TRUE OR FALSE
1. True or false: The hypotheses for the Wilcoxon signed rank test for the population median of the differences are the same as those for the corresponding sign test.
2. True or false: The sample size used in the Wilcoxon signed rank test always equals the number of data values in the sample.
3. True or false: In the Wilcoxon rank sum test, the two samples are temporarily combined, and the ranks of the combined data values are calculated. Then the ranks are summed separately for each sample.
FILL IN THE BLANK
4. A convenient graphic for assessing the symmetry of a data distribution is a ___________.
5. The cutoff sample size between using the small-sample case and the large-sample case for the Wilcoxon signed rank test is ___________.
6. The Kruskal-Wallis test is the nonparametric alternative to ___________ of ___________, which we learned in an earlier chapter.
SHORT ANSWER
7. In the Wilcoxon signed rank test for matched-pair data, which data values need to be omitted?
8. Is the Wilcoxon rank sum test used for dependent or independent samples? What about the Wilcoxon signed rank test?
9. State the conditions for performing the Kruskal-Wallis test.
CALCULATIONS AND INTERPRETATIONS
childhealth
10. Children Without Health Insurance. The following table contains the number of children (in thousands) who are not covered by health insurance for a random sample of 24 states. Use the sign test to test whether the population median number of children per state without health insurance is greater than 75,000, using level of significance α=0.05.
State | Children without health insurance (1000s) |
State | Children without health insurance (1000s) |
---|---|---|---|
Idaho | 52 | Wisconsin | 63 |
Georgia | 314 | Massachusetts | 103 |
Oklahoma | 114 | Illinois | 302 |
Delaware | 24 | California | 1225 |
Minnesota | 104 | New Mexico | 93 |
Louisiana | 170 | Missouri | 127 |
Alabama | 82 | New York | 380 |
Florida | 771 | Ohio | 157 |
Colorado | 176 | Arkansas | 65 |
Washington | 105 | Connecticut | 49 |
Pennsylvania | 203 | Texas | 1392 |
Tennessee | 94 | Indiana | 123 |
carbon3
11. Carbon Emissions. The following table shows the carbon dioxide emissions (in millions of metric tons) from the consumption of fossil fuels in 2000 and 2005 for a random sample of 10 nations. Test whether the emissions have been increasing. That is, test, using a sign test, whether the population median of the difference (2005 – 2000) in carbon dioxide emissions is greater than zero, using level of significance α=0.05.
Nation | Carbon emissions in 2000 (millions of metric tons) |
Carbon emissions in 2005 (millions of metric tons) |
---|---|---|
Brazil | 342.1 | 360.6 |
Canada | 558.4 | 631.3 |
China | 2912.6 | 5322.7 |
France | 399.0 | 415.3 |
India | 994.1 | 1165.7 |
Ireland | 40.4 | 44.1 |
South Africa | 383.4 | 423.8 |
Thailand | 160.6 | 234.2 |
Vietnam | 47.4 | 80.4 |
United States | 5823.5 | 5957.0 |
militaryvets
12. Military Veterans. The following table contains the number of U.S. military veterans (in thousands) for a random sample of 13 states.
State | Veterans (1000s) |
---|---|
Montana | 104 |
Vermont | 55 |
Alaska | 75 |
New Hampshire | 132 |
Kansas | 237 |
Nevada | 246 |
Arkansas | 262 |
South Dakota | 74 |
West Virginia | 178 |
Maine | 144 |
Delaware | 81 |
North Dakota | 58 |
Mississippi | 216 |
13. Trade Balance. Table 20 contains the trade balance (in millions of dollars) that the United States has with a random sample of 12 European countries and a random sample of 11 Asian countries. Positive numbers indicate that our exports to that country exceed in value our imports from that country. Negative numbers indicate that exports are less than imports. Test whether the population median trade balance with European countries differs from the population median trade balance with Asian countries, using level of significance α=0.05.
European country |
Trade balance ($ millions) |
Asian country |
Trade balance ($ millions) |
---|---|---|---|
Austria | −7,497 | Bangladesh | −2,976 |
Belgium | 10,009 | China | −256,207 |
Czech Republic | −1,168 | Japan | −82,760 |
Germany | −44,513 | South Korea | −12,918 |
Greece | 918 | Israel | −7,775 |
Ireland | −21,436 | Malaysia | −20,948 |
United Kingdom | −6,629 | Nepal | −61 |
Netherlands | 14,560 | Thailand | −14,300 |
Norway | −4,256 | Taiwan | −11,968 |
France | −14,140 | Saudi Arabia | −25,230 |
Luxembourg | 475 | Cambodia | −2,325 |
Finland | −2,133 |