Introductory Statistics (10th Edition)
10th Edition
ISBN: 9780321989178
Author: Neil A. Weiss
Publisher: PEARSON
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Chapter 16.3, Problem 52E
To determine
To test: Whether the data provide sufficient evidence to conclude that a difference exists in mean calibration constant among the four compound groups or not.
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Wild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below.
I
II
III
5.5
5.2
6.7
4.4
6.5
5.7
5.2
6.9
4.1
5.9
4.4
7.8
4.3
5.5
5.7
5.3
6.4
6.1
5.8
5.5
6.9
Shall we reject or not reject the claim that there are no differences among the population means of sepal length for the different species of iris? Use a 10% level of significance.
(a) What is the level of significance?
(b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Use 3 decimal places.)
SSTOT
=
?
SSBET
=
?
SSW
=
?
Find d.f.BET, d.f.W, MSBET, and…
Wild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below.
I
II
III
5.5
5.2
6.8
4.6
6.5
5.3
5.1
6.1
4.4
5.5
4.1
7.9
4.1
5.1
5.9
5.4
6.1
6.9
5.4
5.1
6.6
Shall we reject or not reject the claim that there are no differences among the population means of sepal length for the different species of iris? Use a 5% level of significance.
(a) What is the level of significance?State the null and alternate hypotheses.
Ho: ?1 = ?2 = ?3; H1: Exactly two means are equal.Ho: ?1 = ?2 = ?3; H1: Not all the means are equal. Ho: ?1 = ?2 = ?3; H1:…
Wild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below.
I
II
III
5.7
5.4
6.8
4.1
6.3
5.4
5.0
6.7
4.4
5.4
4.3
7.3
4.6
5.5
5.3
5.7
6.5
6.7
5.2
5.3
6.8
Shall we reject or not reject the claim that there are no differences among the population means of sepal length for the different species of iris? Use a 5% level of significance.
(a) What is the level of significance?State the null and alternate hypotheses.
Ho: ?1 = ?2 = ?3; H1: All three means are different.Ho: ?1 = ?2 = ?3; H1: Not all the means are equal. Ho: ?1 = ?2 = ?3;…
Chapter 16 Solutions
Introductory Statistics (10th Edition)
Ch. 16.1 - How do we identify an F-distribution and its...Ch. 16.1 - How many degrees of freedom does an F-curve have?...Ch. 16.1 - What symbol is used to denote the F-value having...Ch. 16.1 - Using the F-notation, identify the F-value having...Ch. 16.1 - An F-curve has df = (12, 7). What is the number of...Ch. 16.1 - An F-curve has df = (8, 19). What is the number of...Ch. 16.1 - In Exercises 16.716.10, use Table VIII in Appendix...Ch. 16.1 - Prob. 8ECh. 16.1 - Prob. 9ECh. 16.1 - Prob. 10E
Ch. 16.2 - One-way ANOVA is a procedure for comparing the...Ch. 16.2 - If we define s=MSE, of which parameter is s an...Ch. 16.2 - Explain the reason for the word variance in the...Ch. 16.2 - For a one-way ANOVA test, suppose that, in...Ch. 16.2 - Regarding one-way ANOVA, fill in the blanks in...Ch. 16.2 - Regarding one-way ANOVA, fill in the blanks in...Ch. 16.2 - Regarding one-way ANOVA, fill in the blanks in...Ch. 16.2 - Explain the logic behind one-way ANOVA.Ch. 16.2 - What does the term one-way signify in the phrase...Ch. 16.2 - Figure 16.6 shows side-by-side boxplots of...Ch. 16.2 - Figure 16.7 shows side-by-side boxplots of...Ch. 16.2 - Discuss two methods for checking the assumptions...Ch. 16.2 - In one-way ANOVA, what is the residual of an...Ch. 16.2 - In Exercises 16.24-16.29, we have provided data...Ch. 16.2 - In Exercises 16.24-16.29. we have provided data...Ch. 16.2 - In Exercises 16.24-16.29, we have provided data...Ch. 16.2 - In Exercises 16.24-16.29, we have provided data...Ch. 16.2 - In Exercises 16.24-16.29, we have provided data...Ch. 16.2 - In Exercises 16.24-16.29, we have provided data...Ch. 16.2 - Show that, for two populations, MSE=sp2, where is...Ch. 16.2 - Suppose that the variable under consideration is...Ch. 16.3 - Suppose that a one-way ANOVA is being performed to...Ch. 16.3 - We stated earlier that a one-way ANOVA test is...Ch. 16.3 - Following are the notations for the three sums of...Ch. 16.3 - State the one-way ANOVA identity, and interpret...Ch. 16.3 - True or false: If you know any two of the three...Ch. 16.3 - In each part, specify what type of analysis you...Ch. 16.3 - Prob. 38ECh. 16.3 - In Exercises 16.38-16.41, fill in the missing...Ch. 16.3 - In Exercises 16.38-16.41 fill in the missing...Ch. 16.3 - Prob. 41ECh. 16.3 - In Exercises 16.42-16.47. wt provide data from...Ch. 16.3 - In Exercises 16.42-16.47, we provide data from...Ch. 16.3 - Prob. 44ECh. 16.3 - Prob. 45ECh. 16.3 - Prob. 46ECh. 16.3 - Prob. 47ECh. 16.3 - Prob. 48ECh. 16.3 - Copepod Cuisine. Copepods are tiny crustaceans...Ch. 16.3 - In Exercises 16.48-16.53, apply Procedure 16.1 on...Ch. 16.3 - Staph Infections. In the article Using EDE, ANOVA...Ch. 16.3 - Prob. 52ECh. 16.3 - Prob. 53ECh. 16.3 - Prob. 54ECh. 16.3 - Prob. 55ECh. 16.3 - In Exercises 16.54-16.59, use the technology of...Ch. 16.3 - Prob. 57ECh. 16.3 - In Exercises 16.54-16.59, use. the technology of...Ch. 16.3 - Prob. 59ECh. 16.3 - Prob. 60ECh. 16.3 - Prob. 61ECh. 16.3 - In Exercises 16.60-16.63, refer to the discussion...Ch. 16.3 - Starting Salaries. The National Association of...Ch. 16.3 - Working with Large Data Sets In Exercises...Ch. 16.3 - Working with Large Data Sets In Exercises...Ch. 16.3 - In Exercises 16.64-16.72, use the technology of...Ch. 16.3 - In Exercises 16.6416.72, use the technology of...Ch. 16.3 - In Exercises 16.64-16.72, use the technology of...Ch. 16.3 - In Exercises 16.64-16.72, use the technology of...Ch. 16.3 - Prob. 70ECh. 16.3 - Prob. 71ECh. 16.3 - Prob. 72ECh. 16.3 - Prob. 73ECh. 16.3 - Prob. 74ECh. 16.3 - Prob. 75ECh. 16.4 - What is the purpose of doing a multiple...Ch. 16.4 - Fill in the blank: If a confidence interval for...Ch. 16.4 - Explain the difference between the family...Ch. 16.4 - Regarding family and individual confidence levels,...Ch. 16.4 - What is the name of the distribution on which the...Ch. 16.4 - The parameter v for the q-curve in a Tukey...Ch. 16.4 - Explain the essential difference between obtaining...Ch. 16.4 - Determine the following for a q-curve with...Ch. 16.4 - Determine the following for a q-curve with...Ch. 16.4 - Find the following for a q-curve with parameters K...Ch. 16.4 - Find the following for a q-curve with parameters K...Ch. 16.4 - Suppose that you conduct a one-way ANOVA test and...Ch. 16.4 - In Exercises 16.88-16.93, we repeal the data from...Ch. 16.4 - In Exercises 16.88-16.93, we repeat the data from...Ch. 16.4 - In Exercises 16.88-16.93, we repeat the data from...Ch. 16.4 - In Exercises 16.88-16.93, we repeat the data from...Ch. 16.4 - In Exercises 16.88-16.93, we repeat the data from...Ch. 16.4 - Prob. 93ECh. 16.4 - Prob. 94ECh. 16.4 - In Exercises 16.94-16.99, use Procedure 16.2 on...Ch. 16.4 - In Exercises 16.94-16.99, use Procedure 16.2 on...Ch. 16.4 - In Exercises 16.94-16.99, use Procedure 16.2 on...Ch. 16.4 - Prob. 98ECh. 16.4 - Prob. 99ECh. 16.4 - Prob. 100ECh. 16.4 - Prob. 101ECh. 16.4 - In Exercises 16.100-16.105, use the technology of...Ch. 16.4 - Prob. 103ECh. 16.4 - Prob. 104ECh. 16.4 - Prob. 105ECh. 16.4 - In Exercises 16.106-16.109, use Procedure 10.2 on...Ch. 16.4 - Prob. 107ECh. 16.4 - Prob. 108ECh. 16.4 - Prob. 109ECh. 16.4 - Prob. 110ECh. 16.4 - In Exercises 16.110-16.118, we repeat information...Ch. 16.4 - Prob. 112ECh. 16.4 - Prob. 113ECh. 16.4 - Prob. 114ECh. 16.4 - In Exercises 16.110-16.118, we repeat information...Ch. 16.4 - Prob. 116ECh. 16.4 - Prob. 117ECh. 16.4 - In Exercises 16.110-16.16.118, we repeat...Ch. 16.4 - Explain why the family confidence level, not the...Ch. 16.4 - Prob. 120ECh. 16.4 - Energy Consumption. Apply Table 16.11 on page 723...Ch. 16.5 - Prob. 122ECh. 16.5 - Prob. 123ECh. 16.5 - Prob. 124ECh. 16.5 - Prob. 125ECh. 16.5 - Prob. 126ECh. 16.5 - The measure of total variation of all the ranks is...Ch. 16.5 - Regarding a Kruskal-Wallis test, fill in the...Ch. 16.5 - Prob. 129ECh. 16.5 - Prob. 130ECh. 16.5 - In each of Exercises 16.130-16.133, suppose that...Ch. 16.5 - Prob. 132ECh. 16.5 - Prob. 133ECh. 16.5 - Prob. 134ECh. 16.5 - Prob. 135ECh. 16.5 - Prob. 136ECh. 16.5 - Prob. 137ECh. 16.5 - Prob. 138ECh. 16.5 - Prob. 139ECh. 16.5 - Prob. 140ECh. 16.5 - Prob. 141ECh. 16.5 - Prob. 142ECh. 16.5 - Prob. 143ECh. 16.5 - Prob. 144ECh. 16.5 - In Exercises 16.144-16.149, perform a...Ch. 16.5 - In Exercises 16.144-16.149, perform a...Ch. 16.5 - In Exercises 16.144-16.149, perform a...Ch. 16.5 - Prob. 148ECh. 16.5 - Prob. 149ECh. 16.5 - Prob. 150ECh. 16.5 - Prob. 151ECh. 16.5 - Prob. 152ECh. 16.5 - Prob. 153ECh. 16.5 - Prob. 154ECh. 16.5 - Prob. 155ECh. 16.5 - Prob. 156ECh. 16.5 - Prob. 157ECh. 16.5 - Prob. 158ECh. 16.5 - Prob. 159ECh. 16.5 - Prob. 160ECh. 16.5 - Prob. 161ECh. 16.5 - Prob. 162ECh. 16.5 - Prob. 163ECh. 16.5 - Prob. 164ECh. 16.5 - Prob. 165ECh. 16.5 - Prob. 166ECh. 16.5 - Prob. 167ECh. 16 - For what is one-way ANOVA used?Ch. 16 - State the four assumptions for one-way ANOVA, and...Ch. 16 - On what distribution does one-way ANOVA rely?Ch. 16 - Suppose that you want to compare the means of...Ch. 16 - Prob. 5RPCh. 16 - In one-way ANOVA, a. list and interpret the three...Ch. 16 - Prob. 7RPCh. 16 - Prob. 8RPCh. 16 - Prob. 9RPCh. 16 - Prob. 10RPCh. 16 - Prob. 11RPCh. 16 - Suppose that you want to compare the means of...Ch. 16 - Prob. 13RPCh. 16 - Prob. 14RPCh. 16 - Prob. 15RPCh. 16 - Prob. 16RPCh. 16 - In Problems 17-21, consider an F-curve with df =...Ch. 16 - Prob. 18RPCh. 16 - Prob. 19RPCh. 16 - Prob. 20RPCh. 16 - Prob. 21RPCh. 16 - Consider a q -curve with parameters 3 and 14. a....Ch. 16 - Consider the following hypothetical samples. A B C...Ch. 16 - Losses to Robbery. The Federal Bureau of...Ch. 16 - Prob. 25RPCh. 16 - Prob. 26RPCh. 16 - Prob. 27RPCh. 16 - Losses to Robbery. Refer to Problem 24. a. At the...Ch. 16 - Foot-pressure Angle. Genu valgum, commonly known...Ch. 16 - Prob. 30RPCh. 16 - Prob. 31RPCh. 16 - Prob. 32RPCh. 16 - In Problems 3234, use the technology of your...Ch. 16 - Prob. 34RPCh. 16 - Prob. 35RPCh. 16 - In Problems 3537, refer to the specified problem...Ch. 16 - Prob. 37RPCh. 16 - Recall from Chapter 1 (see page 34) that the Focus...Ch. 16 - SELF-PERCEPTION AND PHYSICAL ACTIVITY As you...
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- Wild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below. I II III 5.7 5.1 6.5 4.7 6.2 5.1 4.7 6.6 4.7 5.8 4.9 7.5 4.6 5.2 5.3 5.3 6.2 6.2 5.4 5.8 6.4 (b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Use 3 decimal places.) SSTOT = SSBET = SSW = Find d.f.BET, d.f.W, MSBET, and MSW. (Use 4 decimal places for MSBET, and MSW.) dfBET = dfW = MSBET = MSW = Find the value of the sample F statistic. (Use 2 decimal places.)What are the degrees of freedom? (numerator) (denominator)arrow_forwardWild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below. I II III 5.9 5.8 6.9 4.8 6.5 5.6 4.6 6.4 4.9 5.7 4.3 7.7 4.8 5.8 5.6 5.4 6.3 6.3 5.8 5.5 6.6 Shall we reject or not reject the claim that there are no differences among the population means of sepal length for the different species of iris? Use a 5% level of significance. (b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Use 3 decimal places.) SSTOT = SSBET = SSW = Find d.f.BET, d.f.W, MSBET, and MSW. (Use 4 decimal places for MSBET, and…arrow_forwardWild irises are beautiful flowers found throughout the United States, Canada, and northern Europe. This problem concerns the length of the sepal (leaf-like part covering the flower) of different species of wild iris. Data are based on information taken from an article by R. A. Fisher in Annals of Eugenics (Vol. 7, part 2, pp. 179 -188). Measurements of sepal length in centimeters from random samples of Iris setosa (I), Iris versicolor (II), and Iris virginica (III) are as follows below. I II III 5.6 5.5 6.9 4.5 6.6 5.5 5.4 6.5 4.3 5.4 4.6 7.9 4.7 5.6 5.8 5.9 6.6 6.3 5.6 5.6 6.9 Shall we reject or not reject the claim that there are no differences among the population means of sepal length for the different species of iris? (b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Use 3 decimal places.) SSTOT = SSBET = SSW = Find d.f.BET, d.f.W, MSBET, and MSW. (Use 4 decimal places for MSBET, and MSW.) dfBET = dfW =…arrow_forward
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