Question

Run the following multivariate linear regression models:

Model 1: X3 and X4

Model 2: X2,X3,and X4Model 3: X1, X3 and X4Discuss the correlation between each two variables using adjusted R2 and P-value. Write the estimated equation of Y for each regression model. Briefly comment of the Residual Plots.

SUMMARY OUTPUT Regression Statistics Tourist arrivals (X3) Residual Plot Mu R Square Adjusted R Square Standard Error Observations 0.77706686 0.60383291 0.58622549 26011267.3 48 ANOVA Significance F 4.6406E 16 2.3203E 16 34.2942181 8.9591E-10 MS 90C0O0O 10000OOO 2S000000 3000000 3500 000 40000000 45000000 Regression Residual Total 45 47 3.04464E 16 6.7659E 14 7.68523E+16 -10000000 Tourist arrivals (x3) Coefficients Standord Error Lower 95% 172127627.1 7.9920458 3.5402E-10 1.722E+09 -1.029E+09 1.722E+091.029E+09 0.50480B817 1.92569465 0.06047525D.0446295 1.98884479 -0.0446295 1.98884479 Upper 95% Lower g 5.0% Upper g 5.0 Intercept Tourist arrivals (X3 Population X4) 1.376E+09 .7210764 17.4162034 Population (X4) Residual Plot 2.1169259 8.22712 1.614E-10 13.1524958 21.679911 13.1524958 21.679911 10000000 500000 10 1214 16 18 20 RESIDUAL OUTPUT 500C000 Observation umber ofoas Residuais 1 4762727.37 2 7385190.99 3 11813359 4 37644117.7 5 18941858.8 6 22B48440.9 7 9453262.45 1745272.626 335990.9925 3794258.956 30172817.74 9954958.763 13379240.92 1165337.552 -25000000 35000000 Population (K4) SUMMARYOUTPUT Regression Statistics Tourist departures (X2) Residual Plot Multiple R R Square Adjusted R Square Standard Error Observations 0.92247996 0.85096927 0.84080808 16133929.3 48 20000000 80000000 100000000 ANOVA Tourist departures (X2) Signiicance F 6.5399E416 2.18E+16 83.7470405 3.2332E-18 MS Residual Total 44 1.14534E 16 2.603E 14 47 Tourist arrivals (X3) Residual Plot 7.68523E+16 20000000 10000000 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 174018840 1.1598332 D.25237183 -552544763 148879092 -552544763 148879092 Tourist departures (X2 2.94964147 D.345312648 8.5419444 6.8145E-11 2.25370955 3.64557338 2.25370955 3.64557338 Coeficients Standord Error 201832835 Stot Intercept 20 10000000 Tourlst arrlvals X3 0.4710377 0.355788183 1.3239273 0.19236434 -1.1880817 0.24600627-1.1880817 0.24600627 0.67684346 ulation (x4) 2.358901439 0.28693164 0.77551157 4.07721 5.430896934.07721 5.43089693 Tourist arrivals (x3) Population (X4) Residual Plot RESIDUAL OUTPUT Observation 10000000 umber of pas 1 -7279186.3 13787186.29 2 -5299193.8 12348393.79 3 -2698173 10717273.02 4 -159137. 5 1744280.89 Residuois 18 20 35 7630437.346 7242619.106 Population (X4) Regresslon Statistics GDP per capita (X1) Residual Plot Multiple R R Square Adjusted RSquare Standard Error Observatians 0.95876868 0.91923738 0.91373084 11877018.4 48 ANOVA S5 Significance F 7.05456E 16 2.3549E 16 166.935503 4.7003E-24 MS GDP per capita 1] Regression Residual Tatal 6.2068E+15 1.4106E+14 7.69523E-16 Tourist arrivals (X3) Residual Plot 47 10000000 Coefficients Stondard Errar P-volue Lower 95% Upper 95% Lower 95.0%Upper 95.0% 142664023.9 1.29732951 0.201279-102438199 472602697 -102438199 472602697 226.258327 13.1085624 8.5147E-17 2509.92771 3421.9151 2509.92771 3421.9151 0.274398638 3.569388 0.000879521.5324493 0.4264211 1.53244930.4264211 1.785801634 -1.2696765 0.21087419 -5.8664371 1.33165634 -5.B664371 1.33165634 t Stat Intercept GDP per capita (X1) 2965.9214 Taurist arrivals (X3) 0.9794352 Population x4) 185082249 14 16 18 20 5000000 2.2673904 Tourist arrivals D3) Population (X4) Residual Plot RESIDUAL OUTPUT Observotion Vumber ofpas 1 -59555.953 2 1089167.3 3 664142.538 4 -928238.27 5 3564423.83 6 3014720.07 Residucis 6567555.953 8138367.283 7354957.462 8399538.271 422476.172 6454479.926 12 14 16 18 20 5000000 Populatian (X4)

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