In a clinical trial of the effectiveness of echinacea for preventing

colds, the results in the table below were obtained (based on data from “An Evaluation of Echinacea Angustifoliain Experimental Rhinovirus Infections,” by Turner et al., NewEngland Journal of Medicine,Vol. 353, No. 4). Use a 0.05 significance level to test the claim that getting a cold is independent of the treatment group. What do the results suggest about the

effectiveness of echinacea as a prevention against colds?

Treatment Group


Placebo

Echinacea:

20% Extract

Echinacea:

60% Extract

Got a Cold

88

48

42

Did Not Get a Cold

15

4

10

Short Answer

Expert verified

Getting a cold is independent of the treatment group. Thus, Echinacea is not effective to prevent colds.

Step by step solution

01

Given information

The data forthe effectiveness of Echinacea for preventing colds is provided.

The level of significance is 0.05.

02

Compute the expected frequencies

Assume that random selections are done for subjects, and each subject is assigned randomly to each group.

Theexpected frequency formulais computed as,

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

The row and column total for the observed frequencies is represented as,


Placebo

Echinacea:

20% Extract

Echinacea:

60% Extract

Row Total

Got a Cold

88

48

42

178

Did Not Get a Cold

15

4

10

29

Column Total

103

52

52

207

Theexpected frequency tableis represented as,


Placebo

Echinacea:

20% Extract

Echinacea:

60% Extract

Got a Cold

88.5700

44.7150

44.7150

Did Not Get a Cold

14.4300

7.2850

7.2850

Each expected value is greater than 5.

Thus, the requirements for the test are satisfied.

03

State the null and alternate hypothesis

The hypotheses are stated as:

\({H_0}:\)Getting a cold is independent of the treatment group.

\({H_1}:\)Getting a cold is dependent on the treatment group.

04

Compute the test statistic

The value of the test statistic is computed as,

\(\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \\ = \frac{{{{\left( {88 - 88.5700} \right)}^2}}}{{88.5700}} + \frac{{{{\left( {48 - 44.7150} \right)}^2}}}{{44.7150}} + ... + \frac{{{{\left( {10 - 7.2850} \right)}^2}}}{{7.2850}}\\ = 2.925\end{aligned}\)

Therefore, the value of the test statistic is 2.925.

05

Compute the degrees of freedom

The degrees of freedomare computed as,

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

Therefore, the degrees of freedom are 2.

06

Compute the critical value

From the chi-square table, the critical value for the row corresponding to 2 degrees of freedom and at 0.05 level of significance 5.991.

Therefore, the critical value is 5.991.

The P-value is obtained as 0.232.

07

State the decision

Since the critical value (5.991) is greater than the value of the test statistic (2.925). In this case, the null hypothesis fails to be rejected.

Therefore, the decision is that null hypothesis is failed to be rejected.

The P-value is obtained as 0.2316.

08

State the conclusion

There issufficient evidence to support the claimthat getting a cold is independent of the treatment group.

Thus, it can be said that Echinacea is not effective to prevent colds.

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Most popular questions from this chapter

Questions 6–10 refer to the sample data in the following table, which describes the fate of the passengers and crew aboard the Titanic when it sank on April 15, 1912. Assume that the data are a sample from a large population and we want to use a 0.05 significance level to test the claim that surviving is independent of whether the person is a man, woman, boy, or girl.


Men

Women

Boys

Girls

Survived

332

318

29

27

Died

1360

104

35

18

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

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

Kentucky Derby The table below lists the frequency of wins for different post positions through the 141st running of the Kentucky Derby horse race. A post position of 1 is closest to the inside rail, so the horse in that position has the shortest distance to run. (Because the number of horses varies from year to year, only the first 10 post positions are included.) Use a 0.05 significance level to test the claim that the likelihood of winning is the same for the different post positions. Based on the result, should bettors consider the post position of a horse racing in the Kentucky Derby?

Post Position

1

2

3

4

5

6

7

8

9

10

Wins

19

14

11

15

15

7

8

12

5

11

Forward Grip Reach and Ergonomics When designing cars and aircraft, we must consider the forward grip reach of women. Women have normally distributed forward grip reaches with a mean of 686 mm and a standard deviation of 34 mm (based on anthropometric survey data from Gordon, Churchill, et al.).

a. If a car dashboard is positioned so that it can be reached by 95% of women, what is the shortest forward grip reach that can access the dashboard?

b. If a car dashboard is positioned so that it can be reached by women with a grip reach greater than 650 mm, what percentage of women cannot reach the dashboard? Is that percentage too high?

c. Find the probability that 16 randomly selected women have forward grip reaches with a mean greater than 680 mm. Does this result have any effect on the design?

Exercises 1–5 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 “Body Data” 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

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?

In Exercises 1–4, use the following listed arrival delay times (minutes) for American Airline flights from New York to Los Angeles. Negative values correspond to flights that arrived early. Also shown are the SPSS results for analysis of variance. Assume that we plan to use a 0.05 significance level to test the claim that the different flights have the same mean arrival delay time.

Flight 1

-32

-25

-26

-6

5

-15

-17

-36

Flight 19

-5

-32

-13

-9

-19

49

-30

-23

Flight 21

-23

28

103

-19

-5

-46

13

-3

P-Value If we use a 0.05 significance level in analysis of variance with the sample data given in Exercise 1, what is the P-value? What should we conclude? If a passenger abhors late flight arrivals, can that passenger be helped by selecting one of the flights?

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