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Problem 7.54: Fair Coin? P = 0.5 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 X Probability D istribution Plot Binomial,n=25,p=0.5 binomialcdf( 25, 0.5,7) 1 - binomia lcdf(25,0.5, 17) P(x < 7 or x > 18) = 0.043

Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

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Page 1: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Problem 7.54: Fair Coin? P = 0.5

252423222120191817161514131211109876543210

0.16

0.14

0.12

0.10

0.08

0.06

0.04

0.02

0.00

X

Pro

bability

Distribution PlotBinomial, n=25, p=0.5

binomialcd

f(25,0.5,7)

1 - binomialcdf(25,0.5,17)

P(x < 7 or x > 18) = 0.043

Page 2: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Problem 7.54: Fair Coin? P = 0.9

26252423222120191817161514131211109876543210

0.30

0.25

0.20

0.15

0.10

0.05

0.00

X

Pro

bability

Distribution PlotBinomial, n=25, p=0.9

binomialcdf(2

5,0.5,7)

1 - binomialcdf(25,0.5,17)

P(x < 7 or x > 18) = 0.998

Page 3: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

0.30

0.25

0.20

0.15

0.10

0.05

0.00

X

Pro

bability

Distribution PlotBinomial, n=25, p=0.1

Problem 7.54: Fair Coin? P = 0.1

binomialcdf(2

5,0.5,7)

1 - binomialcdf(25,0.5,17)

P(x < 7 or x > 18) = 0.998

Page 4: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

0.18

0.16

0.14

0.12

0.10

0.08

0.06

0.04

0.02

0.00

X

Pro

bability

Distribution PlotBinomial, n=25, p=0.6

Problem 7.54: Fair Coin? P = 0.6

binomialcdf(2

5,0.5,7) 1 - binomialcdf(25,0.5,17)

P(x < 7 or x > 18) = 0.155

Page 5: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

0.18

0.16

0.14

0.12

0.10

0.08

0.06

0.04

0.02

0.00

X

Pro

bability

Distribution PlotBinomial, n=25, p=0.4

Problem 7.54: Fair Coin? P = 0.4

binomialcdf(2

5,0.5,7)

1 - binomialcdf(25,0.5,17)

P(x < 7 or x > 18) = 0.155

Page 6: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Error: Type 1 or Type 11

• What do you think of our decision rule?– If not bias, wrong 4% of the time.– If bias at 60% or 40%, then we are wrong 85% of the

time.– If bias at 90% or 10%, then we are wrong less than

1% of the time.

– Moral of the story, you can’t have it both ways (can’t have your cake and eat it too) and often times we have to decide what we will accept and work with that.

Page 7: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Problem 7.56: Exit Polling

• A. 1 - binomialcdf(25, .9, 20) = 0.902• B. 1 - binomialcdf(25, .9, 20) = 0.902• C. μ = (25)(0.9) = 22.5, σ = =1.5• D. If fewer than 20 favor the ban (0.098), is this

at odds with the assertion that (at least) 90% of the populace favors the ban?

)9.1)(9)(.25(

Page 8: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

The Geometric Distribution

• Suppose that a sequence of trials we are interested in the number of the trials on which the first success occurs.

• Geometric distribution

,3,2,1)1();( 1 xforpppxg x

Page 9: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Mean and variance

• Mean of geometric distribution

• Variance of geometric distribution

p

1

22

1 p

p

Page 10: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Waiting for Reggie JacksonThe Geometric Distribution

Page 11: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Scenario

Children’s cereals sometimes contain small prizes. For example, not too long ago, boxes of Kellogg’s Frosted Flakes contained one of three posters: Ken Griffey, Jr., Nolan Ryan, or Reggie Jackson. A young boy wanted a Reggie Jackson poster and had to buy eight boxes until getting his poster.

Page 12: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Questions

Should this young boy consider himself especially unlucky?

On average, how many boxes would a person have to buy to get the Reggie Jackson poster?

What assumptions would you have to make to answer this question?

Page 13: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Objective

In this activity you will become familiar with the GEOMETRIC DISTRIBUTION, or WAIT TIME DISTRIBUTION, including the shape of the distribution and how to find its mean.

Page 14: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Activity

SIMULATION:

1 = Reggie Jackson

2 = Ken Griffey, Jr.

3 = Nolan Ryan

Count the number of times you enter until you get a “1”.

Repeat several times.

Using your calculator, simulate finding a poster by entering:

randInt(1,3) enter

Page 15: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Exercises

Make a histogram of the number of boxes everyone in the class requires to get their first Reggie Jackson Poster.

Describe its shape and distribution. What was the average number of “boxes”

purchased to get a Reggie Jackson poster?

Page 16: Problem 7.54: Fair Coin? P = 0.5 binomialcdf(25,0.5,7) 1 - binomialcdf(25,0.5,17) P(x 18) = 0.043

Exercises

Estimate the chance that the boy would have to buy eight or more boxes to get his poster.

What assumptions are made in the simulation about the distribution of the prizes?

Do you think the assumptions are reasonable ones?