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STAT 200 Week 7 Homework Problems 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," XXXXXXXXXXCreate a...

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STAT 200 Week 7 Homework Problems
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
ings in ("Capital and rental," XXXXXXXXXXCreate 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
10.1.4
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," XXXXXXXXXXThe data for the countries where this information are available for the year 2011 is in table # XXXXXXXXXXCreate 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
    Health Expenditure (% of GDP)
    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
10.2.2
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house
ings in ("Capital and rental," XXXXXXXXXXFind the co
elation coefficient and coefficient of determination and then interpret both.
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
10.2.4
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," XXXXXXXXXXThe data for the countries where this information is available for the year 2011 are in table # XXXXXXXXXXFind the co
elation coefficient and coefficient of determination and then interpret both.
Table #10.1.8: Data of Health Expenditure versus Prenatal Care
    Health Expenditure (% of GDP)
    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
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
ings in ("Capital and rental," 2013).
Test at the 5% level for a positive co
elation between house value and rental amount.

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
10.3.4
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," XXXXXXXXXXThe 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 co
elation 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
    Health Expenditure (% of GDP)
    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
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," XXXXXXXXXXThe 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
    Row
Total
    
    Morning
    Noon
    Afternoon
    Evening
    
    Travel
    6
    6
    14
    13
    39
    Feed
    28
    4
    0
    56
    88
    Social
    38
    5
    9
    10
    62
    Column Total
    72
    15
    23
    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," XXXXXXXXXXDo 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
    Row Total
    
    25-34
    35-44
    45-54
    55-64
    >64
    
    Did not complete HS
    5416
    5030
    5777
    7606
    13746
    37575
    Competed HS
    16431
    1855
    9435
    8795
    7558
    44074
    College 1-3 years
    8555
    5576
    3124
    2524
    2503
    22282
    College 4 or more years
    9771
    7596
    3904
    3109
    2483
    26863
    Column Total
    40173
    20057
    22240
    22034
    26290
    130794
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," XXXXXXXXXXIn addition, the proportion of deaths of females from all causes for the same age groups are also in table # XXXXXXXXXXDo 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
    
11.2.6
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 Ca
    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.
Answered Same Day Aug 03, 2021

Solution

Biswajit answered on Aug 04 2021
142 Votes
STAT 200 Week 7 Homework Problems
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
ings 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
Ans :

As shown regression equation is Rental income = 0.0244 x House Value + 5363.9
@ 2,30,000 house value,rental income is 10976
@ 4,00,000 house value,rental income is 15124
Well,I think the rental income calculated @2,30,000 is closer to actual value as the prediction is for values of house which lie within available dataset whereas the rental value predicted for 4,00,000 may not be accurate enough as the value 4,00,000 lies beyond the range of given values of house value (it needs extrapolation & extrapolation may not be accurate in regression)
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
    Health Expenditure (% of GDP)
    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
Ans :
We have attached equation for both linear & quadratic regression above but p value of Anova test shows both are not statistically significant.
We will use the linear equation for answering question here.
@5% of GDP on Health expenditure,% of women receiving prenatal care is 78%
@12% of GDP on Health expenditure,% of women receiving prenatal care is 90%.
We think @5% will be more accurate as 5% is within the range of % of GDP on health expenditure available on in dataset but 12% is extrapolated one,so less accurate.
Moreover,both the equations are statistically insignificant so predictions are not robust.
10.2.2
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house
ings in ("Capital and rental," 2013). Find the co
elation coefficient and coefficient of determination and then interpret both.
Table #10.1.6: Data of House Value versus...
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