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Clinical Trial of Lipitor Lipitor is the trade name of the drug atorvastatin, which is used to reduce cholesterol in patients. (Until its patent expired in 2011, this was the largest-selling drug in the world, with annual sales of $13 billion.) Adverse reactions have been studied in clinical trials, and the table below summarizes results for infections in patients from different treatment groups (based on data from Parke-Davis). Use a 0.01 significance level to test the claim that getting an infection is independent of the treatment. Does the atorvastatin (Lipitor) treatment appear to have an effect on infections?


Placebo

Atorvastatin 10 mg

Atorvastatin 40 mg

Atorvastatin 80 mg

Infection

27

89

8

7

No Infection

243

774

71

87

Short Answer

Expert verified

There is not enough evidence to conclude thatgetting an infection is not independent of the treatment.

No, atorvastatin treatment does not have an effect on infection because getting infected does not depend on the type of treatment administered.

Step by step solution

01

Given information

A contingency table is constructed that shows that the number of patients that get/not get an infection when different treatments to reduce cholesterol are administered to them.

02

Hypotheses

The null hypothesis is as follows:

Getting an infection is independent of the treatment.

The alternative hypothesis is as follows:

Getting an infection is not independent of the treatment.

It is considered a right-tailed test.

If the test statistic value is greater than the critical value, then the null hypothesis is rejected, otherwise not.

03

Observed and expected frequencies

Observed Frequency:

The frequencies provided in the table are the observed frequencies. They are denoted by\(O\).

The following contingency table shows the observed frequency for each cell:


Placebo

Atorvastatin 10 mg

Atorvastatin 40 mg

Atorvastatin 80 mg

Infection

\({O_1}\)=27

\({O_2}\)=89

\({O_3}\)=8

\({O_4}\)=7

No Infection

\({O_5}\)=243

\({O_6}\)=774

\({O_7}\)=71

\({O_8}\)=87

Expected Frequency:

The formula for computing the expected frequency for each cell is shown below:

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

The row total for the first row is computed below:

\(\begin{aligned}{c}Row\;Tota{l_1} = 27 + 89 + 8 + 7\\ = 131\end{aligned}\)

The row total for the second row is computed below:

\(\begin{aligned}{c}Row\;Tota{l_2} = 243 + 774 + 71 + 87\\ = 1175\end{aligned}\)

The column total for the first column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_1} = 27 + 243\\ = 270\end{aligned}\)

The column total for the second column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_2} = 89 + 774\\ = 863\end{aligned}\)

The column total for the third column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_3} = 8 + 71\\ = 79\end{aligned}\)

The column total for the fourth column is computed below:

\(\begin{aligned}{c}Column\;Tota{l_4} = 7 + 87\\ = 94\end{aligned}\)

The grand total can be computed as follows:

\(\begin{aligned}{c}Grand\;Total = \left( {131 + 1175} \right)\\ = \left( {270 + 863 + 79 + 94} \right)\\ = 1306\end{aligned}\)

Thus, the following table shows the expected frequencies for each of the corresponding observed frequencies:


Placebo

Atorvastatin

10 mg

Atorvastatin

40 mg

Atorvastatin

80 mg

Infection

\[\begin{aligned}{c}{E_1} = \frac{{\left( {131} \right)\left( {270} \right)}}{{1306}}\\ = 27.083\end{aligned}\]

\[\begin{aligned}{c}{E_2} = \frac{{\left( {131} \right)\left( {863} \right)}}{{1306}}\\ = 86.564\end{aligned}\]

\[\begin{aligned}{c}{E_3} = \frac{{\left( {131} \right)\left( {79} \right)}}{{1306}}\\ = 7.924\end{aligned}\]

\[\begin{aligned}{c}{E_4} = \frac{{\left( {131} \right)\left( {94} \right)}}{{1306}}\\ = 9.429\end{aligned}\]

No Infection

\[\begin{aligned}{c}{E_5} = \frac{{\left( {1175} \right)\left( {270} \right)}}{{1306}}\\ = 242.917\end{aligned}\]

\[\begin{aligned}{c}{E_6} = \frac{{\left( {1175} \right)\left( {863} \right)}}{{1306}}\\ = 776.436\end{aligned}\]

\[\begin{aligned}{c}{E_7} = \frac{{\left( {1175} \right)\left( {79} \right)}}{{1306}}\\ = 71.076\end{aligned}\]

\[\begin{aligned}{c}{E_8} = \frac{{\left( {1175} \right)\left( {94} \right)}}{{1306}}\\ = 84.571\end{aligned}\]

04

Test Statistic

The test statistic is computed as shown below:

\[\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}\;\;\; \sim } {\chi ^2}_{\left( {r - 1} \right)\left( {c - 1} \right)}\\ = \frac{{{{\left( {27 - 27.083} \right)}^2}}}{{27.083}} + \frac{{{{\left( {89 - 86.564} \right)}^2}}}{{86.564}} + ..... + \frac{{{{\left( {87 - 84.571} \right)}^2}}}{{84.571}}\\ = 0.773\end{aligned}\]

Thus, \({\chi ^2} = 0.773\).

05

Obtain the critical value, p-value and determine the conclusion of the test

Let r denote the number of rows in the contingency table.

Let c denote the number of columns in the contingency table.

The degrees of freedom are computed below:

\(\begin{aligned}{c}df = \left( {r - 1} \right)\left( {c - 1} \right)\\ = \left( {2 - 1} \right)\left( {4 - 1} \right)\\ = 3\end{aligned}\)

The critical value of\({\chi ^2}\)for 3 degrees of freedom at 0.01 level of significance for a right-tailed test is equal to 11.3449.

The corresponding p-value is approximately equal to 0.855914.

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

There is not enough evidence to warrant rejection of the claim thatgetting an infection is independent of the treatment.

No, atorvastatin treatment does not have an effect on infection because getting infected does not depend on the type of treatment administered.

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Most popular questions from this chapter

In Exercises 5โ€“20, conduct the hypothesis test and provide the test statistic and the P-value and , or critical value, and state the conclusion.

California Daily 4 Lottery The author recorded all digits selected in Californiaโ€™s Daily 4 Lottery for the 60 days preceding the time that this exercise was created. The frequencies of the digits from 0 through 9 are 21, 30, 31, 33, 19, 23, 21, 16, 24, and 22. Use a 0.05 significance level to test the claim of lottery officials that the digits are selected in a way that they are equally likely.

Cybersecurity What do the results from the preceding exercises suggest about the possibility that the computer has been hacked? Is there any corrective action that should be taken?

Loaded Die The author drilled a hole in a die and filled it with a lead weight, then proceeded to roll it 200 times. Here are the observed frequencies for the outcomes of 1, 2, 3, 4, 5, and 6, respectively: 27, 31, 42, 40, 28, and 32. Use a 0.05 significance level to test the claim that the outcomes are not equally likely. Does it appear that the loaded die behaves differently than a fair die?

Exercises 1โ€“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 โ€œBody Dataโ€ 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

Is the hypothesis test left-tailed, right-tailed, or two-tailed?

In soccer, serious fouls in the penalty box result in a penalty kick withone kicker and one defending goalkeeper. The table below summarizes results from 286 kicksduring games among top teams (based on data from โ€œAction Bias Among Elite Soccer Goalkeepers:

The Case of Penalty Kicks,โ€ by Bar-Eli et al., Journal of Economic Psychology,Vol.28, No. 5). In the table, jump direction indicates which way the goalkeeper jumped, where thekick direction is from the perspective of the goalkeeper. Use a 0.05 significance level to test theclaim that the direction of the kick is independent of the direction of the goalkeeper jump. Dothe results support the theory that because the kicks are so fast, goalkeepers have no time toreact, so the directions of their jumps are independent of the directions of the kicks?

Goalkeeper Jump

Left

Center

Right

Kick to Left

54

1

37

Kick to Center

41

10

31

Kick to Right

46

7

59

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