### Cost of Living Adjustments and Salary Prediction#### OverviewUsing the accompanying Cost of Living Adjustments data, the task is to find the best multiple regression model to predict salary as a function of the adjusted cost for living rates. The goal is to determine the comparable salary for a city with specific cost adjustments.#### InstructionsDetermine the best multiple linear regression model to predict the salary based on other rates. Enter the appropriate coefficients (rounded to three decimal places) for the following potential models:1. **Model A:** - Salary = [ ] + (groceries) + (housing) + (utilities) + (transportation) + (health care)2. **Model B:** - Salary = [ ] + (housing) + (utilities) + (transportation) + (health care)3. **Model C:** - Salary = [ ] + (groceries) + (utilities) + (transportation) + (health care)4. **Model D:** - Salary = [ ] + (groceries) + (housing) + (transportation) + (health care)5. **Model E:** - Salary = [ ] + (groceries) + (housing) + (utilities) + (health care)6. **Model F:** - Salary = [ ] + (housing) + (utilities) + (transportation)7. **Model G:** - Salary = [ ] + (groceries) + (housing) + (health care)8. **Model H:** - Salary = [ ] + (groceries) + (housing) + (utilities) + (transportation)#### Data Table Analysis**Cost of Living Adjustments Data Table:**- This table includes: - **Comparative Salary ($)**: The adjusted salary based on different cost factors. - **Groceries**: Adjustment factor for grocery costs. - **Housing**: Adjustment factor for housing costs. - **Utilities**: Adjustment factor for utilities. - **Transportation**: Adjustment factor for transportation costs. - **Health Care**: Adjustment factor for healthcare costs.#### Example AdjustmentsDetermine the comparable salary for a city with the following adjustments:- **Groceries**: 5%- **Housing**: 8%- **Utilities**: -2%- **Transportation**: -2%- **Health Care**:

The given data is: salary groceries housing utilities health care 60482 0.15 0.25 -0.1 0.05 57530 -0.08 0.13 -0.01 0.06 85904 0.16 1.41 0.45 0.33 60904 0.18 0.22 0.11 0.1 58012 0.11 0.05 0.02 0.06 70000 0.23 0.73 0.01 0.02 54578 0.01 -0.01 -0.05 -0.01 58072 0.12 -0.04 -0.03 0.05 87892 0.2 2.11 -0.06 -0.03 65843 0.07 0.64 -0.08 0.11 57590 -0.02 0.15 0 -0.01 55120 0.03 0.04 -0.11 0.01 83795 0.16 1.69 0.1 0.13 55602 0.01 0.02 -0.13 -0.08 65060 0.16 0.43 -0.1 0.08 57530 0.1 0.24 -0.16 0.01 136024 0.35 4.77 0.29 0.19 72048 0.26 0.72 0.17 0.03 57651 0.07 0.21 -0.08 0.01 59578 0.09 0.21 -0.03 -0.01 77349 0.26 1.08 -0.15 0.15 86446 0.18 1.87 0.18 0.15 105241 0.39 3.02 0.03 0.22 83253 0.31 1.33 0.02 0.24 56084 0.14 -0.09 0.13 0.04 Using Excel<data<megastat<regression Here is the output: Regression Analysis R² 0.996 Adjusted R² 0.995 R 0.998 Std. Error 1369.361 n 25 k 4 Dep. Var. salary ANOVA table Source SS df MS F p-value Regression 8,90,62,36,944.6412 4 2,22,65,59,236.1603 1187.40 1.84E-23 Residual 3,75,02,983.5988 20 18,75,149.1799 Total 8,94,37,39,928.2400 24 Regression output confidence interval variables coefficients std. error t (df=20) p-value 95% lower 95% upper Intercept 55,299.3877 471.41 117.31 0.00 54316.04 56282.74 groceries 13,090.4238 3,777.9545 3.465 .0024 5,209.7488 20,971.0989 housing 14,750.2776 380.0084 38.816 2.64E-20 13,957.5940 15,542.9612 utilities 7,008.4704 2,579.5217 2.717 .0133 1,627.6824 12,389.2585 health care 11,631.4361 4,360.1701 2.668 .0148 2,536.2806 20,726.5916 Answer: Option B Salary= 55299.388 + 13090.424 groceries + 14750.278 housing + 7008.470 utilities + 11631.436 healthcare

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Using the accompanying Cost of Living Adjustments data to find the best multiple regression model to predict the salary as a function of the adjusted cost for living rates. What would the comparable salary be for a city with the following adjustments: groceries. 5%; housing: 8%; utilities: - 2%, transportation: - 2%: and health care: 7%? Use a level of significance of 0.ó5. E Click the icon to view the Cost of Living Adjustments data table. - X Cost of living adjustments data table Determine the best multiple linear regression model to predict the salary as a function of the other rates. Select the best answer below and fil in the corresponding answer boxes to complete your choice. (Type integers or decimals rounded to three decimal places as needed.) Comparative Groceries Housing Utilities Transportation Health Salary (S) O A. Salary =+ (housing + (D utilities + transportation O B. Salary =• O housing + (Dutilitles + Dransportation + (Ohealthcare Care -0. 10 - 0.01 60.482 0.15 0.25 0.06 0.05 57.530 -0.08 0.13 -0.01 0.06 OC. Salary+O 85,904 0.16 1.41 0.45 0.11 0.33 Ogroceries + ( housing + O healthcare OD. Salary =+ (O groceries + Outities + Otransportation +O healthcare • (Dgroceries + (Dhousing + (D OF. Salary =+ (O groceries + (Ohousing + Dutities + (O OG. Salary = (groceries + ( housing + (Dutities + (Dtransportation O H. Salary =• (O groceries + (O housing + O transportation + Oheakhcare 60,904 0.18 0.22 0.11 -0.07 0.10 transportation + ) healthcare 58.012 0.11 0.05 0.02 - 0.02 0.06 70.000 0.23 0.73 0.01 0.18 0.02 OE. Salary= utilities + Ohealthcare 54,578 0.01 - 0.01 - 0.05 -0.06 -0.01 - 0.03 - 0.06 -0.08 transportation + (D healthcare 58.072 0.12 - 0.04 0.01 0.05 87,892 0.20 2.11 0.13 -0.03 65,843 0.07 -0.02 0.64 0.01 0.11 57.590 0.15 0.00 0.06 -0.01 -0.06 0,29 55,120 0.03 0.04 -0.11 0.01 83,795 0.16 1.69 0. 10 - 0. 13 - 0. 10 -0. 16 0.13 55.602 0.01 0.02 0.05 -0.08 0.08 65,060 0.16 0.43 0.10 57,530 0.10 0.24 -0.05 0.01 136,024 0.35 4.77 0.29 0.30 0.19 72.048 0.26 0.72 0.17 0.10 0.03 57,651 0.07 0.21 - 0.08 0.02 0.01 59.578 0.09 0.21 - 0.03 0.14 -0.01 77.349 0.26 1.08 -0.15 0.19 0.15 86,446 0.18 1.87 0.18 0.27 0.15 105,241 0.39 3.02 0.03 0.26 0.22 83.253 0.31 1.33 0.02 0.21 0.24 56.084 0.14 - 0.09 0.13 0.01 0.04