Homework 6
Victoria Escobedo
2025-04-01
- Load your chosen dataset into Rmarkdown
pavements<-read.csv("pavements_3192083553624189959.csv")- Select the dependent variable you are interested in, along with independent variables which you believe are causing the dependent variable
Dependent variable is Pavement Condition Index (PCI). This is the numerical rating of the street surface condition from 0, non-existent, to 100, pristine.
The independent variables are RoadFunction, OneWay, and MaintenanceResponsibility. The road function is the classification of the roadway based on the amount of traffic anticipated.The Oneway is a yes/no response of the roadway being one way or two way traffic. The maintenance responsibility is who is designated to perform routine maintenance on that particular road segment.
- create a linear model using the “lm()” command, save it to some object
pavements_model<-lm(PCI~RoadFunction+OneWay+MaintenanceResponsibility,data=pavements)- call a “summary()” on your new model
summary(pavements_model)##
## Call:
## lm(formula = PCI ~ RoadFunction + OneWay + MaintenanceResponsibility,
## data = pavements)
##
## Residuals:
## Min 1Q Median 3Q Max
## -87.671 0.000 1.719 6.903 62.054
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 52.18637 10.21218
## RoadFunctionAccess Road 36.54569 10.18998
## RoadFunctionAlley 22.79735 10.19052
## RoadFunctionCollector 31.95531 10.18575
## RoadFunctionInterstate 35.95471 10.19574
## RoadFunctionLocal 30.93012 10.18161
## RoadFunctionMinor 30.70638 10.18419
## RoadFunctionOther Freeway and Expressway 37.25830 10.29283
## RoadFunctionPaper Street 3.86661 11.07698
## RoadFunctionPedestrian 20.15588 12.46888
## RoadFunctionPrincipal 32.62333 10.18670
## RoadFunctionROW 33.92146 10.37668
## RoadFunctionTBD 32.46676 10.18807
## OneWayYes -3.12969 0.39527
## MaintenanceResponsibilityBalcones Heights -22.95215 2.03948
## MaintenanceResponsibilityBexar County 0.89217 0.80595
## MaintenanceResponsibilityBrooks City Base -49.12254 1.58042
## MaintenanceResponsibilityBulverde 3.36818 3.76189
## MaintenanceResponsibilityCamp Bullis 2.80666 1.38544
## MaintenanceResponsibilityCamp Stanley 3.88448 1.40796
## MaintenanceResponsibilityCastle Hills 3.66431 1.40957
## MaintenanceResponsibilityChina Grove 3.88350 2.66504
## MaintenanceResponsibilityCibolo 3.88350 10.21126
## MaintenanceResponsibilityComal County 4.68776 1.68221
## MaintenanceResponsibilityConverse -0.09519 0.96811
## MaintenanceResponsibilityCOSA - Public Works Dept -9.59330 0.79370
## MaintenanceResponsibilityElmendorf 3.88350 1.61014
## MaintenanceResponsibilityFair Oaks Ranch 3.88350 1.22494
## MaintenanceResponsibilityFt Sam Houston 3.52975 1.00056
## MaintenanceResponsibilityGarden Ridge 3.88350 12.49370
## MaintenanceResponsibilityGrey Forest 3.88350 2.61598
## MaintenanceResponsibilityHelotes 3.69077 1.29645
## MaintenanceResponsibilityHill Country Village 3.75900 2.27977
## MaintenanceResponsibilityHollywood Park 3.22575 1.58378
## MaintenanceResponsibilityKendall County 3.88350 17.65107
## MaintenanceResponsibilityKirby -2.27378 1.28428
## MaintenanceResponsibilityLackland AFB 3.61436 1.13779
## MaintenanceResponsibilityLackland AFB Annex 3.88350 1.66850
## MaintenanceResponsibilityLeon Valley 3.02312 1.13983
## MaintenanceResponsibilityLive Oak 2.32454 1.04487
## MaintenanceResponsibilityLytle 3.88350 12.49370
## MaintenanceResponsibilityOlmos Park -6.20231 1.55935
## MaintenanceResponsibilityPort Authority of San Antonio -50.03728 1.25338
## MaintenanceResponsibilityPrivate 0.02984 0.86756
## MaintenanceResponsibilityPrivate - Gated Community 2.16433 0.81421
## MaintenanceResponsibilityProperty Owners 11.44261 0.97289
## MaintenanceResponsibilityRandolph AFB 3.87135 1.13913
## MaintenanceResponsibilitySandy Oaks 3.88350 1.48424
## MaintenanceResponsibilitySchertz 3.02452 1.65517
## MaintenanceResponsibilitySelma 3.86344 1.30503
## MaintenanceResponsibilityShavano Park 2.61344 1.64665
## MaintenanceResponsibilitySomerset 3.93392 1.67753
## MaintenanceResponsibilitySt. Hedwig 3.88350 2.20998
## MaintenanceResponsibilityTBD 2.34687 1.08111
## MaintenanceResponsibilityTerrell Hills 3.91628 1.33088
## MaintenanceResponsibilityTXDOT -1.79265 0.85314
## MaintenanceResponsibilityTXDOT_COSA - Public Works Dept -22.42373 17.65726
## MaintenanceResponsibilityUniversal City 3.65770 1.04443
## MaintenanceResponsibilityVon Ormy 3.88350 3.21580
## MaintenanceResponsibilityWindcrest -0.67112 1.19526
## t value Pr(>|t|)
## (Intercept) 5.110 3.22e-07 ***
## RoadFunctionAccess Road 3.586 0.000335 ***
## RoadFunctionAlley 2.237 0.025281 *
## RoadFunctionCollector 3.137 0.001706 **
## RoadFunctionInterstate 3.526 0.000421 ***
## RoadFunctionLocal 3.038 0.002383 **
## RoadFunctionMinor 3.015 0.002570 **
## RoadFunctionOther Freeway and Expressway 3.620 0.000295 ***
## RoadFunctionPaper Street 0.349 0.727039
## RoadFunctionPedestrian 1.616 0.105991
## RoadFunctionPrincipal 3.203 0.001363 **
## RoadFunctionROW 3.269 0.001080 **
## RoadFunctionTBD 3.187 0.001439 **
## OneWayYes -7.918 2.44e-15 ***
## MaintenanceResponsibilityBalcones Heights -11.254 < 2e-16 ***
## MaintenanceResponsibilityBexar County 1.107 0.268308
## MaintenanceResponsibilityBrooks City Base -31.082 < 2e-16 ***
## MaintenanceResponsibilityBulverde 0.895 0.370606
## MaintenanceResponsibilityCamp Bullis 2.026 0.042785 *
## MaintenanceResponsibilityCamp Stanley 2.759 0.005800 **
## MaintenanceResponsibilityCastle Hills 2.600 0.009335 **
## MaintenanceResponsibilityChina Grove 1.457 0.145064
## MaintenanceResponsibilityCibolo 0.380 0.703712
## MaintenanceResponsibilityComal County 2.787 0.005326 **
## MaintenanceResponsibilityConverse -0.098 0.921670
## MaintenanceResponsibilityCOSA - Public Works Dept -12.087 < 2e-16 ***
## MaintenanceResponsibilityElmendorf 2.412 0.015871 *
## MaintenanceResponsibilityFair Oaks Ranch 3.170 0.001523 **
## MaintenanceResponsibilityFt Sam Houston 3.528 0.000419 ***
## MaintenanceResponsibilityGarden Ridge 0.311 0.755925
## MaintenanceResponsibilityGrey Forest 1.485 0.137671
## MaintenanceResponsibilityHelotes 2.847 0.004417 **
## MaintenanceResponsibilityHill Country Village 1.649 0.099181 .
## MaintenanceResponsibilityHollywood Park 2.037 0.041678 *
## MaintenanceResponsibilityKendall County 0.220 0.825860
## MaintenanceResponsibilityKirby -1.770 0.076651 .
## MaintenanceResponsibilityLackland AFB 3.177 0.001490 **
## MaintenanceResponsibilityLackland AFB Annex 2.328 0.019938 *
## MaintenanceResponsibilityLeon Valley 2.652 0.007997 **
## MaintenanceResponsibilityLive Oak 2.225 0.026102 *
## MaintenanceResponsibilityLytle 0.311 0.755925
## MaintenanceResponsibilityOlmos Park -3.977 6.97e-05 ***
## MaintenanceResponsibilityPort Authority of San Antonio -39.922 < 2e-16 ***
## MaintenanceResponsibilityPrivate 0.034 0.972558
## MaintenanceResponsibilityPrivate - Gated Community 2.658 0.007858 **
## MaintenanceResponsibilityProperty Owners 11.762 < 2e-16 ***
## MaintenanceResponsibilityRandolph AFB 3.399 0.000678 ***
## MaintenanceResponsibilitySandy Oaks 2.616 0.008885 **
## MaintenanceResponsibilitySchertz 1.827 0.067656 .
## MaintenanceResponsibilitySelma 2.960 0.003073 **
## MaintenanceResponsibilityShavano Park 1.587 0.112487
## MaintenanceResponsibilitySomerset 2.345 0.019026 *
## MaintenanceResponsibilitySt. Hedwig 1.757 0.078877 .
## MaintenanceResponsibilityTBD 2.171 0.029949 *
## MaintenanceResponsibilityTerrell Hills 2.943 0.003255 **
## MaintenanceResponsibilityTXDOT -2.101 0.035623 *
## MaintenanceResponsibilityTXDOT_COSA - Public Works Dept -1.270 0.204108
## MaintenanceResponsibilityUniversal City 3.502 0.000462 ***
## MaintenanceResponsibilityVon Ormy 1.208 0.227191
## MaintenanceResponsibilityWindcrest -0.561 0.574472
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 17.63 on 97912 degrees of freedom
## Multiple R-squared: 0.1324, Adjusted R-squared: 0.1319
## F-statistic: 253.2 on 59 and 97912 DF, p-value: < 2.2e-16- interpret the model’s r-squared and p-values. How much of the dependent variable does the overall model explain? What are the significant variables? What are the insignificant variables?
The r-square of the model is 13%. That means the model only explains 13% of the relationship between the PCI and other variables in the data. The p-value is really small, 0.00000000000000022 (thats 15 0) so the model is significant and the data is not likely by chance. This means something in the relationship is causing the results. Evaluating the variables would allow for the researcher to identify the cause.
- Choose some significant independent variables. Interpret its Estimates (or Beta Coefficients). How do the independent variables individually affect the dependent variable?
Focusing in on the Maintenance Responsibility variable, there are many entities that have a significant impact on the dependent variable, PCI. Some of the greater one area Balcones Heights, Brooks City Base, COSA Public Works, Port Authority, and Property Owners. Being in the know of public works, COSA is assisting both the Port and Brooks with street bond projects in their area. Additionally, COSA has an initiative to improve the PCI in all 10 council districts to a PCI of 70 or great. This would support the idea that the maintenance responsibility plays a significant role in PCI.
- Does the model you create meet or violate the assumption of linearity? Show your work with “plot(x,which=1)” THis model violates the linearity assumption. The plot shows the red line to not be straight. This is the residual vs fitted line. The model will be inaccurate.
plot(pavements_model, which=1)