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Using the Runs Test for Randomness. In Exercises 5鈥10, use the runs test with a significance level of\(\alpha \)= 0.05. (All data are listed in order by row.) Law Enforcement Fatalities Listed below are numbers of law enforcement fatalities for 20 recent and consecutive years. First find the mean, identify each value as being above the mean (A) or below the mean (B), then test for randomness above and below the mean. Is there a trend?

183

140

172

171

144

162

241

159

150

165

163

156

192

148

125

161

171

126

107

117

Short Answer

Expert verified

The mean of the number of law enforcement fatalities is equal to 157.65.

There is not enough evidence to conclude that the number of law enforcement fatalities is not random.

Thus, it can be said that the sample does not follow a trend.

Step by step solution

01

Given information

Data are given on the number of law enforcement fatalities for 20 years.

02

Calculate the mean

The mean value of the data is computed as follows:

\(\begin{array}{c}Mean = \frac{{183 + 140 + ..... + 117}}{{20}}\\ = 157.65\end{array}\)

Therefore, the mean value is equal to 157.65.

03

Data transformation

Represent values that are greater than the mean as A.

Represent values that are less than the mean as B.

The table below shows the transformed data

Values

Symbol

183

A

140

B

172

A

171

A

144

B

162

A

241

A

159

A

150

B

165

A

163

A

156

B

192

A

148

B

125

B

161

A

171

A

126

B

107

B

117

B

The null hypothesis is as follows:

The given data is random.

The alternative hypothesis is as follows:

The given data is not random.

If the value of the number of runs is less than or equal to the smaller critical value or greater than or equal to the larger critical value, the null hypothesis is rejected.

04

Step 4:Calculate the test statistic and determine the results

The sequence is as follows:

A

B

A

A

B

A

A

A

B

A

A

B

A

B

B

A

A

B

B

B

Now, the number of times A occurs is denoted by\({n_1}\), and the number of times B occurs is denoted by\({n_2}\).

Thus,

\(\begin{array}{l}{n_1} = 11\\{n_2} = 9\end{array}\)

The runs of the sequence are formed as follows:

\(\;\underbrace A_{{1^{st}}run}\underbrace B_{{2^{nd}}run}\underbrace {AA}_{{3^{rd}}run}\underbrace B_{{4^{th}}run}\underbrace {AAA}_{{5^{th}}run}\underbrace B_{{6^{th}}run}\underbrace {AA}_{{7^{th}}run}\underbrace B_{{8^{th}}run}\underbrace A_{{9^{th}}run}\underbrace {BB}_{{{10}^{th}}run}\underbrace {AA}_{{{11}^{th}}run}\underbrace {BBB}_{{{12}^{th}}run}\)

The number of runs denoted by G is equal to 12.

Here,\({n_1} \le 20\)and\({n_2} \le 20\).

Thus, the test statistic is G, and the level of significance\(\left( \alpha \right)\)is equal to 0.05.

The critical values of G for\({n_1} = 10\)and\({n_2} = 10\)are 6 and 16, respectively.

The value of Gequal to 12 is neither less than or equal to 6 nor greater than or equal to 16. Thus, the decision if fail to reject the null hypothesis.

There is not enough evidence to conclude that the given sample is not random.

Since the sample israndom, it can be said that it does not follow any particular trend.

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