Description
N=20 P=.82
A. P(X=19)
B. P(X=18)
C. P(X>18)
FOR PART C THE GREATER THAN SIGN HAS A LINE UNDERNEATH=
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Explanation & Answer
Please note that we have:
P (x = 19) = 20* 0.82^19* 0.18 = 0.101
P( x = 18) = 190*0.82^18 * 0.18^2 =0.173
and:
P(x > 18) = 12.3 %
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Exercise 261. Plot the frequency distribution for “Age at Enrollment” by hand or by using SPSS. 2. How would you characterize the skewness of the distribution in Question 1—positively skewed, negatively skewed, or approximately normal? Provide a rationale for your answer. 3. Compare the original skewness statistic and Shapiro-Wilk statistic with those of the smaller dataset ( n = 15) for the variable “Age at First Arrest.” How did the statistics change, and how would you explain these differences? 4. Plot the frequency distribution for “Years of Education” by hand or by using SPSS. 5. How would you characterize the kurtosis of the distribution in Question 4—leptokurtic, mesokur-tic, or platykurtic? Provide a rationale for your answer. 6. What is the skewness statistic for “Age at Enrollment”? How would you characterize the magnitude of the skewness statistic for “Age at Enrollment”? 7. What is the kurtosis statistic for “Years of Education”? How would you characterize the magnitude of the kurtosis statistic for “Years of Education”? 8. Using SPSS, compute the Shapiro-Wilk statistic for “Number of Times Fired from Job.” What would you conclude from the results? 9. In the SPSS output table titled “Tests of Normality,” the Shapiro-Wilk statistic is reported along with the Kolmogorov-Smirnov statistic. Why is the Kolmogorov-Smirnov statistic inappropriate to report for these example data? 10. How would you explain the skewness statistic for a particular frequency distribution being low and the Shapiro-Wilk statistic still being significant at p < 0.05?
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10.1.2Table
#10.1.6 contains the value of the house and the amount of rental income
in a year that the house brings in ...
statistics ques
10.1.2Table
#10.1.6 contains the value of the house and the amount of rental income
in a year that the house brings in ("Capital and rental," 2013). Create
a scatter plot and find a regression equation between house value and
rental income. Then use the regression equation to find the rental
income a house worth $230,000 and for a house worth $400,000. Which
rental income that you calculated do you think is closer to the true
rental income? Why?Table #10.1.6: Data of House Value versus Rental Value Rental Value Rental Value Rental Value Rental 81000 6656 77000 4576 75000 7280 67500 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9568 140000 9152 135000 7488 165000 13312 165000 8528 155000 7488 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 200000 12272 200000 10608 194000 11232 190000 8320 214000 8528 208000 10400 200000 10400 200000 8320 240000 10192 240000 12064 240000 11648 225000 12480 289000 11648 270000 12896 262000 10192 244500 11232 325000 12480 310000 12480 303000 12272 300000 12480 10.1.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information are available
for the year 2011 is in table #10.1.8. Create a scatter plot of the data
and find a regression equation between percentage spent on health
expenditure and the percentage of woman receiving prenatal care. Then
use the regression equation to find the percent of woman receiving
prenatal care for a country that spends 5.0% of GDP on health
expenditure and for a country that spends 12.0% of GDP. Which prenatal
care percentage that you calculated do you think is closer to the true
percentage? Why? Table #10.1.8: Data of Heath Expenditure versus Prenatal Care HealthExpenditure(% of GDP) PrenatalCare (%) 9.6 47.9 3.7 54.6 5.2 93.7 5.2 84.7 10.0 100.0 4.7 42.5 4.8 96.4 6.0 77.1 5.4 58.3 4.8 95.4 4.1 78.0 6.0 93.3 9.5 93.3 6.8 93.7 6.1 89.8 For
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are any outliers that need to be removed. Do the correlation analysis
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removal affects the correlation. The data sets in this section are in
section 10.1.10.2.2Table
#10.1.6 (from problem 10.1.2) contains the value of the house and the
amount of rental income in a year that the house brings in ("Capital and
rental," 2013). Find the correlation coefficient and coefficient of
determination and then interpret both.10.2.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information is available
for the year 2011 are in table #10.1.8 (from problem 10.1.4). Find the
correlation coefficient and coefficient of determination and then
interpret both.For each problem, state the random
variables. The data sets in this section are in the homework for section
10.1 and were also used in section 10.2. If you removed any data points
as outliers in the other sections, remove them in this sections
homework too.10.3.2Table
#10.1.6 (from problem 10.1.2) contains the value of the house and the
amount of rental income in a year that the house brings in ("Capital and
rental," 2013).a.) Test at the 5% level for a positive correlation between house value and rental amount.b.) Find the standard error of the estimate.c.) Compute a 95% prediction interval for the rental income on a house worth $230,000.10.3.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information is available
for the year 2011 are in table #10.1.8 (from problem 10.1.4).a.)
Test at the 5% level for a correlation between percentage spent on
health expenditure and the percentage of woman receiving prenatal care.b.) Find the standard error of the estimate.c.)
Compute a 95% prediction interval for the percentage of woman receiving
prenatal care for a country that spends 5.0 % of GDP on health
expenditure.In each problem show all steps of the
hypothesis test. If some of the assumptions are not met, note that the
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watched groups of dolphins off the coast of Ireland in 1998 to
determine what activities the dolphins partake in at certain times of
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represent the number of groups of dolphins that were partaking in an
activity at certain times of days. Is there enough evidence to show that
the activity and the time period are independent for dolphins? Test at
the 1% level. Table #11.1.6: Dolphin Activity Activity Period RowTotal Morning Noon Afternoon Evening Travel 6 6 14 13 39 Feed 28 4 0 56 88 Social 38 5 9 10 62 ColumnTotal 72 15 23 79 189 11.1.4A
person’s educational attainment and age group was collected by the U.S.
Census Bureau in 1984 to see if age group and educational attainment
are related. The counts in thousands are in table #11.1.8 ("Education by
age," 2013). Do the data show that educational attainment and age are
independent? Test at the 5% level.Table #11.1.8: Educational Attainment and Age Group Education Age Group RowTotal 25-34 35-44 45-54 55-64 >64 Did not completeHS 5416 5030 5777 7606 13746 37575 CompletedHS 16431 1855 9435 8795 7558 44074 College 1-3year 8555 5576 3124 2524 2503 22282 College 4 or more years 9771 7596 3904 3109 2483 26863 ColumnTotal 40173 20057 22240 22034 26290 130794 In
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assumptions are not met, note that the results of the test may not be
correct and then continue the process of the hypothesis test.11.2.4In
Africa in 2011, the number of deaths of a female from cardiovascular
disease for different age groups are in table #11.2.6 ("Global health
observatory," 2013). In addition, the proportion of deaths of females
from all causes for the same age groups are also in table #11.2.6. Do
the data show that the death from cardiovascular disease are in the same
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MIS 301 Academy College Independent Samples Assuming Unequal Variances Worksheet
1. T-test: 2 Independent Samples Assuming Unequal Variances2. T-Test: 2 Dependent Samples (Paired)Test
MIS 301 Academy College Independent Samples Assuming Unequal Variances Worksheet
1. T-test: 2 Independent Samples Assuming Unequal Variances2. T-Test: 2 Dependent Samples (Paired)Test
Exercise 26
Exercise 261. Plot the frequency distribution for “Age at Enrollment” by hand or by using SPSS. 2. How would you cha ...
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Exercise 261. Plot the frequency distribution for “Age at Enrollment” by hand or by using SPSS. 2. How would you characterize the skewness of the distribution in Question 1—positively skewed, negatively skewed, or approximately normal? Provide a rationale for your answer. 3. Compare the original skewness statistic and Shapiro-Wilk statistic with those of the smaller dataset ( n = 15) for the variable “Age at First Arrest.” How did the statistics change, and how would you explain these differences? 4. Plot the frequency distribution for “Years of Education” by hand or by using SPSS. 5. How would you characterize the kurtosis of the distribution in Question 4—leptokurtic, mesokur-tic, or platykurtic? Provide a rationale for your answer. 6. What is the skewness statistic for “Age at Enrollment”? How would you characterize the magnitude of the skewness statistic for “Age at Enrollment”? 7. What is the kurtosis statistic for “Years of Education”? How would you characterize the magnitude of the kurtosis statistic for “Years of Education”? 8. Using SPSS, compute the Shapiro-Wilk statistic for “Number of Times Fired from Job.” What would you conclude from the results? 9. In the SPSS output table titled “Tests of Normality,” the Shapiro-Wilk statistic is reported along with the Kolmogorov-Smirnov statistic. Why is the Kolmogorov-Smirnov statistic inappropriate to report for these example data? 10. How would you explain the skewness statistic for a particular frequency distribution being low and the Shapiro-Wilk statistic still being significant at p < 0.05?
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10.1.2Table
#10.1.6 contains the value of the house and the amount of rental income
in a year that the house brings in ...
statistics ques
10.1.2Table
#10.1.6 contains the value of the house and the amount of rental income
in a year that the house brings in ("Capital and rental," 2013). Create
a scatter plot and find a regression equation between house value and
rental income. Then use the regression equation to find the rental
income a house worth $230,000 and for a house worth $400,000. Which
rental income that you calculated do you think is closer to the true
rental income? Why?Table #10.1.6: Data of House Value versus Rental Value Rental Value Rental Value Rental Value Rental 81000 6656 77000 4576 75000 7280 67500 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9568 140000 9152 135000 7488 165000 13312 165000 8528 155000 7488 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 200000 12272 200000 10608 194000 11232 190000 8320 214000 8528 208000 10400 200000 10400 200000 8320 240000 10192 240000 12064 240000 11648 225000 12480 289000 11648 270000 12896 262000 10192 244500 11232 325000 12480 310000 12480 303000 12272 300000 12480 10.1.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information are available
for the year 2011 is in table #10.1.8. Create a scatter plot of the data
and find a regression equation between percentage spent on health
expenditure and the percentage of woman receiving prenatal care. Then
use the regression equation to find the percent of woman receiving
prenatal care for a country that spends 5.0% of GDP on health
expenditure and for a country that spends 12.0% of GDP. Which prenatal
care percentage that you calculated do you think is closer to the true
percentage? Why? Table #10.1.8: Data of Heath Expenditure versus Prenatal Care HealthExpenditure(% of GDP) PrenatalCare (%) 9.6 47.9 3.7 54.6 5.2 93.7 5.2 84.7 10.0 100.0 4.7 42.5 4.8 96.4 6.0 77.1 5.4 58.3 4.8 95.4 4.1 78.0 6.0 93.3 9.5 93.3 6.8 93.7 6.1 89.8 For
each problem, state the random variables. Also, look to see if there
are any outliers that need to be removed. Do the correlation analysis
with and without the suspected outlier points to determine if their
removal affects the correlation. The data sets in this section are in
section 10.1.10.2.2Table
#10.1.6 (from problem 10.1.2) contains the value of the house and the
amount of rental income in a year that the house brings in ("Capital and
rental," 2013). Find the correlation coefficient and coefficient of
determination and then interpret both.10.2.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information is available
for the year 2011 are in table #10.1.8 (from problem 10.1.4). Find the
correlation coefficient and coefficient of determination and then
interpret both.For each problem, state the random
variables. The data sets in this section are in the homework for section
10.1 and were also used in section 10.2. If you removed any data points
as outliers in the other sections, remove them in this sections
homework too.10.3.2Table
#10.1.6 (from problem 10.1.2) contains the value of the house and the
amount of rental income in a year that the house brings in ("Capital and
rental," 2013).a.) Test at the 5% level for a positive correlation between house value and rental amount.b.) Find the standard error of the estimate.c.) Compute a 95% prediction interval for the rental income on a house worth $230,000.10.3.4The
World Bank collected data on the percentage of GDP that a country
spends on health expenditures ("Health expenditure," 2013) and also the
percentage of woman receiving prenatal care ("Pregnant woman receiving,"
2013). The data for the countries where this information is available
for the year 2011 are in table #10.1.8 (from problem 10.1.4).a.)
Test at the 5% level for a correlation between percentage spent on
health expenditure and the percentage of woman receiving prenatal care.b.) Find the standard error of the estimate.c.)
Compute a 95% prediction interval for the percentage of woman receiving
prenatal care for a country that spends 5.0 % of GDP on health
expenditure.In each problem show all steps of the
hypothesis test. If some of the assumptions are not met, note that the
results of the test may not be correct and then continue the process of
the hypothesis test.11.1.2Researchers
watched groups of dolphins off the coast of Ireland in 1998 to
determine what activities the dolphins partake in at certain times of
the day ("Activities of dolphin," 2013). The numbers in table #11.1.6
represent the number of groups of dolphins that were partaking in an
activity at certain times of days. Is there enough evidence to show that
the activity and the time period are independent for dolphins? Test at
the 1% level. Table #11.1.6: Dolphin Activity Activity Period RowTotal Morning Noon Afternoon Evening Travel 6 6 14 13 39 Feed 28 4 0 56 88 Social 38 5 9 10 62 ColumnTotal 72 15 23 79 189 11.1.4A
person’s educational attainment and age group was collected by the U.S.
Census Bureau in 1984 to see if age group and educational attainment
are related. The counts in thousands are in table #11.1.8 ("Education by
age," 2013). Do the data show that educational attainment and age are
independent? Test at the 5% level.Table #11.1.8: Educational Attainment and Age Group Education Age Group RowTotal 25-34 35-44 45-54 55-64 >64 Did not completeHS 5416 5030 5777 7606 13746 37575 CompletedHS 16431 1855 9435 8795 7558 44074 College 1-3year 8555 5576 3124 2524 2503 22282 College 4 or more years 9771 7596 3904 3109 2483 26863 ColumnTotal 40173 20057 22240 22034 26290 130794 In
each problem show all steps of the hypothesis test. If some of the
assumptions are not met, note that the results of the test may not be
correct and then continue the process of the hypothesis test.11.2.4In
Africa in 2011, the number of deaths of a female from cardiovascular
disease for different age groups are in table #11.2.6 ("Global health
observatory," 2013). In addition, the proportion of deaths of females
from all causes for the same age groups are also in table #11.2.6. Do
the data show that the death from cardiovascular disease are in the same
proportion as all deaths for the different age groups? Test at the 5%
level.Table #11.2.6: Deaths of Females for Different Age Groups Age 5-14 15-29 30-49 50-69 Total Cardiovascular Frequency 8 16 56 433 513 All Cause Proportion 0.10 0.12 0.26 0.52 11.2.6A
project conducted by the Australian Federal Office of Road Safety asked
people many questions about their cars. One question was the reason
that a person chooses a given car, and that data is in table #11.2.8
("Car preferences," 2013).Table #11.2.8: Reason for Choosing a Car Safety Reliability Cost Performance Comfort Looks 84 62 46 34 47 27 Do
the data show that the frequencies observed substantiate the claim that
the reason for choosing a car are equally likely? Test at the 5% level.
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