Radon exposure in Egyptian tombs. Refer to the Radiation Protection Dosimetry (December 2010) study of radon exposure in Egyptian tombs, Exercise 6.30 (p. 349). The radon levels—measured in becquerels per cubic meter (\({{Bq} \mathord{\left/ {\vphantom {{Bq} {{m^3}}}} \right. \\} {{m^3}}}\) )—in the inner chambers of a sample of 12 tombs are listed in the table shown below. For the safety of the guards and visitors, the Egypt Tourism Authority (ETA) will temporarily close the tombs if the true mean level of radon exposure in the tombs rises to 6,000\({{Bq} \mathord{\left/ {\vphantom {{Bq} {{m^3}}}} \right. \\} {{m^3}}}\) . Consequently, the ETA wants to conduct a test to determine if the true mean level of radon exposure in the tombs is less than 6,000\({{Bq} \mathord{\left/ {\vphantom {{Bq} {{m^3}}}} \right. \\} {{m^3}}}\) , using a Type I error probability of .10. An SPSS analysis of the data is shown at the bottom of the page. Specify all the elements of the test: \({H_0}\,,{H_a}\) test statistic, p-value,\(\alpha \) , and your conclusion.

50 910 180 580 7800 4000 390 12100 3400 1300 11900 110

Short Answer

Expert verified

The null and alternative hypothesis are given by

\(\begin{aligned}{l}{H_0}:\mu = 6000\\{H_a}:\mu < 6000\end{aligned}\)

Test statistic is -1.766.

We reject the null hypothesis.

Step by step solution

01

Stating the hypothesis

The null and alternative hypothesis are given by

\(\begin{aligned}{l}{H_0}:\mu = 6000\\{H_a}:\mu < 6000\end{aligned}\)

02

Computing mean and standard deviation

The sample size is 12

The mean is given by

\(\begin{aligned}\bar x &= \frac{{50 + 910 + 180 + 580 + 7800 + 4000 + 390 + 12100 + 3400 + 1300 + 11900 + 110}}{{12}}\\ &= \frac{{42720}}{{12}}\\ &= 3560\end{aligned}\)

The standard deviation is given by

\(\begin{aligned}sd &= \sqrt {\frac{\begin{aligned}{l}{\left( { - 3510} \right)^2} + {\left( { - 2650} \right)^2} + {\left( { - 3380} \right)^2} + {\left( { - 2980} \right)^2} + {\left( {4240} \right)^2}{\left( { - 3170} \right)^2}\\ + {\left( {8540} \right)^2} + {\left( { - 160} \right)^2} + {\left( { - 2260} \right)^2} + {\left( {8340} \right)^2} + {\left( { - 3510} \right)^2} + {\left( { - 3450} \right)^2}\end{aligned}}{{11}}} \\ &= \sqrt {\frac{\begin{aligned}{l}12320100 + 7022500 + 11424400 + 8880400 + 17977600 + 10048900 + \\72931600 + 25600 + 5107600 + 69555600 + 12320100 + 11902500\end{aligned}}{{11}}} \\ &= \sqrt {\frac{{251837000}}{{11}}} \\ &= \sqrt {22894272.73} \\ &= 4784.79\end{aligned}\)

The mean and standard deviation are 3560 and 4784.79.

03

Test statistic

The test statistic is computed as

\(\begin{aligned}t &= \frac{{\bar x - \mu }}{{\frac{s}{{\sqrt n }}}}\\ &= \frac{{3560 - 6000}}{{\frac{{4784.79}}{{\sqrt {12} }}}}\\ &= \frac{{ - 2440}}{{1381.24}}\\ &= - 1.766\end{aligned}\)

Therefore, the test statistic is -1.766.

04

P-value

The Type-1 error probability is given.

Hence,\(\alpha = .10\)

Degrees of freedom are

\(\begin{aligned}df &= n - 1\\ &= 12 - 1\\ &= 11\end{aligned}\)

The tabulated value is -1.363

05

Conclusion

The calculated value is less than the tabulated value.

Therefore, we reject the null hypothesis.

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Most popular questions from this chapter

For each of the following rejection regions, sketch the sampling distribution for z and indicate the location of the rejection region.

a. \({H_0}:\mu \le {\mu _0}\) and \({H_a}:\mu > {\mu _0};\alpha = 0.1\)

b. \({H_0}:\mu \le {\mu _0}\) and \({H_a}:\mu > {\mu _0};\alpha = 0.05\)

c. \({H_0}:\mu \ge {\mu _0}\) and \({H_a}:\mu < {\mu _0};\alpha = 0.01\)

d. \({H_0}:\mu = {\mu _0}\) and \({H_a}:\mu \ne {\mu _0};\alpha = 0.05\)

e. \({H_0}:\mu = {\mu _0}\) and \({H_a}:\mu \ne {\mu _0};\alpha = 0.1\)

f. \({H_0}:\mu = {\mu _0}\) and \({H_a}:\mu \ne {\mu _0};\alpha = 0.01\)

g. For each rejection region specified in parts a–f, state the probability notation in z and its respective Type I error value.

A random sample of 175 measurements possessed a mean x¯=8.2 and a standard deviation s = .79.

a. Test H0:μ=8.3 against Ha:μ8.3Use a=0.05

Consider the test \({H_0}:\mu = 70\) versus \({H_a}:\mu \ne 70\) using a large sample of size n = 400. Assume\(\sigma = 20\).

a. Describe the sampling distribution of\(\bar x\).

b. Find the value of the test statistic if\(\bar x = 72.5\).

c. Refer to part b. Find the p-value of the test.

d. Find the rejection region of the test for\(\alpha = 0.01\).

e. Refer to parts c and d. Use the p-value approach to

make the appropriate conclusion.

f. Repeat part e, but use the rejection region approach.

g. Do the conclusions, parts e and f, agree?

: A random sample of n = 200 observations from a binomial population yield

p^=0.29

a. Test H0:p=0.35 against H0:p<0.35. Usea=0.05.

Hotels’ use of ecolabels. Refer to the Journal of Vacation Marketing (January 2016) study of travelers’ familiarity with ecolabels used by hotels, Exercise 2.64 (p. 104). Recall that adult travelers were shown a list of 6 different ecolabels, and asked, “Suppose the response is measured on a continuous scale from 10 (not familiar at all) to 50 (very familiar).” The mean and standard deviation for the Energy Star ecolabel are 44 and 1.5, respectively. Assume the distribution of the responses is approximately normally distributed.

a. Find the probability that a response to Energy Star exceeds 43.

b. Find the probability that a response to Energy Star falls between 42 and 45. c. If you observe a response of 35 to an ecolabel, do you think it is likely that the ecolabel was Energy Star? Explain.

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