Alert nurses at the Veteran’s Affairs Medical Center in Northampton, Massachusetts, noticed an unusually high number of deaths at times when another nurse, Kristen Gilbert, was working. Those same nurses later noticed missing supplies of the drug epinephrine, which is a synthetic adrenaline that stimulates the heart. Kristen Gilbert was arrested and charged with four counts of murder and two counts of attempted murder. When seeking a grand jury indictment, prosecutors provided a key piece of evidence consisting of the table below. Use a 0.01 significance level to test the defense claim that deaths on shifts are independent of whether Gilbert was working. What does the result suggest about the guilt or innocence of Gilbert?

Shifts With a Death

Shifts Without a Death

Gilbert Was Working

40

217

Gilbert Was Not Working

34

1350

Short Answer

Expert verified

The deaths on shifts are dependent on whether Gilbert was working, which suggests the guilt of Gilbert.

Step by step solution

01

Given information

The data for theshifts with and without death and whether Gilbert was working is provided.

The level of significance is 0.01.

02

Compute the expected frequencies

Compute theexpected frequencies using the formula stated below,

\(E = \frac{{\left( {row\;total} \right)\left( {column\;total} \right)}}{{\left( {grand\;total} \right)}}\)

The counts for total rows and columns are,


Shifts With a Death

Shifts Without a Death

Row Total

Gilbert Was Working

40

217

257

Gilbert Was Not Working

34

1350

1384

Column Total

74

1567

1641

Theexpected frequency tableis represented as,


Shifts With a Death

Shifts Without a Death

Gilbert Was Working

11.5893

245.4107

Gilbert Was Not Working

62.4107

1321.5893

03

State the null and alternate hypothesis

The hypotheses are formulated as,

\({H_0}:\)The deaths on shifts are independent of whether Gilbert was working.

\({H_1}:\)The deaths on shifts are dependent on whether Gilbert was working.

04

Compute the test statistic

The value of the test statisticis computed as,

\(\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \\ = \frac{{{{\left( {40 - 11.5893} \right)}^2}}}{{11.5893}} + \frac{{{{\left( {217 - 245.4107} \right)}^2}}}{{245.4107}} + ... + \frac{{{{\left( {1350 - 1321.5893} \right)}^2}}}{{1321.5893}}\\ = 86.4809\\ \approx 86.481\end{aligned}\)

Therefore, the value of the test statistic is 86.481.

05

Compute the degrees of freedom

The degrees of freedomare computed as,

\(\begin{aligned}{c}\left( {r - 1} \right)\left( {c - 1} \right) = \left( {2 - 1} \right)\left( {2 - 1} \right)\\ = 1\end{aligned}\)

Therefore, the degrees of freedom are 1.

06

Compute the critical value

The critical value for 1 degrees of freedom and at 0.01 level of significance is 6.635.

Therefore, the critical value is 6.635.

The P-value is computed as 0.000.

07

State the decision

The critical (6.635) is less than the value of the test statistic (86.481). In this case, the null hypothesis is rejected.

Therefore, the decision is to reject the null hypothesis.

08

State the conclusion

There isinsufficient evidence to support the claimthat deaths on shifts are independent of whether Gilbert was working or not.

The results suggest that Gilbert cannot be considered as innocence for the deaths on the basis of results.

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Most popular questions from this chapter

A study of people who refused to answer survey questions provided the randomly selected sample data shown in the table below (based on data from “I Hear You Knocking But You Can’t Come In,” by Fitzgerald and Fuller, Sociological Methods and Research,Vol. 11, No. 1). At the 0.01 significance level, test the claim that the cooperation of

the subject (response or refusal) is independent of the age category. Does any particular age group appear to be particularly uncooperative?

Age


18-21

22-29

30-39

40-49

50-59

60 and over

Responded

73

255

245

136

138

202

Refused

11

20

33

16

27

49

Benford’s Law. According to Benford’s law, a variety of different data sets include numbers with leading (first) digits that follow the distribution shown in the table below. In Exercises 21–24, test for goodness-of-fit with the distribution described by Benford’s law.

Leading Digits

Benford's Law: Distributuon of leading digits

1

30.10%

2

17.60%

3

12.50%

4

9.70%

5

7.90%

6

6.70%

7

5.80%

8

5.10%

9

4.60%

Detecting Fraud When working for the Brooklyn district attorney, investigator Robert Burton analyzed the leading digits of the amounts from 784 checks issued by seven suspect companies. The frequencies were found to be 0, 15, 0, 76, 479, 183, 8, 23, and 0, and those digits correspond to the leading digits of 1, 2, 3, 4, 5, 6, 7, 8, and 9, respectively. If the observed frequencies are substantially different from the frequencies expected with Benford’s law, the check amounts appear to result from fraud. Use a 0.01 significance level to test for goodness-of-fit with Benford’s law. Does it appear that the checks are the result of fraud?

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

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

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

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