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Please help me with my multiple regression model using the variables and parameter that i have chosen c. For your chosen Qualitative parameters, state the
Please help me with my multiple regression model using the variables and parameter that i have chosen
c. For your chosen Qualitative parameters, state the different "conditions". The Conditions are the different models that I am looking at which are Civic(1,0), BR-V (0,1), and Yezel(0,0). d. Clearly define and state the values for each of the Dummy Variables for your Qualitative parameter. The Dummy variables are Civic(1,0), BR-V (0,1). 4. State your proposed Multilinear Regression Model for Y Yin the general form. State the equation for YY in the general form. Keep in mind that you can introduce quadratic Independent Variables in your model (1+1=2 Points) 5. Collect at least 25 sets of observations ( Y and S ) for your model and report it in a table formot that includes the values for the Dummy Variables and the column stating the qualitative. conditions. The required data needs to be from a reliable source (10 Points) 6. Identify at least one other possible variable (quantitative or qualitative) that you may consider including in your model later and state your reason for its possible relevance (1+1=2 Points) Part 2-Calculation and Interpretation 7. Run the Regression Model using the data collected in Part 1, using the Excel Add-Ins. Provide a copy of your printout -6 Points Note: Must have ot leost 2 Quantitative and ot leost 1 Qualitative Independent Variables 8. Using the calculated values in your printout, state the regression equation for YY1 foints 9. Report and interpret the value of the r22 Points 10. Using a 95% level of confidence, test if the model (equation) is statically significant and state why? -1 Points 11. Using a 95% level of confidence, test if each of the independent Variables are statically significant in explaining the variations in YY and state why? -2 Points 12. State up to what level of confidence is the model statically significant - 1 points 13. State up to what level of confidence is each independent Variable statically significant -2 fepints 14. State how a unit change in eoch Quantitative Independent Variable changes the predicted value of the Dependent Variable - 4 Points 14. State how a unit change in each Quantitative Independent Variable changes the predicted value of the Dependent Variable -4 Points 15. State how each category of the Qualitative Variables changes the predicted value of the Dependent Variable -4 Points 16. For any XXii found not to be significant, provide a possible explanation -2 Points (8) Possible Data Loss Some features might be lost if you save this workbook in the comma-del. \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline 12 & & ^x & fx & & & = & & & & \\ \hline & A & 8 & c & D & E & F & G & H & 1 & 1 \\ \hline 1 & make & model & year & engine ( x1) & mileage (xz) & price & Ovic (X3) & BR-V (XA) & Verel (XS) & \\ \hline 2 & Honda. & Cwic & 2017 & 1800 & 86000 & 4850000 & 1 & 0 & 0 & \\ \hline 3 & Honda & BRV & 2020 & 1500 & 67500 & 5175000 & 0 & 1 & 0 & \\ \hline 4 & Honda & Ovic & 2018 & 1800 & 76000 & 5200000 & 1 & 0 & 0 & \\ \hline 5 & Honda & Civic & 2017 & 1800 & 117000 & 4900000 & 1 & 0 & 0 & \\ \hline 6 & Honda & Givic & 2015 & 1800 & 126000 & 2975000 & 1 & 0 & 0 & \\ \hline 7 & Honda & Cvic & 2015 & 1800 & 147000 & 4300000 & 1 & 0 & 0 & \\ \hline 8 & Honda & Ovic & 2017 & 1800 & 106000 & 5150000 & 1 & 0 & 0 & \\ \hline 9 & Honda & Civic & 2015 & 1800 & 126000 & 2975000 & 1 & 0 & 0 & \\ \hline 10 & Honda & Civic & 2018. & 1800 & 114200 & 5090000 & 1 & 0 & 0 & \\ \hline 11 & Honda & Vezel & 2017 & 1500 & 10500 & 8475000 & 0 & 0 & 1 & \\ \hline 12 & Honda & Vezel & 2015 & 1500 & 100423 & 4395000 & 0 & 0 & 1 & \\ \hline 13 & Honds & Givic & 2018 & 1800 & 65000 & 5395000 & 1 & 0 & 0 & \\ \hline 14 & Honda & Civic & 2020 & 1800 & 41000 & 6300000 & 1 & 0 & 0 & \\ \hline 15 & Honda & Vezel & 2018 & 1500 & 59000 & 8900000 & 0 & 0 & 1 & \\ \hline 16 & Honda & Civic & 2018 & 1800 & 73000 & 5250000 & 1 & 0 & 0 & \\ \hline 17 & Honda & Ovie & 2021 & 1800 & 28000 & 6700000 & 1 & 0 & 0. & \\ \hline 18 & Honda & Give & 2018 & 1800 & 75000 & 5750000 & 1 & r: & 0 & \\ \hline 19 & Honda & Givic & 2019 & 1800 & 60500 & 5700000 & 1 & 0 & 0 & \\ \hline 20 & Honda & Give & 2015 & 1800 & 91000 & 3850000 & 1 & 0 & 0 & \\ \hline 21 & Hondar & Give & 2015 & 1800 & 64000 & 4500000 & 1 & 0 & 0 & \\ \hline 22 & Honda & Give & 2020 & 1800 & 3000 & 6700000 & 1 & 0 & 0 & \\ \hline 23 & Honda & BR-V & 2019 & 1500 & 55800 & 3965000 & 0 & -1 & 0 & \\ \hline 24 & Honda & Givic & 2017 & 1800 & 80000 & 4850000 & 1 & 0 & 0 & \\ \hline 25 & Honda & Givic & 2016 & 1800 & 156000 & 3200000 & 1 & 0 & 0 & \\ \hline 26 & Honda & BRV & 2017 & 1500 & 33193 & 4250000 & 0 & 1 & 0 & \\ \hline 27 & Honda & Civic & 2017 & 1800 & 71941 & 5190000 & 1 & 0 & 0 & \\ \hline 28 & Honds & Givic & 2018 & 1800 & 75000 & 5350000 & 1 & 0 & 0 & \\ \hline 29 & Honda & BRV & 2019 & 1500 & 33700 & 4800000 & 0 & 1 & 0 & \\ \hline 30 & Honda & Oric & 2018 & 1800 & 84000 & 5550000 & 1 & D & 0 & \\ \hline 31 & Honda & Civic & 2018 & 1800 & 76000 & 5550000 & 1 & 0 & 0 & \\ \hline 32 & & & & & is & & & & & \\ \hline 33 & & 3 & & 4. & 4 & & & & & \\ \hline & & & & & & & & & & \\ \hline & & & & & & & & & & \\ \hline 37 & & & & E. & & & & & & \\ \hline 38 & & & & & & & & & & \\ \hline 4 & 41 & pakwheels y & used_car dat & ta v02 & Data & Sheet2 & + & & & \\ \hline & Reody & if Accessibil & ility: Unavaila & able & & (If) & & & - & + \\ \hline \end{tabular} 1. Dependent Variable (1+1=2 Points ) a. Choose and define a variable that you have an interest in predicting/estimating ( n ) The variable that I am interested in predicting is the Selling price of a used car(Y) b. State what is your interest in this variable I am curious as to what goes into determining the price one should pay for a used car: 2. Quantitative Independent Variables (2+2=4 Points ) a. Identify and define at least two quantitative parameters (XX1,XX2, and ...) that you believe to be relevant in explaining the variations in The two quantitative parameters that I believe are rievant when determining price of a used car are the mileage that the car has on it and the cc 's of the engine. b. State your logic/reasons for believing why each XXU is relevant in predicting the values of Y Mileage is relevant because it can be used to predict how much use you can get out of that car. Engine CC's is relevant because it plays a huge role in performance factors. 3. Qualitative Independent Variable (1+1+1+2=5 Points) a. Identify and define at least one Qualitotive parameter that you believe to be relevant in explaining the variations in Y. One qualitative parameter that I believe is relevant to price is the model of the car being sold. b. State your logic/reasons for believing why each qualitative variable is relevant in predicting the values of . The car model is relevant because different models of cars are usually more expensive than others. For example, a Honda Accord is usually more expensive than a Honda Clvic even though they are made by the same company, there are differences in the model that make it more expensive. c. For your chosen Qualitative parameters, state the different "conditions". The Conditions are the different models that I am looking at which are Civic(1,0), BR-V(0,1), and Vezel (0,0). c. For your chosen Qualitative parameters, state the different "conditions". The Conditions are the different models that I am looking at which are Civic(1,0), BR-V (0,1), and Yezel(0,0). d. Clearly define and state the values for each of the Dummy Variables for your Qualitative parameter. The Dummy variables are Civic(1,0), BR-V (0,1). 4. State your proposed Multilinear Regression Model for Y Yin the general form. State the equation for YY in the general form. Keep in mind that you can introduce quadratic Independent Variables in your model (1+1=2 Points) 5. Collect at least 25 sets of observations ( Y and S ) for your model and report it in a table formot that includes the values for the Dummy Variables and the column stating the qualitative. conditions. The required data needs to be from a reliable source (10 Points) 6. Identify at least one other possible variable (quantitative or qualitative) that you may consider including in your model later and state your reason for its possible relevance (1+1=2 Points) Part 2-Calculation and Interpretation 7. Run the Regression Model using the data collected in Part 1, using the Excel Add-Ins. Provide a copy of your printout -6 Points Note: Must have ot leost 2 Quantitative and ot leost 1 Qualitative Independent Variables 8. Using the calculated values in your printout, state the regression equation for YY1 foints 9. Report and interpret the value of the r22 Points 10. Using a 95% level of confidence, test if the model (equation) is statically significant and state why? -1 Points 11. Using a 95% level of confidence, test if each of the independent Variables are statically significant in explaining the variations in YY and state why? -2 Points 12. State up to what level of confidence is the model statically significant - 1 points 13. State up to what level of confidence is each independent Variable statically significant -2 fepints 14. State how a unit change in eoch Quantitative Independent Variable changes the predicted value of the Dependent Variable - 4 Points 14. State how a unit change in each Quantitative Independent Variable changes the predicted value of the Dependent Variable -4 Points 15. State how each category of the Qualitative Variables changes the predicted value of the Dependent Variable -4 Points 16. For any XXii found not to be significant, provide a possible explanation -2 Points (8) Possible Data Loss Some features might be lost if you save this workbook in the comma-del. \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline 12 & & ^x & fx & & & = & & & & \\ \hline & A & 8 & c & D & E & F & G & H & 1 & 1 \\ \hline 1 & make & model & year & engine ( x1) & mileage (xz) & price & Ovic (X3) & BR-V (XA) & Verel (XS) & \\ \hline 2 & Honda. & Cwic & 2017 & 1800 & 86000 & 4850000 & 1 & 0 & 0 & \\ \hline 3 & Honda & BRV & 2020 & 1500 & 67500 & 5175000 & 0 & 1 & 0 & \\ \hline 4 & Honda & Ovic & 2018 & 1800 & 76000 & 5200000 & 1 & 0 & 0 & \\ \hline 5 & Honda & Civic & 2017 & 1800 & 117000 & 4900000 & 1 & 0 & 0 & \\ \hline 6 & Honda & Givic & 2015 & 1800 & 126000 & 2975000 & 1 & 0 & 0 & \\ \hline 7 & Honda & Cvic & 2015 & 1800 & 147000 & 4300000 & 1 & 0 & 0 & \\ \hline 8 & Honda & Ovic & 2017 & 1800 & 106000 & 5150000 & 1 & 0 & 0 & \\ \hline 9 & Honda & Civic & 2015 & 1800 & 126000 & 2975000 & 1 & 0 & 0 & \\ \hline 10 & Honda & Civic & 2018. & 1800 & 114200 & 5090000 & 1 & 0 & 0 & \\ \hline 11 & Honda & Vezel & 2017 & 1500 & 10500 & 8475000 & 0 & 0 & 1 & \\ \hline 12 & Honda & Vezel & 2015 & 1500 & 100423 & 4395000 & 0 & 0 & 1 & \\ \hline 13 & Honds & Givic & 2018 & 1800 & 65000 & 5395000 & 1 & 0 & 0 & \\ \hline 14 & Honda & Civic & 2020 & 1800 & 41000 & 6300000 & 1 & 0 & 0 & \\ \hline 15 & Honda & Vezel & 2018 & 1500 & 59000 & 8900000 & 0 & 0 & 1 & \\ \hline 16 & Honda & Civic & 2018 & 1800 & 73000 & 5250000 & 1 & 0 & 0 & \\ \hline 17 & Honda & Ovie & 2021 & 1800 & 28000 & 6700000 & 1 & 0 & 0. & \\ \hline 18 & Honda & Give & 2018 & 1800 & 75000 & 5750000 & 1 & r: & 0 & \\ \hline 19 & Honda & Givic & 2019 & 1800 & 60500 & 5700000 & 1 & 0 & 0 & \\ \hline 20 & Honda & Give & 2015 & 1800 & 91000 & 3850000 & 1 & 0 & 0 & \\ \hline 21 & Hondar & Give & 2015 & 1800 & 64000 & 4500000 & 1 & 0 & 0 & \\ \hline 22 & Honda & Give & 2020 & 1800 & 3000 & 6700000 & 1 & 0 & 0 & \\ \hline 23 & Honda & BR-V & 2019 & 1500 & 55800 & 3965000 & 0 & -1 & 0 & \\ \hline 24 & Honda & Givic & 2017 & 1800 & 80000 & 4850000 & 1 & 0 & 0 & \\ \hline 25 & Honda & Givic & 2016 & 1800 & 156000 & 3200000 & 1 & 0 & 0 & \\ \hline 26 & Honda & BRV & 2017 & 1500 & 33193 & 4250000 & 0 & 1 & 0 & \\ \hline 27 & Honda & Civic & 2017 & 1800 & 71941 & 5190000 & 1 & 0 & 0 & \\ \hline 28 & Honds & Givic & 2018 & 1800 & 75000 & 5350000 & 1 & 0 & 0 & \\ \hline 29 & Honda & BRV & 2019 & 1500 & 33700 & 4800000 & 0 & 1 & 0 & \\ \hline 30 & Honda & Oric & 2018 & 1800 & 84000 & 5550000 & 1 & D & 0 & \\ \hline 31 & Honda & Civic & 2018 & 1800 & 76000 & 5550000 & 1 & 0 & 0 & \\ \hline 32 & & & & & is & & & & & \\ \hline 33 & & 3 & & 4. & 4 & & & & & \\ \hline & & & & & & & & & & \\ \hline & & & & & & & & & & \\ \hline 37 & & & & E. & & & & & & \\ \hline 38 & & & & & & & & & & \\ \hline 4 & 41 & pakwheels y & used_car dat & ta v02 & Data & Sheet2 & + & & & \\ \hline & Reody & if Accessibil & ility: Unavaila & able & & (If) & & & - & + \\ \hline \end{tabular} 1. Dependent Variable (1+1=2 Points ) a. Choose and define a variable that you have an interest in predicting/estimating ( n ) The variable that I am interested in predicting is the Selling price of a used car(Y) b. State what is your interest in this variable I am curious as to what goes into determining the price one should pay for a used car: 2. Quantitative Independent Variables (2+2=4 Points ) a. Identify and define at least two quantitative parameters (XX1,XX2, and ...) that you believe to be relevant in explaining the variations in The two quantitative parameters that I believe are rievant when determining price of a used car are the mileage that the car has on it and the cc 's of the engine. b. State your logic/reasons for believing why each XXU is relevant in predicting the values of Y Mileage is relevant because it can be used to predict how much use you can get out of that car. Engine CC's is relevant because it plays a huge role in performance factors. 3. Qualitative Independent Variable (1+1+1+2=5 Points) a. Identify and define at least one Qualitotive parameter that you believe to be relevant in explaining the variations in Y. One qualitative parameter that I believe is relevant to price is the model of the car being sold. b. State your logic/reasons for believing why each qualitative variable is relevant in predicting the values of . The car model is relevant because different models of cars are usually more expensive than others. For example, a Honda Accord is usually more expensive than a Honda Clvic even though they are made by the same company, there are differences in the model that make it more expensive. c. For your chosen Qualitative parameters, state the different "conditions". The Conditions are the different models that I am looking at which are Civic(1,0), BR-V(0,1), and Vezel (0,0)
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