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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.

California Daily 4 Lottery The author recorded all digits selected in California’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.

Short Answer

Expert verified

There is enough evidence to conclude that the different digits in the lottery occur equally likely.

Step by step solution

01

Given information

The frequencies of digits that appear in the lottery are recorded for 60 days.

02

Check the requirements

As per the requirements of the chi-square test, the samples must be randomly selected, and the expected value must be larger than 5.

Let O denote the observed frequencies of the games.

The following values are obtained for the 10 digits:

\(\begin{aligned}{l}{O_0} = 21\\{O_1} = 30\\{O_2} = 31\\{O_3} = 33\\{O_4} = 19\end{aligned}\)

\(\begin{aligned}{l}{O_5} = 23\\{O_6} = 21\\{O_7} = 16\\{O_8} = 24\end{aligned}\)

\({O_9} = 22\)

The sum of all observed frequencies is computed below:

\(\begin{aligned}{c}n = 21 + 30 + ...... + 22\\ = 240\end{aligned}\)

Let E denote the expected frequencies.

It is given that the digits are expected to be selected in a way that they are equally likely.

The expected frequency for each of the 10 digits is the same and is equal to:

\(\begin{aligned}{c}E = \frac{{240}}{{10}}\\ = 24\end{aligned}\)

Assuming the samples are randomly taken, the requirements of the test are satisfied.

03

Conduct the hypothesis test

The table below shows the necessary calculations:

Digits

O

E

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

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

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

0

21

24

-3

9

0.375

1

30

24

6

36

1.5

2

31

24

7

49

2.04167

3

33

24

9

81

3.375

4

19

24

-5

25

1.0417

5

23

24

-1

1

0.0417

6

21

24

-3

9

0.375

7

16

24

-8

64

2.6667

8

24

24

0

0

0

9

22

24

-2

4

0.1667

The value of the test statistic is equal to:

\(\begin{aligned}{c}{\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \;\\ = 0.375 + 1.5 + ....... + 0.1667\\ = 11.583\end{aligned}\)

Thus,\({\chi ^2} = 11.583\).

Let k be the number of digits, which are 10.

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

\(\begin{aligned}{c}df = k - 1\\ = 10 - 1\\ = 9\end{aligned}\)

04

State the decision

The critical value of\({\chi ^2}\)at\(\alpha = 0.05\)with 9 degrees of freedom is obtained from chi-square table as 16.919.

The p-value is,

\(\begin{aligned}{c}p - value = P\left( {{\chi ^2} > 11.583} \right)\\ = 0.238\end{aligned}\)

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.

05

State the conclusion

There is enough evidence to favor the claim that the different digits in the lottery do occur equally likely.

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Most popular questions from this chapter

Is the hypothesis test described in Exercise 1 right tailed, left-tailed, or two-tailed? Explain your choice.

Using Yates’s Correction for Continuity The chi-square distribution is continuous, whereas the test statistic used in this section is discrete. Some statisticians use Yates’s correction for continuity in cells with an expected frequency of less than 10 or in all cells of a contingency table with two rows and two columns. With Yates’s correction, we replace

\(\sum \frac{{{{\left( {O - E} \right)}^2}}}{E}\)with \(\sum \frac{{{{\left( {\left| {O - E} \right| - 0.5} \right)}^2}}}{E}\)

Given the contingency table in Exercise 9 “Four Quarters the Same as $1?” find the value of the test \({\chi ^2}\)statistic using Yates’s correction in all cells. What effect does Yates’s correction have?

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 “Action Bias Among Elite Soccer Goalkeepers:

The Case of Penalty Kicks,” 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

Cybersecurity The accompanying Statdisk results shown in the margin are obtained from the data given in Exercise 1. What should be concluded when testing the claim that the leading digits have a distribution that fits well with Benford’s law?

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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