STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup Page 1 of 4 Assignment #3: Inferential Statistics Analysis and Writeup Identifying Information Student (Full Name): Kayla Johnson...

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Answered Same DayFeb 26, 2021

Answer To: STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup Page 1 of 4 Assignment #3:...

Monali answered on Mar 01 2021
155 Votes
10.1.6
                                    Value    Rental        Rental income
                                    81000    6656        Mean    9611
                                    95000    7904        Mode    8320
                                    121000    12064        Median    9568
                                    135000    8320        Standard deviation    2213
                                    145000    8320
                                    165000    13312
                                    178000    11856
                                    200000    12272
                                    214000    8528
                                    240000    10192
                                    289000    11648
                                    325000    12480
                                    77000    4576
                                    94000    8736
                                    115000    7904
                                    130000    9776
                                    140000    9568
                                    165000    8528
                                    174000    10400
                                    200000    10608
                                    208000    10400
                                    240000    12064
                                    270000    12896
                                    310000    12480
                                
    75000    7280
                                    90000    6240
                                    110000    7072
                                    126000    6240
                                    140000    9152
                                    155000    7488
                                    170000    9568
                                    194000    11232
                                    200000    10400
                                    240000    11648
                                    262000    10192
                                    303000    12272
                                    67500    6864
                                    85000    7072
                                    104000    7904
                                    125000    7904
                                    135000    7488
                                    148000    8320
                                    170000    12688
                                    190000    8320
                                    200000    8320
                                    225000    12480
                                    244500    11232
                                    300000    12480
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?
- Regression Equation
y = 0.0244x + 5363.9
- Value of house = X = 230000
Rental = 0.0244 * 230000 +5363.9. Therefore, rental = 10,975.9
- Value of house = X = 40000
Rental = 0.0244 * 400000 +5363.9. Therefore, rental = 15,123.9
-Mean rental income is 9611 and median rental income is 9568. Based on these two statistic rental income of 10,975.9 ~~ 10,956 is close to actual rental income.
Rental - Value of house
Rental    y = 0.0244x + 5363.9
R² = 0.5848
81000    95000    121000    135000    145000    165000    178000    200000    214000    240000    289000    325000    77000    94000    115000    130000    140000    165000    174000    200000    208000    240000    270000    310000    75000    90000    110000    126000    140000    155000    170000    194000    200000    240000    262000    303000    67500    85000    104000    125000    135000    148000    170000    190000    200000    225000    244500    300000    6656    7904    12064    8320    8320    13312    11856    12272    8528    10192    11648    12480    4576    8736    7904    9776    9568    8528    10400    10608    10400    12064    12896    12480    7280    6240    7072    6240    9152    7488    9568    11232    10400    11648    10192    12272    6864    7072    7904    7904    7488    8320    12688    8320    8320    12480    11232    12480    Value of house
Rental
10.1.4
                                                Health Expenditure (% of GDP)    Prenatal Care (%)
                                                9.6    47.9
                                                3.7    54.6
                                                5.2    93.7
                                                5.2    84.7
                                                10    100
                                                4.7    42.5
                                                4.8    96.4
                                                6    77.1
                                                5.4    58.3
                                                4.8    95.4
                                                4.1    78
                                                6    93.3
                                                9.5    93.3
                                                6.8    93.7        Parental care %
                                                6.1    89.8        Mean    79.9
                                                            Median     89.8
                                                            Mode    93.7
                                                            Standard Deviation     19.5
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?
- Regression equation;
y = 1.6606x + 69.739
- GDP expenditure %, X = 5%
Parental care = y = 1.6606 *5 + 69.739 = 78.042
- GDP expenditure % X = 12%
Parental care = y = 1.6606 *12 + 69.739 = 89.6662
- Mean parental care % is 79.9 and Media is 89.8. Based on these two parameters parental care of 89.6662 ~~ 89.7 is closer to true value.
Prenatal Care (%)    y = 1.6606x + 69.739
R² = 0.0294
9.6    3.7    5.2    5.2    10    4.7    4.8    6    5.4    4.8    4.0999999999999996    6    9.5    6.8    6.1    47.9    54.6    93.7    84.7    100    42.5    96.4    77.099999999999994    58.3    95.4    78    93.3    93.3    93.7    89.8    
10.2.2
                                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
                                    77000    4576
                                    94000    8736
                                    115000    7904
                                    130000    9776            Value    Rental
                                    140000    9568        Value    1
                                    165000    8528        Rental    0.7647157521    1
                                    174000    10400
                                    200000    10608
                                    208000    10400
                                    240000    12064
                                    270000    12896
                                    310000    12480
                                    75000    7280
                                    90000    6240
                                    110000    7072
                                    126000    6240
                                    140000    9152
                                    155000    7488
                                    170000    9568
                                    194000    11232
                                    200000    10400
                                    240000    11648
                                    262000    10192
                                    303000    12272
                                    67500    6864
                                    85000    7072
                                    104000    7904
                                    125000    7904
                                    135000    7488
                                    148000    8320
                                    170000    12688
                                    190000    8320
                                    200000    8320
                                    225000    12480
                                    244500    11232
                                    300000    12480
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). Find the correlation coefficient and coefficient of determination and then interpret both.
Correlation coefficient measures linear relationship between two variables, that is, how closely or spread out two variable data points are. Correlation coefficient is = √0.5048 = 0.7647. This means that variable of value explains rental to 76.47% which is very strong relationship exists between value and rental.
Coefficient of determination tells how well model explains and predict based on given regression. This is important statistic to look in conjunction to correlation coefficient to get complete...
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