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Do World War II Bomb Hits Fit a Poisson Distribution? In analyzing hits by V-1 buzz bombs in World War II, South London was subdivided into regions, each with an area of 0.25\(k{m^2}\). Shown below is a table of actual frequencies of hits and the frequencies expected with the Poisson distribution. (The Poisson distribution is described in Section 5-3.) Use the values listed and a 0.05 significance level to test the claim that the actual frequencies fit a Poisson distribution. Does the result prove that the data conform to the Poisson distribution?

Number of Bomb Hits

0

1

2

3

4

Actual Number of Regions

229

211

93

35

8

Expected Number of Regions

(from Poisson Distribution)

227.5

211.4

97.9

30.5

8.7

Short Answer

Expert verified

There is not enough evidence to conclude that theobserved frequencies of bomb hits do not fit well with the Poisson distribution.

Therefore, the given data conforms to the Poisson distribution.

Step by step solution

01

Given information

The observed and expected frequencies of bomb hits in different regions are provided.

02

Check the requirements

Let O denote the observed frequencies of hits.

The following values are obtained:

\(\begin{aligned}{l}{O_0} = 229\\{O_1} = 211\\{O_2} = 93\\{O_3} = 35\\{O_4} = 8\end{aligned}\)

Let E denote the expected frequencies.

The expected frequencies are noted below:

\(\begin{aligned}{l}{E_0} = 227.5\\{E_1} = 211.4\\{E_2} = 97.9\\{E_3} = 30.5\\{E_4} = 8.7\end{aligned}\)

It is observed that each of the frequencies is greater than 5.

Thus, the requirements for the test are satisfied, assuming the sampling is done randomly.

03

State the hypotheses

The hypotheses are,

\({H_0}:\)The observed frequencies of bomb hits fit well with the Poisson distribution.

\({H_a}:\)The observed frequencies of bomb hits do not fit well with the Poisson distribution.

The test is right-tailed.

The table below shows the necessary calculations:

Bomb Hits

O

E

\(\left( {O - E} \right)\)

\({\left( {O - E} \right)^2}\)

\(\frac{{{{\left( {O - E} \right)}^2}}}{E}\)

0

229

227.5

1.5

2.25

0.00989

1

211

211.4

-0.4

0.16

0.000757

2

93

97.9

-4.9

24.01

0.24525

3

35

30.5

4.5

20.25

0.66393

4

8

8.7

-0.7

0.49

0.05632

The value of the test statistic is equal to:

\(\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \;\\ = 0.00989 + 0.000757 + ...... + 0.056322\\ = 0.976\end{aligned}\)

Thus,\({\chi ^2} = 0.976\).

Let k be the different number of bomb hits, which is equal to 5.

The degrees of freedom for\({\chi ^2}\)is computed below:

\(\begin{aligned}{c}df = k - 1\\ = 5 - 1\\ = 4\end{aligned}\)

The critical value of\({\chi ^2}\)at\(\alpha = 0.05\)with 4 degrees of freedom is equal to 9.4877.

The p-value is equal to,

\(\begin{aligned}{c}p - value = P\left( {{\chi ^2} > 0.976} \right)\\ = 0.913\end{aligned}\)

Since the test statistic value is less than the critical value and the p-value is greater than 0.05, the null hypothesis is failed to be rejected.

04

State the conclusion

There is not enough evidence to conclude that theobserved frequencies of bomb hits do not fit well with the Poisson distribution.

Therefore, the given data conforms to the Poisson distribution.

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Most popular questions from this chapter

Motor Vehicle Fatalities The table below lists motor vehicle fatalities by day of the week for a recent year (based on data from the Insurance Institute for Highway Safety). Use a 0.01 significance level to test the claim that auto fatalities occur on the different days of the week with the same frequency. Provide an explanation for the results.

Day

Sun.

Mon.

Tues.

Wed.

Thurs.

Fri.

Sat.

Frequency

5304

4002

4082

4010

4268

5068

5985

Probability Refer to the results from the 150 subjects in Cumulative Review Exercise 5.

a.Find the probability that if 1 of the 150 subjects is randomly selected, the result is a woman who spent the money.

b.Find the probability that if 1 of the 150 subjects is randomly selected, the result is a woman who spent the money or was given a single 100-yuan bill.

c.If two different women are randomly selected, find the probability that they both spent the money.

The accompanying table is from a study conducted

with the stated objective of addressing cell phone safety by understanding why we use a particular ear for cell phone use. (See 鈥淗emispheric Dominance and Cell Phone Use,鈥 by Seidman, Siegel, Shah, and Bowyer, JAMA Otolaryngology鈥擧ead & Neck Surgery,Vol. 139, No. 5.)

The goal was to determine whether the ear choice is associated with auditory or language brain hemispheric dominance. Assume that we want to test the claim that handedness and cell phone ear preference are independent of each other.

a. Use the data in the table to find the expected value for the cell that has an observed frequency of 3. Round the result to three decimal places.

b. What does the expected value indicate about the requirements for the hypothesis test?

Right Ear

Left Ear

No Preference

Right-Handed

436

166

40

Left-Handed

16

50

3

Exercises 1鈥5 refer to the sample data in the following table, which summarizes the last digits of the heights (cm) of 300 randomly selected subjects (from Data Set 1 鈥淏ody Data鈥 in Appendix B). Assume that we want to use a 0.05 significance level to test the claim that the data are from a population having the property that the last digits are all equally likely.

Last Digit

0

1

2

3

4

5

6

7

8

9

Frequency

30

35

24

25

35

36

37

27

27

24

If using a 0.05 significance level to test the stated claim, find the number of degrees of freedom.

Cybersecurity The table below lists leading digits of 317 inter-arrival Internet traffic times for a computer, along with the frequencies of leading digits expected with 叠别苍蹿辞谤诲鈥檚 law (from Table 11-1 in the Chapter Problem).

a. Identify the notation used for observed and expected values.

b. Identify the observed and expected values for the leading digit of 2.

c. Use the results from part (b) to find the contribution to the\({\chi ^2}\)test statistic from the category representing the leading digit of 2.

Leading Digit

1

2

3

4

5

6

7

8

9

叠别苍蹿辞谤诲鈥檚

Law

30.1%

17.6%

12.5%

9.7%

7.9%

6.7%

5.8%

5.1%

4.6%

Leading Digits

of Inter-Arrival

Traffic Times

76

62

29

33

19

27

28

21

22

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