Transcribed Text
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.
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