Critical Thinking: Was Allstate wrong? The Allstate insurance company once issued a press release listing zodiac signs along with the corresponding numbers of automobile crashes, as shown in the first and last columns in the table below. In the original press release, Allstate included comments such as one stating that Virgos are worried and shy, and they were involved in 211,650 accidents, making them the worst offenders. Allstate quickly issued an apology and retraction. In a press release, Allstate included this: “Astrological signs have absolutely no role in how we base coverage and set rates. Rating by astrology would not be actuarially sound.”

Analyzing the Results The original Allstate press release did not include the lengths (days) of the different zodiac signs. The preceding table lists those lengths in the third column. A reasonable explanation for the different numbers of crashes is that they should be proportional to the lengths of the zodiac signs. For example, people are born under the Capricorn sign on 29 days out of the 365 days in the year, so they are expected to have 29/365 of the total number of crashes. Use the methods of this chapter to determine whether this appears to explain the results in the table. Write a brief report of your findings.

Zodiac sign

Dates

Length(days)

Crashes

Capricorn

Jan.18-Feb. 15

29

128,005

Aquarius

Feb.16-March 11

24

106,878

Pisces

March 12-April 16

36

172,030

Aries

April 17-May 13

27

112,402

Taurus

May 14-June 19

37

177,503

Gemini

June 20-July 20

31

136,904

Cancer

July21-Aug.9

20

101,539

Leo

Aug.10-Sep.15

37

179,657

Virgo

Sep.16-Oct.30

45

211,650

Libra

Oct.31-Nov 22

23

110,592

Scorpio

Nov. 23-Nov. 28

6

26,833

Ophiuchus

Nov.29-Dec.17

19

83,234

Sagittarius

Dec.18-Jan.17

31

154,477

Short Answer

Expert verified

There is enough evidence to conclude that the number of crashes is not proportional to the lengths of the zodiac signs.

Step by step solution

01

Given information

The number of automobile crashes is given for the corresponding lengths of the zodiac signs.

02

Hypotheses

The null hypothesis of this test is as follows:

The number of crashes is proportional to the lengths of the zodiac signs.

The alternative hypothesis is as follows:

The number of crashes is not proportional to the lengths of the zodiac signs.

03

Calculations

Let\({O_i}\)denote the observed frequencies of the crashes.

The sums of all the observed frequencies is computed below:

\(\begin{aligned}{c}n = 128005 + 106878 + .... + 154477\\ = 1701704\end{aligned}\)

Let E denote the expected frequencies.

The expected frequencies are computed as shown:

\(E = \frac{{{\rm{Length}}\;{\rm{of the}}\;{\rm{zodiac}}\;{\rm{sign}}}}{{{\rm{Total}}\;{\rm{number}}\;{\rm{of}}\;{\rm{days}}\;{\rm{in}}\;{\rm{a}}\;{\rm{year}}}} \times {\rm{Total}}\;{\rm{crashes}}\)

Therefore, the expected frequencies are computed below:

\(\begin{aligned}{c}{E_1} = \frac{{29}}{{365}} \times 1701704\\ = 135203.87\end{aligned}\)

\(\begin{aligned}{c}{E_2} = \frac{{24}}{{365}} \times 1701704\\ = 111892.87\end{aligned}\)

\(\begin{aligned}{c}{E_3} = \frac{{36}}{{365}} \times 1701704\\ = 167839.30\end{aligned}\)

\(\begin{aligned}{c}{E_4} = \frac{{27}}{{365}} \times 1701704\\ = 125879.47\end{aligned}\)

\(\begin{aligned}{c}{E_5} = \frac{{37}}{{365}} \times 1701704\\ = 172501.50\end{aligned}\)

\(\begin{aligned}{c}{E_6} = \frac{{31}}{{365}} \times 1701704\\ = 144528.28\end{aligned}\)

\(\begin{aligned}{c}{E_7} = \frac{{20}}{{365}} \times 1701704\\ = 93244.05\end{aligned}\)

\(\begin{aligned}{c}{E_8} = \frac{{37}}{{365}} \times 1701704\\ = 172501.50\end{aligned}\)

\(\begin{aligned}{c}{E_9} = \frac{{45}}{{365}} \times 1701704\\ = 209799.12\end{aligned}\)

\(\begin{aligned}{c}{E_{10}} = \frac{{23}}{{365}} \times 1701704\\ = 107230.66\end{aligned}\)

\(\begin{aligned}{c}{E_{11}} = \frac{6}{{365}} \times 1701704\\ = 27973.22\end{aligned}\)

\(\begin{aligned}{c}{E_{12}} = \frac{{19}}{{365}} \times 1701704\\ = 88581.85\end{aligned}\)

\(\begin{aligned}{c}{E_{13}} = \frac{{31}}{{365}} \times 1701704\\ = 144528.28\end{aligned}\)

The table below shows the necessary calculations:

Zodiac sign

\({O_i}\)

\({E_i}\)

\(\frac{{{{\left( {{O_i} - {E_i}} \right)}^2}}}{{{E_i}}}\)

Capricorn

128,005

135203.87

383.3006

Aquarius

106,878

111892.87

224.7589

Pisces

172,030

167839.30

104.6356

Aries

112,402

125879.47

1442.985

Taurus

177,503

172501.50

145.0132

Gemini

136,904

144528.28

402.2026

Cancer

101,539

93244.05

737.9151

Leo

179,657

172501.50

296.8159

Virgo

211,650

209799.12

16.3288

Libra

110,592

107230.66

105.3673

Scorpio

26,833

27973.22

46.4767

Ophiuchus

83,234

88581.85

322.8596

Sagittarius

154,477

144528.28

684.8281

\(\sum {\frac{{{{\left( {{O_i} - {E_i}} \right)}^2}}}{E}} = 4913.487\)

04

Test statistic

The value of the test statistic is equal to:

\(\begin{aligned}{c}{\chi ^2} = \sum {\frac{{\left( {O - {E^2}} \right)}}{E}} \;\;\;\;\; \sim {\chi ^2}_{\left( {k - 1} \right)}\\ = 4913.487\end{aligned}\)

Thus,\({\chi ^2} = 4913.487\).

Let k be the number of observations.

Here, k=13.

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

\(\begin{aligned}{c}df = k - 1\\ = 13 - 1\\ = 12\end{aligned}\)

The critical value of\({\chi ^2}\)at\(\alpha = 0.05\)with 12 degrees of freedom is equal to 21.0261.

Since the test statistic value is greater than the critical value, the null hypothesis is rejected.

05

Conclusion

There is enough evidence to conclude that the number of crashes is not proportional to the lengths of the zodiac signs.

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Most popular questions from this chapter

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 Benford’s 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

Benford’s

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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Last Digit

0

1

2

3

4

5

6

7

8

9

Frequency

30

35

24

25

35

36

37

27

27

24

Given that the P-value for the hypothesis test is 0.501, what do you conclude? Does it appear that the heights were obtained through measurement or that the subjects reported their heights?

American Idol Contestants on the TV show American Idol competed to win a singing contest. At one point, the website WhatNotToSing.com listed the actual numbers of eliminations for different orders of singing, and the expected number of eliminations was also listed. The results are in the table below. Use a 0.05 significance level to test the claim that the actual eliminations agree with the expected numbers. Does there appear to be support for the claim that the leadoff singers appear to be at a disadvantage?

Singing Order

1

2

3

4

5

6

7–12

Actual Eliminations

20

12

9

8

6

5

9

Expected Eliminations

12.9

12.9

9.9

7.9

6.4

5.5

13.5

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Was the Challenge to the Call Successful?


Yes

No

Men

161

376

Women

68

152

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