Question

Run the following multivariate linear regression models:

Notes: Every Professor or Tutor, I used Excel to do my data analysis ( regression) below. Thanks

1.Model 1(X3, X4):2. Model 2 ( X2, X3 &X4):3. Model 3 (X1,X3 & X4):a) Discuss the correlation between each two variables using adjusted R2 and P-Value

b) Write the estimated equation of Y for each regression model.

c) Briefly comment of the Residual Plots.

SUMMARY OUTPUT Tourist arrivals (X3) Residual Plot Regression Stotistics 80000000 Multpe R RSquarm Adjusted R Squarr Standard Ermor Observatlons 0.7770SG964 0.603832912 6C0DoDo0 Plot Area 26011267.32 .. . / ANOVA 5000 до 100 000 15000000 00425000000 30000000 35000000 40000000 45000000 -200000,' MS Sianficance F Regression 2 4.640654162.3203E+16 34.29421806 8.95909E-10 45 3.044645+16 6.75586E+14 47 7.68S23+16 Tatal Tourist arrvals (x3) Coefficients Stundard Error Population (X4) Residual Plot Intercrpt Taurist amals X3 Popuation (X4) 1375651882 172127627.1 7.992045817 3.54019E-1017223347191028969045 1722334719 1028959045 0.972107638 0.504808817 1.925694650.0E0475247 -Q0446295 11 1.988844788 -Q044629511 1.988844788 2.1169259 8.227119598 1.61402E-10 13,15249577 21.67991103 13.1524957721.67991103 78880000000 17,4162034 RESIDUALOUTPUT Observution Predicted Nuumber of passengers Residus 83000000 4762727.374 1745272.626 7385190.993 -335990.9925 11913358.96-3794259.956 37644113.430172817.74 18941858.76 9954958 763 Population (X4) SUMMARY OUTPUT Tourist departures (X2) Residual Plot Regression Stotishics Multple R RSquare djusted RSquare Standard Emor observatons 0.922479956 0.85096927 Chart Area 16133929.29 ANOVA S5 IMS Regression Resicual 3 6.5399 1621797E+16 83.7470403.23317E-18 44 1.14534E+16 260304E+14 47 7.68523E+ 16 Tourlst departures x2) Tourist arrivals (X3) Residual Plot Coefficients Stundurd Error Stat Lower 95% Upper 9536 Lower 95.0% Upper 95.0% 201932935.1 174019840 1.15983324 0.252371831 552544762.6 149879092.4552544762.6148879092.4 2.9496414670.ョ45312648 &:41944477 6.81452E-11 2.253709553 ョ.645573381 2.253709553 3.645573381 0,471037557 0.3557881831.32327326 01923643391.188081664 .246006269-1.1880816640.246006269 0.286931641 0.775511575 -4.077210011 5.43086933 -4.077210011 5.430896933 nterceat Tourist antvals (x3 Popu ation (x4 0.676843461 2.358901439 2soc h09 45 5000000 100СООО 15000000 2000000 RESIDUALOUTPUT Observation dicted Numberof passengers Residos Tourist arriwals X3 7279188.293 13787196.29 5299193.788 12348393.79 2638173.024 10717273,02 59137.3455 7630437.346 1744280.894 7242619.106 2993997.064 6475202 936 5387568.331 5231031.669 6653424,229 4314075 771 8691671.947 3318128.053 1095220417 1881695.831 13366360.96319960.9576 185114616 5447059.165 Population (X4) Residual Plot odd 000000 ◆ 800 sooo ◆81000000 ◆42000000 83000000 Population (x4) 12 SUMMARY OUTPUT GDP per capita (X1) Residual Plot Regresskon Shotks 10000000 Multple R RSquare Adjusted R Square Standard Error Observatons 0.95876868 0.919237282 0.91373084 11877018.37 1000 eup 40000 50000 60000 GDP per capita (x1) Regression 3 7.06456+16 2.3549SE+16 166.9355032 4.70033E-24 446.2068E+15 141064E-14 47 7.68523E+16 Tourist arrivals (X3) Residual Plot Total Standord Emor Upper 95% Lower 95 036 Upper 95.0% 20000000 8.5147E17 2309.927O 3421.91SS 2509.9273421.915088 0.9794352 0.274398038 1.509387984 0.00087952 -1532449316 -0.420421083 -1.532449316 -0.420421083 2.26739063 1.79580134 -126957497 0.21087416 -5.866437071 1.331656344-5.965437071 1.331656344 955.921402 226.25832713.10856242.5 Taurist arrivals 0X3) Papulaton (x4 Tourist amivals [3) Population (X4) Residual Plot Observotion Predicted Nnber enger Y esua 59555.95286 6567555.953 1089167.283 8138367.283 664142.5375 7354957,462 9282382711 8359538.271 40000000 2000000 10000000 014720.04 6454479.926 6077022.539 4541577.461 7166380.45 3841119.55 11443936.09 565853.9111 15877721.43 -3033821.432 Populati 4

Answer 1

wr hove fhree mhvariate models del 3 we have fo dir(utr Clahor eween each tuoo variales usin adiuu rion mde4 comment on resitere s

t) estimahed refveJsion mode .462034) Residual lot here fonts 「caHered amoun come poinht are fasitive some a^e nejahve hente t s Random pattern indrcater Flat a eo mode frovide decent t to tme datq

e Point oe not - random r attertn = 0.9 2.2

f value from aNDV From p value here only ti var o agnificant other not because otrer valde 〉 ο.ος.

) f esidwelelot: ratHem indiceaber nat ne model Provider fo daha 2 hone it is ind/cates tna ๑ltir non in mode it is indicates 따 non 'mem model

foymodel 3 very grod . relah given Regrerrjon mod i Sjjficont E timated Regression mbd J :.

From p value her onl y,4 vanjakle )Kenidual plot:- dato frr X2 hene Random patterm no+ no tinear model ht to data