘K if J’ %m ,, g . m g “new”; 1; fix 2' ’ a r it. Nu ‘ a/j ‘ - . g m? k i} ‘What is the standard tieviation (if this distribution. WW”: m r” M MW W ...
View Full Document

Page1 / 3

L11Binomial - MGT 2250 _ Lesson 11 Discrete Probability...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online