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Minimizing tractor skidding distance. Refer to the Journal of Forest Engineering (July 1999) study of minimizing tractor skidding distances along a new road in a European forest, Exercise 6.37 (p. 350). The skidding distances (in meters) were measured at 20 randomly selected road sites. The data are repeated below. Recall that a logger working on the road claims the mean skidding distance is at least 425 meters. Is there sufficient evidence to refute this claim? Use \(\alpha = .10\)

Short Answer

Expert verified

There is sufficient evidence to refute this claim.

Step by step solution

01

Given Information

The sample size is 20.

The hypothesis are given by

\(\begin{aligned}{H_0}:\mu = 425\\{H_a}:\mu > 425\end{aligned}\)

02

Compute and standard deviation

The mean is calculated as

\(\begin{aligned}\bar x &= \frac{{\sum\limits_{i = 1}^n {{X_i}} }}{n}\\ &= \frac{{7169}}{{20}}\\ &= 358.45\end{aligned}\)

The standard deviation is calculated as

\(\begin{aligned}sd &= \sqrt {\frac{{\sum\limits_{i = 1}^n {{{({X_i} - \bar X)}^2}} }}{{n - 1}}} \\ &= \sqrt {\frac{\begin{aligned}16783.2 + 71.4025 + 9712.103 + 25424.3 + 5394.903 + 2555.303 + \\5859.903 + 46461.8 + 6488.303 + 35175 + 704.9025 + 4025.903 + \\30432.8 + 9496.503 + 7301.703 + 1726.403 + 2251.503 + 2157.603 + \\47284.5 + 4428.903\end{aligned}}{{19}}} \\ &= \sqrt {\frac{{266292.3}}{{19}}} \\ &= \sqrt {14015.38} \\ &= 118.38\end{aligned}\)

Therefore, the mean and standard deviation are 358.45 and 118.38.

03

Test statistic

The test statistic is computed as

\(\begin{aligned}t &= \frac{{\bar x - \mu }}{{\frac{s}{{\sqrt n }}}}\\ &= \frac{{358.45 - 425}}{{\frac{{118.38}}{{\sqrt {20} }}}}\\ &= \frac{{ - 66.55}}{{26.47}}\\ &= - 2.514\end{aligned}\)

Therefore, the test statistic is-2.514.

04

Conclusion

For, \(\alpha = .10\,and\,n - 1 = 19\)

\(\begin{aligned}{t_{\alpha ,n - 1}} &= {t_{0.10,19}}\\ &= 1.327\end{aligned}\)

The calculated value is less than tabulated value.

Therefore, we reject the null hypothesis.

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Most popular questions from this chapter

Authorizing computer users with palm prints. Access to computers, email, and Facebook accounts is achieved via a passwordโ€”a collection of symbols (usually letters and numbers) selected by the user. One problem with passwords is that persistent hackers can create programs that enter millions of combinations of symbols into a target system until the correct password is found. An article in IEEE Pervasive Computing (October-December 2007) investigated the effectiveness of using palm prints to identify authorized users. For example, a system developed by Palmguard, Inc. tests the hypothesis

\({H_0}\): The proposed user is authorized

\({H_a}\): The proposed user is unauthorized

by checking characteristics of the proposed userโ€™s palm print against those stored in the authorized usersโ€™ data bank.

a. Define a Type I error and Type II error for this test. Which is the more serious error? Why?

a. List three factors that will increase the power of a test.

b. What is the relationship between b, the probability of committing a Type II error, and the power of a test?

If you test a hypothesis and reject the null hypothesis in favor of the alternative hypothesis, does your test prove that the alternative hypothesis is correct? Explain.

For each of the following situations, determine the p-value and make the appropriate conclusion.

a.\({H_0}:\mu \le 25\),\({H_a}:\mu > 25\),\(\alpha = 0.01\),\(z = 2.02\)

b.\({H_0}:\mu \ge 6\),\({H_a}:\mu < 6\),\(\alpha = 0.05\),\(z = - 1.78\)

c.\({H_0}:\mu = 110\),\({H_a}:\mu \ne 110\),\(\alpha = 0.1\),\(z = - 1.93\)

d. \({H_0}:\mu = 10\), \({H_a}:\mu \ne 10\), \(\alpha = 0.05\), \(z = 1.96\)

Managers who engage in โ€œcoopetition.โ€ In business, firms that both cooperate and compete with other firms are described as engaging in โ€œcoopetition.โ€ A study published in Industrial Marketing Management (February 2016) examined the level of external tension experienced by managers who engage in coopetition. External tension (measured on a 20-point scale) was recorded for each in a sample of 1,532 managers, all from firms that were engaged in coopetition. The sample mean tension was x=10.82 and the sample standard deviation was s=3.04.

Conduct a test (using a=.05) to determine if the true mean external tension level of all managers who engage in coopetition differs from 10.5 points.

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