10.1.2 Table #10.1.6 contains the value of the house and the amoun...

10.1.2 Table #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 81000 6656 95000 7904 121000 12064 135000 8320 145000 8320 165000 13312 178000 11856 200000 12272 214000 8528 240000 10192 289000 11648 325000 12480 Value Rental 77000 4576 94000 8736 115000 7904 130000 9776 140000 9568 165000 8528 174000 10400 200000 10608 208000 10400 240000 12064 270000 12896 310000 12480 Value Rental Value Rental 75000 7280 67500 6864 90000 6240 85000 7072 110000 7072 126000 6240 140000 9152 155000 7488 170000 9568 194000 11232 200000 10400 240000 11648 262000 10192 303000 12272 104000 7904 125000 7904 135000 7488 148000 8320 170000 12688 190000 8320 200000 8320 225000 12480 244500 11232 300000 12480 10.1.4 The World Bank collected data on the percentage of GDP that a country spends on health expenditures ("Health expenditure," 2013) and also the percentage of women 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 women receiving prenatal care. Then use the regression equation to find the percent of women 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 Health Expenditure versus Prenatal Care 9.6 47.9 3.7 54.6 5.2 93.7 5.2 84.7 10.0 100.0 4.7 42.5 Health Expenditure (% of GDP) Prenatal Care (%) 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 10.2.2 Table #10.1.6 contains the value of the house and the amount of rental income in house brings in ("Capital and rental," 2013). Find the correlation coefficient and determination and then interpret both. a year that the coefficient of Rental 6864 7072 7904 7904 7488 8320 12688 8320 8320 12480 11232 12480 Table #10.1.6: Data of House Value versus Rental Value Rental 81000 6656 95000 7904 121000 12064 135000 8320 145000 8320 165000 13312 178000 11856 200000 12272 214000 8528 240000 10192 289000 11648 325000 12480 Value Rental 77000 4576 94000 8736 115000 7904 130000 9776 140000 9568 165000 8528 174000 10400 200000 10608 208000 10400 240000 12064 270000 12896 310000 12480 Value Rental 75000 7280 90000 6240 110000 7072 126000 6240 140000 9152 155000 7488 170000 9568 194000 11232 200000 10400 240000 11648 262000 10192 303000 12272 Value 67500 85000 104000 125000 135000 148000 170000 190000 200000 225000 244500 300000 10.2.4 The World Bank collected data on the percentage of GDP that a country spends on health expenditures ("Health expenditure," 2013) and also the percentage of women 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. Find the correlation coefficient and coefficient of determination and then interpret both. Table #10.1.8: Data of Health Expenditure versus Prenatal Care 9.6 47.9 Health Expenditure (% of GDP) Prenatal Care (%) 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 10.3.2 Table #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). Test at the 5% level for a positive correlation between house value and rental amount. Table #10.1.6: Data of House Value versus Rental Value Rental 81000 6656 95000 7904 121000 12064 135000 8320 145000 8320 165000 13312 178000 11856 200000 12272 214000 8528 240000 10192 289000 11648 325000 12480 Value Rental 77000 4576 94000 8736 115000 7904 130000 9776 140000 9568 165000 8528 174000 10400 200000 10608 208000 10400 240000 12064 270000 12896 310000 12480 Value Rental 75000 7280 90000 6240 110000 7072 126000 6240 140000 9152 155000 7488 170000 9568 194000 11232 200000 10400 240000 11648 262000 10192 303000 12272 Value Rental 67500 6864 85000 7072 104000 7904 125000 7904 135000 7488 148000 8320 170000 12688 190000 8320 200000 8320 225000 12480 244500 11232 300000 12480 10.3.4 The World Bank collected data on the percentage of GDP that a country spends on health expenditures ("Health expenditure," 2013) and also the percentage of women 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. Test at the 5% level for a correlation between percentage spent on health expenditure and the percentage of women receiving prenatal care. Table #10.1.8: Data of Health Expenditure versus Prenatal Care 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 Health Expenditure (% of GDP) Prenatal Care (%) 11.1.2 Researchers 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 Morning Travel 6 Feed 28 Social 38 Column 72 Total Period Row Noon Afternoon 6 14 4 0 5 9 15 23 Evening Total 13 39 56 88 10 62 79 189 11.1.4 A 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 Age Group Education 25-34 35-44 45-54 55-64 >64 Competed 16431 1855 9435 8795 7558 HS Row Total 44074 22282 26863 130794 Did not complete HS 5416 5030 5777 7606 13746 37575 College 1-3 years College 4 or more years Column Total 8555 5576 9771 7596 40173 20057 3124 2524 2503 3904 3109 2483 22240 22034 26290 11.2.4 In 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 Cardiovascular Frequency All Cause Proportion 5-14 15-29 30-49 50-69 Total 8 16 56 433 513 0.10 0.12 0.26 0.52 11.2.6 A 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 reasons for choosing a car are equally likely? Test at the 5% level.