(a) Is the data collected categorical or quantitative? (b) How many groups of da
ID: 3309890 • Letter: #
Question
(a) Is the data collected categorical or quantitative?
(b) How many groups of data were collected?
(c) What type of test would you do? (Choose from: one proportion, two proportions, chi-square goodness of fit, chi-square test for independence, one mean, paired means, independent means, ANOVA for independent samples, ANOVA for blocked samples)
(d) Write the null and alternative hypotheses. (Do not perform the test)
Review question 10: Each person in a group of 300 college students was identified as male or female and then asked whether he or she preferred taking liberal arts courses in the area of math/science, social science or humanities. Is there a relationship between the gender of a college student and their preference of liberal arts courses?
Review question 11 : A random sample of 800 people shows that 96 of them had purchased hunting licenses. A random sample of a different 800 people showed that 120 of them had purchased fishing licenses. Does the data indicate that the proportion of people who hunt is less than the proportion who fish?
Review question 12 : A study comparing attitudes toward death was conducted in which organ donors (individuals who signed organ donor cards) were compared with non-donors. Templer's Death Anxiety Scale (DAS) was administered to both groups. Higher scores indicate high anxiety concerning death. There were 65 organ donors sampled with a mean DAS of 5.36. There were 68 non-donors sampled with a mean DAS of 7.62. Is there a significant difference in the mean DAS scores for the two groups?
Explanation / Answer
Solution:-
11)
State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.
Null hypothesis: PHunting> PFishes
Alternative hypothesis: PHunting < PFishes
Note that these hypotheses constitute a one-tailed test.
Formulate an analysis plan. For this analysis, the significance level is 0.05. The test method is a two-proportion z-test.
Analyze sample data. Using sample data, we calculate the pooled sample proportion (p) and the standard error (SE). Using those measures, we compute the z-score test statistic (z).
p = (p1 * n1 + p2 * n2) / (n1 + n2)
p = 0.135
SE = sqrt{ p * ( 1 - p ) * [ (1/n1) + (1/n2) ] }
SE = 0.0171
z = (p1 - p2) / SE
z = - 1.75
where p1 is the sample proportion in sample 1, where p2 is the sample proportion in sample 2, n1 is the size of sample 1, and n2 is the size of sample 2.
Since we have a one-tailed test, the P-value is the probability that the z-score is less than -1.75. We use the Normal Distribution Calculator to find P(z < - 1.75).
Thus, the P-value = 0.0401
Interpret results. Since the P-value (0.0401) is less than the significance level (0.05), we have to reject the null hypothesis.
From the above test we have sufficient evidence in the favor of the claim that the proportion of people who hunt is less than the proportion who fish.
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