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WorldHappinessReport2019

WorldHappinessReport2019

active ARFF CC0PublicDomain Visibility: public Uploaded 23-03-2022 by Lowe
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ThedatahasbeenreleasedbySDSNandextractedbyPromptCloudscustomwebcrawlingsolutionContextTheWorldHappinessReportisalandmarksurveyofthestateofglobalhappinessthatranks156countriesbyhowhappytheircitizensperceivethemselvestobeThisyearsWorldHappinessReportfocusesonhappinessandthecommunityhowhappinesshasevolvedoverthepastdozenyearswithafocusonthetechnologiessocialnormsconflictsandgovernmentpoliciesthathavedriventhosechangesContentWhatisDystopiaDystopiaisanimaginarycountrythathastheworldsleasthappypeopleThepurposeinestablishingDystopiaistohaveabenchmarkagainstwhichallcountriescanbefavorablycomparednocountryperformsmorepoorlythanDystopiaintermsofeachofthesixkeyvariablesthusallowingeachsubbartobeofpositiveorzeroinsixinstanceswidthThelowestscoresobservedforthesixkeyvariablesthereforecharacterizeDystopiaSincelifewouldbeveryunpleasantinacountrywiththeworldslowestincomeslowestlifeexpectancylowestgenerositymostcorruptionleastfreedomandleastsocialsupportitisreferredtoasDystopiaincontrasttoUtopiaWhataretheresidualsTheresidualsorunexplainedcomponentsdifferforeachcountryreflectingtheextenttowhichthesixvariableseitheroverorunderexplainaverage20162018lifeevaluationsTheseresidualshaveanaveragevalueofapproximatelyzerooverthewholesetofcountriesFigure27showstheaverageresidualforeachcountryiftheequationinTable21isappliedtoaverage20162018dataforthesixvariablesinthatcountryWecombinetheseresidualswiththeestimateforlifeevaluationsinDystopiasothatthecombinedbarwillalwayshavepositivevaluesAscanbeseeninFigure27althoughsomelifeevaluationresidualsarequitelargeoccasionallyexceedingonepointonthescalefrom0to10theyarealwaysmuchsmallerthanthecalculatedvalueinDystopiawheretheaveragelifeisratedat188onthe0to10scaleTable7oftheonlineStatisticalAppendix1forChapter2putstheDystopiaplusresidualblockattheleftsideandalsodrawstheDystopialinemakingiteasytocomparethesignsandsizesoftheresidualsindifferentcountriesWhydoweusethesesixfactorstoexplainlifeevaluationsThevariablesusedreflectwhathasbeenbroadlyfoundintheresearchliteraturetobeimportantinexplainingnationalleveldifferencesinlifeevaluationsSomeimportantvariablessuchasunemploymentorinequalitydonotappearbecausecomparableinternationaldataarenotyetavailableforthefullsampleofcountriesThevariablesareintendedtoillustrateimportantlinesofcorrelationratherthantoreflectcleancausalestimatessincesomeofthedataaredrawnfromthesamesurveysourcessomearecorrelatedwitheachotherorwithotherimportantfactorsforwhichwedonothavemeasuresandinseveralinstancestherearelikelytobetwowayrelationsbetweenlifeevaluationsandthechosenvariablesforexamplehealthypeopleareoverallhappierbutasChapter4intheWorldHappinessReport2013demonstratedhappierpeopleareoverallhealthierInStatisticalAppendix1ofWorldHappinessReport2018weassessedthepossibleimportanceofusingexplanatorydatafromthesamepeoplewhoselifeevaluationsarebeingexplainedWedidthisbyrandomlydividingthesamplesintotwogroupsandusingtheaveragevaluesforegfreedomgleanedfromonegrouptoexplainthelifeevaluationsoftheothergroupThisloweredtheeffectsbutonlyveryslightlyeg2to3assuringusthatusingdatafromthesameindividualsisnotseriouslyaffectingtheresultsDatasourcehttpworldhappinessreported2019MoresuchdatasetscanbedownloadedfromDataStock

13 features

Modelstring1038 unique values
0 missing
Release_datenumeric14 unique values
0 missing
Max_resolutionnumeric99 unique values
0 missing
Low_resolutionnumeric70 unique values
0 missing
Effective_pixelsnumeric16 unique values
0 missing
Zoom_wide_(W)numeric25 unique values
0 missing
Zoom_tele_(T)numeric100 unique values
0 missing
Normal_focus_rangenumeric32 unique values
0 missing
Macro_focus_rangenumeric29 unique values
1 missing
Storage_includednumeric44 unique values
2 missing
Weight_(inc._batteries)numeric237 unique values
2 missing
Dimensionsnumeric101 unique values
2 missing
Pricenumeric43 unique values
0 missing
Show all 13 features

19 properties

NumberOfInstances
1038
Number of instances (rows) of the dataset.
NumberOfFeatures
13
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
7
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
2
Number of instances with at least one value missing.
NumberOfNumericFeatures
12
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfNumericFeatures
92.31
Percentage of numeric attributes.
PercentageOfMissingValues
0.05
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0.19
Percentage of instances having missing values.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
NumberOfBinaryFeatures
0
Number of binary attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
Dimensionality
0.01
Number of attributes divided by the number of instances.
Show all 19 properties

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