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Final Exam_Yang Liu

# Final Exam_Yang Liu - Final Exam 1 Boxplot of consumption...

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Final Exam 1. Boxplot of consumption of sex1 (male) and sex2 (female) Comment on the distributions of these two groups meat consumption: We can also draw a histogram to see the distribution of the data: The distributions of each groups are approximately normal distributed regardless the outliers lie in zero consumption of meat which might because the volunteers who may be vegetarian. 2. Normal probability plots for each gender’s meat consumption: 1) Sex 1:

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2) Sex 2: 3) Comment: Because the outliers which might result from vegetarian volunteers, we regardless the outliers in this analysis. The consumption values appear normally distributed since the probability plots are quite linear. 3. Test the hypothesis: a. 1) The null and alternative hypotheses are H 0 : μ = 62lb (the mean consumption of meat per person for 2007 is not greater than which in 2002) H a : μ > 62lb (the mean consumption of meat per person for 2007 is greater than which in 2002) Where μ denote the mean consumption of meat per person, and the hypothesis test is right tailed because there is greater than sign (>). 2) We are to perform the hypothesis test at the 5% significance level, or =0.05. α 3) The test statistic, t= - / x μ0s n , we have μ0 =62, n=50, s=19.6076, and x = 59.5 Thus the value of the test statistic is t= - / x μ0s n = -0.89 and P= 0.814 4) Since the test is right tailed, so = . t0 05 with df=n-1= 49, so = . t0 05 = 1.677 5) Because P> , / t does not fall in the rejection region, so do not α reject H 0. The test results are not statistically significant at the 5% level. 6) At the 5% significance level, the data does not provide sufficient evidence to conclude that the mean consumption of meat per person for 2007 is greater than which in 2002. b. Minitab output:
c. Conclusion: In the contest of the problem, at the 5% significance level, the data does not provide sufficient evidence to conclude that the mean consumption of meat per person for 2007 is greater than which in 2002. The evidence against the null hypothesis is very weak. 4. P-value: To obtain P-value of a hypothesis test, we assume that the null hypothesis is true and compute the probability of observing a value of the test statistic as extreme as or more extreme than that observed. By extreme we mean “far from what we would expect to observe if the null hypothesis is true.” We use the letter

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Final Exam_Yang Liu - Final Exam 1 Boxplot of consumption...

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