[ad_1]
1. For a multinomial experiment with k categories, the goodness-of-fit test statistic is assumed to follow a chi-square distribution with k degrees of freedom.
True False
2. If the null hypothesis is rejected by the goodness-of-fit test, the alternative hypothesis specifies which of the population proportions differ from their hypothesized values.
True False
3. For a chi-square goodness-of-fit test, the expected category frequencies are calculated using the sample category proportions.
True False
4. For a chi-square test of a contingency table, the expected frequencies for each cell are calculated assuming the null hypothesis is true.
True False
5. For a chi-square test of a contingency table, the degrees of freedom are calculated as (r – 1)(c – 1) where r and c are the number of rows and columns in the contingency table.
True False
6. For a chi-square test of a contingency table, each observation may be counted in multiple cells of the contingency table.
True False
7. The chi-square test statistic measures the difference between the observed frequencies and the expected frequencies assuming the null hypothesis is true.
True False
8. A goodness-of-fit test analyzes for two qualitative variables whereas a chi-square test of a contingency table is for a single qualitative variable.
True False
9. When applying the goodness-of-fit test for normality, the quantitative data must be converted into a qualitative format.
True False
10. For the Jarque-Bera test for normality, the test statistic is assumed to have a chi-square distribution with 2 degrees of freedom.
True False
11. For a multinomial experiment, which of the following is not true?
A. The number of categories is at least two,
B. The trials are dependent
C. The sum of the category probabilities is 1,
D. The category probabilities are the same for each trial
12. For the goodness-of-fit test, the expected category frequencies found are the:
A. sample proportions
B. hypothesized proportions
C. average of the hypothesized and sample proportions
D. proportions specified under the alternative hypothesis
lOMoARcPSD|3013804
13. Which of the following null hypotheses is used to test if five population proportions are the same?
A.
B.
C.
D.
14. For the goodness-of-fit test, the sum of the expected frequencies must equal:
A.
B. n
C. k
D. k – 1
15. For the goodness-of-fit test, the chi-square test statistic will:
A. always equal zero
B. always be negative
C. be at least zero
D. always be equal to n
16. The chi-square test of a contingency table is a test of independence for:
A. A single qualitative variable
B. Two qualitative variables
C. Two quantitative variables
D. Three or more quantitative variables
17. For the chi-square test of a contingency table, the expected cell frequencies are found as:
A. The row total multiplied by the column total divided by the sample size
B. The observed cell frequency
C. (r – 1) (c – 1)
D. (r)(c)
18. The chi-square test of a contingency table is valid when the expected cell frequencies are:
A. Equal to 0
B. More than 0 but less than 5
C. At least 5
D. Negative
19. For the chi-square test of a contingency table, the expected cell frequencies are found
as which is the same as:
A. The observed cell frequencies
B. The cell probability multiplied by the sample size
C. The row total
D. The column total
20. What are the degrees of freedom for the goodness-of-fit test for normality?
A. 2
B. k – 3
C. k – 2
D. k – 1
lOMoARcPSD|3013804
21. For the chi-square test for normality, the expected frequencies for each interval must be:
A. Exactly 2
B. k – 3
C. At least 5
D. k – 1
22. For the goodness-of-fit test for normality, the null and alternative hypotheses are:
A.
B.
C.
D.
23. For the goodness-of-fit test for normality to be applied, what is the minimum number of qualitative intervals the quantitative data can be converted to?
A. 2
B. 4
C. 5
D. 10
24. The calculation of the Jarque-Bera test statistic involves:
A. Only the sample size
B. The sample size, standard deviation, and average
C. The sample size, skewness coefficient, and the kurtosis coefficient
D. The sample average, skewness coefficient, and the kurtosis coefficient
25. For the Jarque-Bera test for normality, the null and alternative hypotheses are:
A.
B.
C.
D.
26. Packaged candies have three different types of colors, suppose you want to determine if the population proportion of each color is the same. The most appropriate test is the:
A. Goodness-of-fit test for a multinomial experiment
B. Chi-square test for independence
C. Goodness-of-fit test for normality
D. Jarque-Bera test for normality
27. Suppose you want to determine if gender and major are independent. Which test should you use?
A. Goodness-of-fit test for a multinomial experiment
B. Chi-square test for independence
C. Goodness-of-fit test for normality
D. Jarque-Bera test for normality
lOMoARcPSD|3013804
28. Suppose you want to determine if mutual funds quarterly returns have a normal distribution when your available data is partitioned into some non-overlapping intervals with given frequencies. The most appropriate test is the:
A. Goodness-of-fit test for a multinomial experiment
B. Chi-square test for independence
C. Goodness-of-fit test for normality
D. Jarque-Bera test for normality
29. Suppose you want to determine if mutual funds quarterly returns have a normal distribution using quantitative summary statistics. The most appropriate test is the:
A. Goodness-of-fit test for a multinomial experiment
B. Chi-square test for independence
C. Goodness-of-fit test for normality
D. Jarque-Bera test for normality
30. If a test statistic has a value of X and is assumed to be χ2 distributed with df degrees of freedom, then the p-value for a right-tailed test found by Excel is:
A. CHISQ.DIST.RT(X, df)
B. CHISQ.DIST.RT(df, X)
C. 1-CHISQ.DIST.RT(X, df)
D. 1-CHISQ.DIST.RT(df, X)
31. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. To test if the poker dealing machine deals cards at random, the null and alternative
hypotheses are:
A.
B.
C.
D.
lOMoARcPSD|3013804
32. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. For the goodness-of-fit test, the degrees of freedom are:
A. 2
B. 3
C. 4
D. 5
33. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. For the goodness-of-fit test, the value of the test statistic is:
A. 2.25
B. 3.125
C. 6.45
D. 7.815
34. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
lOMoARcPSD|3013804
35. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. Using the p-value approach and α = 0.05, the decision and conclusion are:
A. Do not reject the null hypothesis, all of the population proportions are the same
B. Reject the null hypothesis, conclude that not all proportions are equal to 0.20
C. Reject the null hypothesis, conclude that not all proportions are equal to 0.25
D. Do not reject the null hypothesis, cannot conclude that not all of the proportions are equal to 0.25
36. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. At the 5% significance level, the critical value is:
A. 6.251
B. 7.815
C. 9.348
D. 11.345
37. EXHIBIT 12-1 A card dealing machine deals spades (1), hearts (2), clubs (3), and diamonds (4) at random as if from an infinite deck. In a randomness check, 1,600 cards were dealt and counted. The results are shown below.
Refer to Exhibit 12.1. Using the critical value approach, the decision and conclusion are:
A. Do not reject the null hypothesis, cannot conclude that not all of the proportions are equal to 0.25
B. Do not reject the null hypothesis, all of the population proportions are the same
C. Reject the null hypothesis, conclude that not all proportions are equal to 0.25
D. Reject the null hypothesis, conclude that not all proportions are equal to 0.20
lOMoARcPSD|3013804
38. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. For the goodness-of-fit test, the assumed degrees of freedom are:
A. 2
B. 3
C. 4
D. 5
39. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. For the goodness-of-fit test, the alternative hypothesis states that A.
B.
C.
D.
lOMoARcPSD|3013804
40. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. What is the value of the goodness-of-fit test statistic?
A. 3.08
B. 15.09
C. 15.64
D. 16.75
41. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
lOMoARcPSD|3013804
42. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. Using the p-value approach and α = 0.01, the decision and conclusion are:
A. Do not reject the null hypothesis; all proportions are equal to
B. Do not reject the null hypothesis; cannot conclude that not all of the proportions are the same
C. Reject the null hypothesis; at least one of the proportions is different from its hypothesized value
D. Reject the null hypothesis; all of the proportions are not the same
43. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. At the 1% significance level, the critical value is:
A. 9.236
B. 11.070
C. 12.833
D. 15.086
lOMoARcPSD|3013804
44. EXHIBIT 12.2 A university has six colleges and takes a poll to gauge student support for a tuition increase. The university wants to insure each college is represented fairly. The below table shows the observed number students that participate in the poll from each college and the actual proportion of students in each college.
Refer to Exhibit 12.2. Using the critical value approach, the decision and conclusion are:
A. Reject the null hypothesis, at least one of the proportions is different from its hypothesized value
B. Reject the null hypothesis, all of the proportions are not the same
C. Do not reject the null hypothesis, all proportions are equal to 0.20
D. Do not reject the null hypothesis, cannot conclude not all of the proportions are the same
45. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. For the goodness-of-fit test, what are the degrees of freedom for the chi-squared test statistic?
A. 4
B. 5
C. 6
D. 7
lOMoARcPSD|3013804
46. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. For the goodness-of -fit test, the null and alternative hypotheses are:
A.
B.
C.
D.
47. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. What is the value of goodness-of-fit chi-square test statistic?
A. 0.605
B. 0.632
C. 1.62
D. 2.57
lOMoARcPSD|3013804
48. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
49. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. Using the p-value approach and α = 0.05, the decision and conclusion are:
A. Do not reject the null hypothesis, all of the proportions are the same
B. Do not reject the null hypothesis, cannot conclude that not all of the proportions are the same
C. Reject the null hypothesis, not all of the proportions are the same
D. Reject the null hypothesis, all of the proportions are not the same
50. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. At the 5% significance level, the critical value is:
A. 7.779
B. 9.488
C. 11.143
D. 13.277
lOMoARcPSD|3013804
51. EXHIBIT 12.3 A fund manager wants to know if it equally likely that the Dow Jones Industrial average will go up each day of the week. For each day of the week, the fund manager observes the following number of days when the Dow Jones Industrial average goes up.
Refer to Exhibit 12.3. Using the critical value approach, the decision and conclusion are:
A. Reject the null hypothesis, not all of the proportions are the same
B. Reject the null hypothesis, all of the proportions are not the same
C. Do not reject the null hypothesis, all of the proportions are the same
D. Do not reject the null hypothesis, cannot conclude not all of the proportions are the same
52. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. To test that gender and candidate preference are independent, the null and alternative hypothesis are:
A.
B.
C.
D.
53. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. For the chi-square test of independence, the assumed degrees of freedom are:
A. 1
B. 2
C. 3
D. 4
lOMoARcPSD|3013804
54. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. For the chi-square test of independence, the value of the test statistic is:
A. 2.34
B. 1.62
C. 3.25
D. 4
55. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
56. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. Using the p-value approach and α = 0.10, the decision and conclusion are:
A. Reject the null hypothesis, gender and candidate preference are dependent
B. Do not reject the null hypothesis, gender and candidate preference are independent
C. Reject the null hypothesis, gender and candidate preference are independent
D. Do not reject null hypothesis, gender and candidate preference are dependent
57. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. At the 10% significance level, the critical value is:
A. 6.635
B. 5.024
C. 3.841
D. 2.706
lOMoARcPSD|3013804
58. EXHIBIT 12. In the following table, likely voters’ preferences of two candidates are cross-classified by gender.
Refer to Exhibit 12.4. Using the critical value approach, the decision and conclusion are:
A. Reject the null hypothesis, gender and candidate preference are dependent
B. Do not reject the null hypothesis, gender and candidate preference are independent
C. Reject the null hypothesis, gender and candidate preference are independent
D. Do not reject the null hypothesis, gender and candidate preference are dependent
59. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. Which of the following is the estimated joint probability for the ‘low income and
21 -35 age group’ cell?
A. 0.0830
B. 0.0874
C. 0.0996
D. 0.1328
60. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. Which of the following is the expected joint probability for the ‘low income and
21 -35 age group’ cell assuming age group and income are independent?
A. 0.0830
B. 0.0874
C. 0.0996
D. 0.1328
61. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. Assuming age group and income are independent, the expected ‘low income and
21 -35 age group’ cell frequency is:
A. 105.27
B. 107.72
C. 146.31
D. 178.42
lOMoARcPSD|3013804
62. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. To test that age group and income are independent, the null and alternative
hypothesis are:
A.
B.
C.
D.
63. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. For the chi-square test of independence, the degrees of freedom are:
A. 2
B. 4
C. 9
D. 8
64. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. For the chi-square test of independence, the value of the test statistic is:
A. 8.779
B. 10.840
C. 13.243
D. 16.159
lOMoARcPSD|3013804
65. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
66. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. Using the p-value approach and α = 0.05, the decision and conclusion are:
A. Do not reject the null hypothesis, age and income are dependent
B. Do not reject the null hypothesis, age and income are independent
C. Reject the null hypothesis, age and income are dependent
D. Reject the null hypothesis, age and income are independent
67. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. At the 5% significance level, the critical value is:
A. 13.277
B. 11.143
C. 9.488
D. 7.779
68. EXHIBIT 12.5 In the following table, individuals are cross-classified by their age group and income level.
Refer to Exhibit 12.5. Using the critical value approach, the decision and conclusion are:
A. Do not reject the null hypothesis, age and income are dependent
B. Do not reject the null hypothesis, age and income are independent
C. Reject the null hypothesis, age and income are dependent
D. Reject the null hypothesis, age and income are independent
lOMoARcPSD|3013804
69. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. The row total for Asians is:
A. 86
B. 75
C. 62
D. 31
70. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. The column total for directors is:
A. 16
B. 56
C. 73
D. 109
71. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. Assuming that race and seniority are independent, what is the expected frequency of Asian directors?
A. 0
B. 1.95
C. 3.91
D. 5.42
lOMoARcPSD|3013804
72. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. To test that race and seniority are independent, the null and alternative hypothesis
are:
A.
B.
C.
D.
73. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. For the chi-square test for independence, the degrees of freedom used are:
A. 2
B. 16
C. 9
D. 0
74. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. For the chi-square test of independence, the value of the test statistic is:
A. 12.221
B. 15.378
C. 17.853
D. 20.154
lOMoARcPSD|3013804
75. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
76. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.5. Using the p-value approach and α = 0.05, the decision and conclusion are:
A. Reject the null hypothesis, conclude race and seniority are dependent
B. Reject the null hypothesis, conclude race and seniority are independent
C. Do not reject the null hypothesis, cannot conclude race and seniority are dependent
D. Do not reject the null hypothesis, conclude race and seniority are independent
77. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. At the 5% significance level, the critical value is:
A. 14.684
B. 16.919
C. 19.023
D. 21.666
lOMoARcPSD|3013804
78. EXHIBIT 12.6 The following table shows the distribution of employees in an Organization. Martha Foreman, an analyst wants to see if race has a bearing on the position a person holds with this company.
Refer to Exhibit 12.6. Using the critical value approach, the decision and conclusion are:
A. Reject the hypothesis, conclude race and seniority are dependent
B. Reject the null hypothesis, conclude race and seniority are independent
C. Do not reject the null hypothesis, conclude race and seniority are dependent
D. Do not reject the null hypothesis, conclude race and seniority are independent
79. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. For the chi-square test for normality, the null and alternative hypothesis are:
A.
B.
C.
D.
lOMoARcPSD|3013804
80. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. The heights are subdivided into five intervals. The degrees of freedom for the goodness-of-fit test for normality is:
A. 2
B. 3
C. 4
D. 5
81. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. For the heights subdivided into five intervals, the expected frequency of males that weigh less than 150 is:
A. 5.4
B. 12.6
C. 18.6
D. 8.4
lOMoARcPSD|3013804
82. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. For the goodness-of-fit test for normality, suppose the value of the test statistic is 7.71. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
83. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. Using the p-value approach and , the decision and conclusion are:
A. Reject the null hypothesis, conclude heights have a normal distribution
B. Reject the null hypothesis, conclude heights do not have a normal distribution
C. Do not reject the null hypothesis, conclude heights have a normal distribution
D. Do not reject the null hypothesis, conclude heights do not have a normal distribution
lOMoARcPSD|3013804
84. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. At the 5% significance level, the critical value is:
A. 4.605
B. 5.991
C. 7.378
D. 9.210
85. EXHIBIT 12.7 The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23. The following table shows the heights subdivided into non-overlapping intervals.
Refer to Exhibit 12.7. Suppose the value of the test statistic is 7.71. Using the critical value approach, decision and conclusion are:
A. Reject the null hypothesis, conclude heights have a normal distribution
B. Reject the null hypothesis, conclude heights do not have a normal distribution
C. Do not reject the null hypothesis, conclude heights have a normal distribution
D. Do not reject the null hypothesis, conclude heights do not have a normal distribution
86. EXHIBIT 12.8 The heights (in cm) for a random sample of 60 male employees of S&M Construction Company were measured. The sample mean is 166.5, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23.
Refer to Exhibit 12.8. The null and alternative hypotheses for the Jarque-Bera test for normality are:
A.
B.
C.
D.
lOMoARcPSD|3013804
87. EXHIBIT 12.8 The heights (in cm) for a random sample of 60 male employees of S&M Construction Company were measured. The sample mean is 166.5, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23.
Refer to Exhibit 12.8. The Jarque-Bera test statistic for normality is assumed to follow a χ2 distribution with the following degrees of freedom:
A. k – 1
B. 2
C. k – 1
D. (r – 1) (c – 1)
88. EXHIBIT 12.8 The heights (in cm) for a random sample of 60 male employees of S&M Construction Company were measured. The sample mean is 166.5, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23.
Refer to Exhibit 12.8. The value of the Jarque-Bera test statistic is:
A. 0.28
B. -0.493
C. 0.57
D. 2
89. EXHIBIT 12.8 The heights (in cm) for a random sample of 60 male employees of S&M Construction Company were measured. The sample mean is 166.5, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23.
Refer to Exhibit 12.8. The p-value is:
A. Less than 0.01
B. Between 0.01 and 0.05
C. Between 0.05 and 0.10
D. Greater than 0.10
90. EXHIBIT 12.8 The heights (in cm) for a random sample of 60 male employees of S&M Construction Company were measured. The sample mean is 166.5, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is -0.23.
Refer to Exhibit 12.8. Suppose the null hypothesis of normality is rejected. Which of the following is a valid conclusion?
A. The heights have a normal distribution
B. Not being able to determine the heights means it does not have a normal distribution
C. The heights do not have a normal distribution
D. Not being able to determine the heights means it has a normal distribution
91. A travel agent wants to determine if clients have a preference of four different airlines. For a sample of 200 flight reservations, there were 70, 45, 48, and 37 reservations for the four different airlines.
a. Set up the competing hypotheses to test if the population proportions are not equal to each other.
b. Calculate the value of the test statistic.
c. Specify the critical value at the 5% significance level.
d. What is the conclusion of the hypothesis test?
lOMoARcPSD|3013804
92. A researcher wants to determine if the distribution of races hired at government agencies is reflective of the overall U.S. population demographics. The researcher uses census data on demographics to obtain proportions for different races. The following table shows these proportions and the number of each race hired for a particular government agency.
a. Set up the competing hypotheses to test if at least one proportion is different from the population demographics.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Compute the p-value. Does the evidence suggest at least one proportion is different from the population demographics at the 1% significance level?
93. MARS claims that Skittles candies should be comprised of 30% purple, 10% orange, and 20% should be red, yellow, and green. Business students count a large bag of Skittles and find 265 red, 279 purple, 303 yellow, 271 green, and 212 orange candies.
a. Set up the competing hypotheses to test if at least one proportion is different than the value claimed by MARS.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Compute the p-value. Does the evidence suggest that at least one proportion is different from the claimed value at the 5% significance level?
lOMoARcPSD|3013804
94. A researcher wants to verify his belief that smoking and drinking go together. The following table shows individuals cross-classified by drinking and smoking habits.
a. Set up the competing hypotheses to determine if drinking and smoking are dependent.
b. Calculate the value of the test statistic.
c. Specify the critical value at the 5% significance level.
d. Can you conclude smoking and drinking are dependent?
95. The following table shows the cross-classification of hedge funds by market capitalization (either small, mid, or large cap) and objective (either growth or value).
a. Set up the competing hypotheses to determine if market capitalization and objective are dependent.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Compute the p-value. Does the evidence suggest market capitalization and objective are dependent at the 5% significance level?
96. The following table shows the cross-classification of accounting practices (either straight line, declining balance, or both) and country (either France, Germany, or UK).
a. Set up the competing hypotheses to determine if accounting practice and country are dependent.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Compute the p-value. Does the evidence suggest market capitalization and objective are dependent at the 1% significance level?
lOMoARcPSD|3013804
97. The following table shows the observed frequencies of the quarterly returns for a sample of 60 hedge funds. The table also contains the hypothesized proportions of each class assuming the quarterly returns have a normal distribution. The sample mean and standard deviation are 3.6% and 7.4% respectively.
a. Set up the competing hypotheses for the goodness-of-fit test of normality for the quarterly returns.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Compute the p-value. Does the evidence suggest that the quarterly returns do not have a normal distribution at the 10% significance level?
98. The following table shows the observed frequencies of the amount of assets under management for a sample of 134 hedge funds. The table also contains the hypothesized proportion of each class assuming the amount of assets under management has a normal distribution. The sample mean and standard deviation are 15 billion and 11 billion respectively.
a. Set up the competing hypotheses for the goodness-of-fit test of normality for amount of assets under management.
b. Calculate the value of the test statistic and determine the degrees of freedom.
c. Specify the critical value at the 5% significance level.
d. Is there evidence to suggest the amount of assets under management do not have a normal distribution?
e. Are there any conditions which may not be satisfied?
lOMoARcPSD|3013804
99. The following table shows numerical summaries of the best quarter returns (in percentages) for a sample of 121 hedge funds.
a. Set up the competing hypotheses for the Jarque-Bera test for normality for the best quarter returns.
b. Calculate the value of the test statistic.
c. Specify the critical value at the 1% significance level.
d. Does the evidence suggest that the best quarter returns do not have a normal distribution?
100.The following table shows numerical summaries of the worst quarter returns (in percentages) for a sample of 121 hedge funds.
a. Set up the competing hypotheses for the Jarque-Bera test for normality for the worst quarter returns.
b. Calculate the value of the test statistic and find the p-value.
c. Does the evidence suggest the worst quarter returns do not have a normal distribution at the 5% significance level?
The post For a chi-square goodness-of-fit test, the expected category frequencies are calculated using the sample category proportions. True False appeared first on Scholar Writers.
[ad_2]
Source link
"96% of our customers have reported a 90% and above score. You might want to place an order with us."
