A random sample of n₁ = 16 communities in western Kansas gave the following ratesof hay fever per 1000 population for people under 25 years of age.121 115 124 99 134 121 110 116 113 96 116 116 135 96 96 116A random sample of n₂ = 14 communities in western Kansas gave the following ratesof hay fever per 1000 population for people over 50 years old.113 86 106 102 113 94 94 108 103 99 78 105 88 100Assume that the hay fever rate in each age group has an approximately normaldistribution. Using the method outlined in Brase and Brase, do the data indicate thatthe age group over 50 has a lower rate of hay fever? Use a = 0,05. Do you reject orfail to reject the null hypothesis? Are the data statistically significant at the α =0.05 level of significance? Since the p-value is greater than the level of significance, the data are notstatistically significant. Thus, we fail to reject the null hypothesis.Since the p-value is less than the level of significance, the data are notstatistically significant. Thus, we fail to reject the null hypothesis.Since the p-value is greater than the level of significance, the data arestatistically significant. Thus, we fail to reject the null hypothesis.Since the p-value is less than the level of significance, the data are statisticallysignificant. Thus, we reject the null hypothesis.Since the p-value is greater than the level of significance, the data are notstatistically significant. Thus, we reject the null hypothesis.

From the data given There is no difference in rate of Hay fever 0"…

Answered: er per population for people 25 years…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Recall the data for the three populations. p1 = 0.576 n1 = 250 p2 = 0.48 n2 = 300 p3 = 0.45 n3 = 200 Find the critical value for the pairwise difference between populations i = 1 and j = 3, CV13, rounding the result to four decimal places. CVij = ??2 pi(1 − pi) ni + pj(1 − pj) nj CV13 = ?20.05 p1(1 − p1) n1 + p3(1 − p3) n3 = 5.991 0.576(1 − 0.576) 250 + 0.45(1 − 0.45) = Find the critical value for the pairwise difference between populations i = 2 and j = 3, CV23, rounding the result to four decimal places. CVij = ??2 pi(1 − pi) ni + pj(1 − pj) nj CV23 = ?20.05 p2(1 − p2) n2 + p3(1 − p3) n3 = 5.991 0.48(1 − 0.48) 300 + 0.45(1 − 0.45) =
Bighorn sheep are beautiful wild animals found throughout the western United States. Let x be the age of a bighorn sheep (in years), and let y be the mortality rate (percent that die) for this age group. For example, x = 1, y = 14 means that 14% of the bighorn sheep between 1 and 2 years old died. A random sample of Arizona bighorn sheep gave the following information: x 1 2 3 4 5 y 13.2 19.3 14.4 19.6 20.0 Σx = 15; Σy = 86.5; Σx2 = 55; Σy2 = 1,538.25; Σxy = 273.4 (a) Find x, y, b, and the equation of the least-squares line. (Round your answers for x and y to two decimal places. Round your least-squares estimates to three decimal places.) x = y = b = ŷ = + x (b) Draw a scatter diagram for the data. Plot the least-squares line on your scatter diagram. (c) Find the sample correlation coefficient r and the coefficient of determination r2. (Round your answers to three decimal places.) r = r2 = What percentage of variation in y is explained by the…
Data consistent with summary quantities in the article "Effects of Fast-Food Consumption on Energy Intake and Diet Quality Among Children" on total calorie consumption on a particular day are given for a sample of children who did not eat fast food on that day and for a sample of children who did eat fast food on that day. Assume that it is reasonable to regard these samples as representative of the population of children in the United States. No Fast Food 2332 1919 1010 1731 1470 2054 2144 1982 1853 17781766 1828 1649 1507 2670 Fast Food 2517 1752 928 2322 2428 2261 2520 1189 884 1505 869 2201 1805 1244 2111 In USE SALT (a) Use the given information to estimate the mean calorie intake for children in the United States on a day when no fast food is consumed. (b) Use the given information to estimate the mean calorie intake for children in the United States on a day when fast food is consumed. (Round your answer to four decimal places.) (c) Use the given information to estimate the…
Archeologists have discovered a sample of ancient Egyptian skulls from two different time periods, 4000 B.C. and 150 A.D. They believe that the mean maximum skull breadth (the width of the skull at its widest part) has increased from 4000 B.C. to 150 A.D. A sample of 16 Egyptian skull breadths (in mm) from each time period is show below: 4000 BC 133 137 130 131 130 131 123 130 121 124 136 124 130 123 122 134 150 AD 139 141 141 136 137 131 139 128 133 141 134 140 131 141 128 140 (a) Calculate the mean and standard deviation for each data set. Round each mean to 2 decimal places, and each standard deviation to 4 decimal places. 4000 BC mean: 128.6876 x o 150 AD mean: 136.2500 4000 BC standard deviation: 5.1603 150 AD standard deviation: 4.7679 (b) Using your answers from part (a) and the formula for a 95% confidence interval as presented in lecture, fill in the blanks with the appropriate values for this problem for calculating the confidence interval below. • To enter Va where x is any…
How Much Older Are Husbands? Exercise 2.213 introduces a dataset giving the ages of the two people getting married for a sample of 105 marriage licenses. All of the couples in the sample were male-female couples. We see in Exercise 6.272 that the average age of husbands is greater than the average age of wives. Here, we wish to estimate how much older husbands are than their wives. Because this is paired data, we answer this question by first finding the difference in ages (Husband’s age minus Wife’s age) for each couple. For the 105 differences, the mean difference is 2.829 years with a standard deviation of 4.995. Find a 95% confidence interval for the mean difference in ages between a husband and a wife. Round to three decimal places.
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Evans conducted a study to determine if the frequency and characteristics of pediatric problems in elderly patients with diabetes present differences with respect to patients of the same age, but without diabetes. The individuals studied, interned in a clinic, were between 70 and 90 years old. Among the researchers' findings are the following statistics. with respect to the scores on the deep tendon reflexes meters:Sample without Diabetes: 79 / 2.1 / 1.1With Diabetes: 74 / 1.6 / 1.2Is it possible to conclude, based on the data, that, on average, diabetic patients they have reduced deep tendon reflexes in comparison with patients without diabetes of the same age?
Bighorn sheep are beautiful wild animals found throughout the western United States. Let x be the age of a bighorn sheep (in years), and let y be the mortality rate (percent that die) for this age group. For example, x = 1, y = 14 means that 14% of the bighorn sheep between 1 and 2 years old died. A random sample of Arizona bighorn sheep gave the following information: x 1 2 3 4 5 y 14.2 17.7 14.4 19.6 20.0 Σx = 15; Σy = 85.9; Σx2 = 55; Σy2 = 1,506.45; Σxy = 271.2 (a) Find x, y, b, and the equation of the least-squares line. (Round your answers for x and y to two decimal places. Round your least-squares estimates to three decimal places.) x = y = b = ŷ = + x (b) Draw a scatter diagram for the data. Plot the least-squares line on your scatter diagram. (c) Find the sample correlation coefficient r and the coefficient of determination r2. (Round your answers to three decimal places.) r = r2 = What percentage of variation in y is explained…
1. Consider the following information. SSTR = 6750 H0: μ1 = μ2 = μ3 = μ4 SSE = 8000 Ha: At least one mean is different If n = 5, the mean square due to error (MSE) equals?
The weight of a car can influence the mileage that the car can obtain. A random sample of 17 cars was taken and the weight (in pounds) and mileage (in mpg) were recorded and are in the table below. X, weight Y, mileage 4000 23.6 4000 23.4 2500 40.9 3500 28 2750 46.9 3000 32.2 3000 31.4 4500 17.2 2250 38.9 3500 31.3 3500 32.6 2750 36.3 5500 13.2 3000 31.4 3500 31.3 2250 53.3 3500 28 a) The symbol and value of the correlation coefficient are as follows: Round final answer to 2 decimal places. Select an answer r R² ρ ŷ y p̂ X̄ p μ σ s = Interpret this value: There is a strong Select an answer positive negative Select an answer linear quadratic bell-shaped uniform relation between weight and mileage for cars. b) The symbol and value of the coefficient of determination are as follows: Select an answer Fail to Reject the Null Accept the Null Reject the Null
Thomas wants to compare the mean concentration of carbon monoxide (CO) on residential versus commercial streets, since these differ in terms of car traffic. In each of three neighborhoods of Montréal (named A, B, and C below), he randomly chooses four locations for each type of street, for a total of 24 observations (2 street types x 3 neighborhoods x 4 locations). At each location, he measures CO concentration in the air over a period of 10 hours (8:00 AM-6:00 PM), and obtains the following data (in ppm/h). Question: Test whether or not the difference between residential and commercial streets in mean atmospheric CO concentration is the same among the three neighborhoods, and whether or not CO concentration in the air is the same, on average, for the two types of streets. Note that Neighborhood is considered a random block factor in the ANOVA. Use significant level= 0.05.
The article cited in Exercise 4 also investigated the effects of the factors on glucose consumption (in g/L). A single measurement is provided for each combination of factors (in the article, there was some replication). The results are presented in the following table. Glucose Consumption 68.0 -1 -1 -1 -1 -1 77.5 -1 -1 98.0 1. 1. -1 98.0 -1 -1 74.0 -1 77.0 -1 97.0 98.0 Compute estimates of the main effects and the interactions. a. Is it possible to compute an error sum of squares? Explain. Are any of the interactions among the larger effects? If so, which ones? d. Assume that it is known from past experience that the additive model holds. Add the sums of squares for the interactions, and use that result in place of an error sum of squares to test the hypotheses that the main effects are equal to 0. Ъ. C.

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