A random sample of n1 = 16 communities in western Kansas gave the following information for people under 25 years of age. x1: Rate of hay fever per 1000 population for people under 25 97 91 122 127 92 123 112 93 125 95 125 117 97 122 127 88 A random sample of n2 = 14 regions in western Kansas gave the following information for people over 50 years old. x2: Rate of hay fever per 1000 population for people over 50 94 108 100 95 111 88 110 79 115 100 89 114 85 96 (i) Use a calculator to calculate x1, s1, x2, and s2. (Round your answers to four decimal places.) x1 = s1 = x2 = s2 = (ii) Assume that the hay fever rate in each age group has an approximately normal distribution. Do the data indicate that the age group over 50 has a lower rate of hay fever? Use ? = 0.05. (a) What is the level of significance? State the null and alternate hypotheses. H0: ?1 = ?2; H1: ?1 > ?2 H0: ?1 = ?2; H1: ?1 < ?2 H0: ?1 > ?2; H1: ?1 = ?2 H0: ?1 = ?2; H1: ?1 ≠ ?2 (b) What sampling distribution will you use? What assumptions are you making? The standard normal. We assume that both population distributions are approximately normal with unknown standard deviations. The standard normal. We assume that both population distributions are approximately normal with known standard deviations. The Student's t. We assume that both population distributions are approximately normal with unknown standard deviations. The Student's t. We assume that both population distributions are approximately normal with known standard deviations. What is the value of the sample test statistic? (Test the difference ?1 − ?2. Round your answer to three decimal places.) (c) Find (or estimate) the P-value. P-value > 0.250 0.125 < P-value < 0.250 0.050 < P-value < 0.125 0.025 < P-value < 0.050 0.005 < P-value < 0.025 P-value < 0.005 (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level ?? At the ? = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant. At the ? = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant. At the ? = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant. At the ? = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant. (e) Interpret your conclusion in the context of the application. Fail to reject the null hypothesis, there is insufficient evidence that the mean rate of hay fever is lower for the age group over 50. Reject the null hypothesis, there is sufficient evidence that the mean rate of hay fever is lower for the age group over 50. Fail to reject the null hypothesis, there is sufficient evidence that the mean rate of hay fever is lower for the age group over 50. Reject the null hypothesis, there is insufficient evidence that the mean rate of hay fever is lower for the age group over 50.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
A random sample of n1 = 16 communities in western Kansas gave the following information for people under 25 years of age.
x1: Rate of hay fever per 1000 population for people under 25
97 | 91 | 122 | 127 | 92 | 123 | 112 | 93 |
125 | 95 | 125 | 117 | 97 | 122 | 127 | 88 |
A random sample of n2 = 14 regions in western Kansas gave the following information for people over 50 years old.
x2: Rate of hay fever per 1000 population for people over 50
94 | 108 | 100 | 95 | 111 | 88 | 110 |
79 | 115 | 100 | 89 | 114 | 85 | 96 |
(i) Use a calculator to calculate x1, s1, x2, and s2. (Round your answers to four decimal places.)
x1 | = |
s1 | = |
x2 | = |
s2 | = |
(ii) Assume that the hay fever rate in each age group has an approximately
(a) What is the level of significance?
State the null and alternate hypotheses.
(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level ??
(e) Interpret your conclusion in the context of the application.
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