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Chapter 9: Solution Manual for Introductory Biological Statistics, 3rd edition, Raymond E. Hampton and John E. Havel Lianfen Qian ® Chapter 9: Statistical Inference of One Population Mean 9-1: We are given n 30, x 70.2, s 10.51,1 .95. From Table A.2, we have t( 0.05, 29) 2.045 Thus the 95% confidence interval for the population mean (the mean pulse rate) is x t( , n 1) s 70.2 (2.045)(10.51/ 30 ) 70.2 (2.045)(1.9189) 70.2 3.924 (66.28,74.12). n 9-3: We are given n 9, x 19.256, s 0.855,1 .95 and 1 .99 From Table A.2, we have t(0.05,8) 2.306, t( 0.01,8) 3.355 Thus the 95% confidence interval for the population mea is x t( , n 1) s 19.256 (2.306)(2.564 / 9 ) 19.256 (2.306)(.855) 19.256 1.971 (17.28,21.23). n Thus the 99% confidence interval for the population mea is x t( , n 1) s 19.256 (3.355)(2.564 / 9 ) 19.256 (3.355)(.855) 19.256 2.867 (16.39,22.12). n 9-5: We are testing H0: μ=100 vs. Ha: μ100 grams We are given n 20, x 97, s 2.5 The computed t-test statistic is t x 100 97 100 3 5.37 s/ n 2.5 / 20 0.559 Conclusion: We are almost 100% confident to conclude that the mean weight is significantly different from 100 grams with a p-value=0.000. Hence they should be removed from the breeding program. 9-7: We are testing H0: μ≤3.5 vs. Ha: μ>3.5 mg per cigarette We are given n 10, x 4.2, s 1.4 The computed t-test statistic is t x 3.5 4.2 3.5 0.7 1.581 which is between 1.383 and 1.833 for df=9. The s / n 1.4 / 10 0.443 corresponding two-tailed probabilities are 0.2 and 0.1. Since we are testing one-tailed alternative hypothesis, so the one one-tail probability is between 0.1 and 0.05. That is, 0.05<p-value<0.1. Hence we fail to reject the null hypothesis at 0.05 significance level and conclude that there is not strong enough evidence to reject the manufacturer’s claim. 9-9: We are testing H0: μ≥50 vs. Ha: μ<50 grams We are given n 20, x 46.1, s 6.025 The computed t-test statistic is x 50 46.1 50 3.9 2.895 which is between -2.861 and -3.883 from the table s / n 6.025 / 20 1.347 (with a negative sign added) for left-tailed alternative hypothesis) with df=19. Thus, the p-value (the left tail probability) is between 0.0005 and 0.005 leading to conclude that there is strong enough evidence to reject the null hypothesis. That is, the enzyme activities are depressed in this population and hence there is significant indication of the presence of the pollutant. t 9-11. We are testing H0: μ≥8.0 vs. Ha: μ<8.0 ppm We are given n 20, x 7.94, s 0.204 The computed t-test statistic is x 8.0 7.94 8.0 0.06 1.3176 which is bigger than -1.328 from the table for lefts / n 0.204 / 20 0.0455 tailed alternative hypothesis ( a negative sign added) with df=19. Thus, the p-value (the left tail probability) is bigger than 0.2/2=0.1 leading to conclude that there is not enough evidence to reject the null hypothesis. That is, the average weight of the chicks is not below normal weight of 8.0 kg. t 9-13. We are testing H0: μd =0 vs. Ha: μd 0 We are given n 8, xd 35.625, s 23.6156 The computed t-test statistic is xd 0 35.625 35.625 4.267 which is between 3.499 and 5.408 from the table for s / n 23.6156 / 8 8.349 two-tailed alternative hypothesis with df=7. Thus, the p-value is between 0.001 and 0.01 leading to conclude that there is enough evidence to reject the null hypothesis. That is, the pre-exercise and post-exercise pulse rates are significantly different t 9-15. We are testing H0: μd ≥0 vs. Ha: μd <0 We are given n 12, xd 3, s 1.809 The computed t-test statistic is xd 0 3 3 5.745 which is between -5/921 and -4.437 from the table s / n 1.809 / 12 .522 (with negative sign added) for left-tailed alternative hypothesis with df=11. Thus, the p-value is between 0.00005 and 0.0005 leading to conclude that there is strong evidence to reject the null hypothesis. That is, Cortisone decrease long term memory significantly. t 9-17. We are testing H0: md ≤0 vs. Ha: md >0 T=1.5+1.5=3, and W=78. From A.5, n=12, c.v.=7 at α=0.005. Reject H0 at 0.005 significant level to conclude that the vaccine increase the encounter rate significantly. Minitab output shows that 9-19: We are given: n=8 (7(+),1(-)) Let Y=the number of subjects who reported an improvement. Then Y~Bin(8,.5) under null hypothesis of no change. P-value=P(Y≥7)=p(7)+p(8)=p(1)+p(0)=(1+8)(.5)8=0.0352. We conclude there is sufficient evidence of improvement with p-value=0.0352.