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xplain why x follows a binomial distabuton . blnsfead of using What probabilcty use to appoximate the distabution of X? Explain and state relevant para- meter value (5). ()Approximate the Probabulity that more than '200 customers' order pepperonL DA heur pizza. (4 Charactenstics) the bunomial distnbution istnbution Could you any

xplain why x follows a binomial distabuton . blnsfead of using What probabilcty use to appoximate the distabution of X? Explain and state relevant para- meter value (5). ()Approximate the Probabulity that more than '200 customers' order pepperonL DA heur pizza. (4 Charactenstics) the bunomial distnbution istnbution Could you any

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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X sepresents the number of customers'who order'pepperon on theur PUZza then X At Paulis Pizzeria, Folo Dff all cusfomers a random'Sample of 300 cusfomers. If Quesfion? order peppe S randonSample of 300 roni on ther PUZza. Consider a'bunomjal disfabution with 0.7 follows D=300 and ajexplain why X follows a bnomial distnbut bllnsfead of wsing the bunomial dustnbution What probability disfnbution could you useto appnximate the dista bution of X? Explain and state y relevant meter value (5). () Approximate the Probabulity that more than '200 customers' order pepperoni DA heur puzza (4'Charactenstics) any Pard-
Transcribed Image Text:X sepresents the number of customers'who order'pepperon on theur PUZza then X At Paulis Pizzeria, Folo Dff all cusfomers a random'Sample of 300 cusfomers. If Quesfion? order peppe S randonSample of 300 roni on ther PUZza. Consider a'bunomjal disfabution with 0.7 follows D=300 and ajexplain why X follows a bnomial distnbut bllnsfead of wsing the bunomial dustnbution What probability disfnbution could you useto appnximate the dista bution of X? Explain and state y relevant meter value (5). () Approximate the Probabulity that more than '200 customers' order pepperoni DA heur puzza (4'Charactenstics) any Pard-
C CM CHAPTER 2 (EF,. 1 n-1 n-1 Position of the pth percentile (n+1) %3D 100 CHAPTER 3 Sxy , Sxy = SxSy regression line: y=a+bx, b r(), a y-bx n-1 CHAPTER 4 For any two events A and B P(AUB) = P(A) + P(B) – P(A B) and if A and B are mutually exclusive events, then • P(A“) = 1– P(A) P(AN B) = 0 If A and B are 2 independent events, then P(AN B) = P(A) x P(B) Conditional probability: If A and B are 2 events, then P(ANB) P(A|B) = P(B) Bayes Rule: P(S\A) P(SNA) %3D P(Si).P(A|St) %3D P(A) E-1 P(S:).P(A|Si) n! • pn = (n-r)! n! C = r!(n-r)! E (X) = E, xip(x,), v(X) = E, x7p(x;) -E, x;p(x;))' = E(Xx²) – (E(X))? CHAPTER 5 Distribution Probability Mass Function Mean Variance Binomial P(X=x)=C#p°(1-p*, x= 0,1,..n пр пр(1 - р) Poisson P(X = x) = ' ,x = 0,1,... M(N-MN- Hypergeometric P(X=x)3D CN N N- Approximations: If n/N <0.05(N/n 220), then the hypergeometric distribution can be approximated by the binomial distribution with parameters n and p = MIN. If p is small, n is large, and np <7, then the binomial distribution can be approximated by the Poisson distribution with u = np. MacBook Air
Transcribed Image Text:C CM CHAPTER 2 (EF,. 1 n-1 n-1 Position of the pth percentile (n+1) %3D 100 CHAPTER 3 Sxy , Sxy = SxSy regression line: y=a+bx, b r(), a y-bx n-1 CHAPTER 4 For any two events A and B P(AUB) = P(A) + P(B) – P(A B) and if A and B are mutually exclusive events, then • P(A“) = 1– P(A) P(AN B) = 0 If A and B are 2 independent events, then P(AN B) = P(A) x P(B) Conditional probability: If A and B are 2 events, then P(ANB) P(A|B) = P(B) Bayes Rule: P(S\A) P(SNA) %3D P(Si).P(A|St) %3D P(A) E-1 P(S:).P(A|Si) n! • pn = (n-r)! n! C = r!(n-r)! E (X) = E, xip(x,), v(X) = E, x7p(x;) -E, x;p(x;))' = E(Xx²) – (E(X))? CHAPTER 5 Distribution Probability Mass Function Mean Variance Binomial P(X=x)=C#p°(1-p*, x= 0,1,..n пр пр(1 - р) Poisson P(X = x) = ' ,x = 0,1,... M(N-MN- Hypergeometric P(X=x)3D CN N N- Approximations: If n/N <0.05(N/n 220), then the hypergeometric distribution can be approximated by the binomial distribution with parameters n and p = MIN. If p is small, n is large, and np <7, then the binomial distribution can be approximated by the Poisson distribution with u = np. MacBook Air
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