The 5 Basic Statistics Concepts Data Scientists Need to Know · Statistical Features · Probability Distributions · Dimensionality Reduction · Over and Under Sampling.GetstartedOpeninappSigninGetstartedFollow551KFollowers·Editors'PicksFeaturesDeepDivesGrowContributeAboutGetstartedOpeninappThe5BasicStatisticsConceptsDataScientistsNeedtoKnowGeorgeSeifOct22,2018·9minreadIrecentlystartedabook-focusededucationalnewsletter.BookDivesisabi-weeklynewsletterwhereforeachnewissuewediveintoanon-fictionbook.You’lllearnaboutthebook’scorelessonsandhowtoapplytheminreallife.Youcansubscribeforithere.StatisticscanbeapowerfultoolwhenperformingtheartofDataScience(DS).Fromahigh-levelview,statisticsistheuseofmathematicstoperformtechnicalanalysisofdata.Abasicvisualisationsuchasabarchartmightgiveyousomehigh-levelinformation,butwithstatisticswegettooperateonthedatainamuchmoreinformation-drivenandtargetedway.Themathinvolvedhelpsusformconcreteconclusionsaboutourdataratherthanjustguesstimating.Usingstatistics,wecangaindeeperandmorefinegrainedinsightsintohowexactlyourdataisstructuredandbasedonthatstructurehowwecanoptimallyapplyotherdatasciencetechniquestogetevenmoreinformation.Today,we’regoingtolookat5basicstatisticsconceptsthatdatascientistsneedtoknowandhowtheycanbeappliedmosteffectively!Justbeforewejumpin,checkouttheAISmartNewslettertoreadthelatestandgreatestonAI,MachineLearning,andDataScience!StatisticalFeaturesStatisticalfeaturesisprobablythemostusedstatisticsconceptindatascience.It’softenthefirststatstechniqueyouwouldapplywhenexploringadatasetandincludesthingslikebias,variance,mean,median,percentiles,andmanyothers.It’sallfairlyeasytounderstandandimplementincode!Checkoutthegraphicbelowforanillustration.AbasicboxplotThelineinthemiddleisthemedianvalueofthedata.Medianisusedoverthemeansinceitismorerobusttooutliervalues.Thefirstquartileisessentiallythe25thpercentile;i.e25%ofthepointsinthedatafallbelowthatvalue.Thethirdquartileisthe75thpercentile;i.e75%ofthepointsinthedatafallbelowthatvalue.Theminand

The 8 Basic Statistics Concepts for Data Science · Understand the Type of Analytics · Probability · Central Tendency · Variability · Relationship Between Variables ...KDnuggetsSubscribetoKDnuggets       SubmitablogWinaReward! SubmitablogtoKDnuggets--TopBlogsWinARewardTopics:AI|DataScience|DataVisualization|DeepLearning|MachineLearning|NLP|Python|R|StatisticsKDnuggetsHome»News»2020»Jun»Tutorials,Overviews»The8BasicStatisticsConceptsforDataScience( 20:n26 )The8BasicStatisticsConceptsforDataScience<=PreviouspostNextpost=>  Tags:Beginners,Causation,Correlation,LinearRegression,Probability,StatisticsUnderstandingthefundamentalsofstatisticsisacorecapabilityforbecomingaDataScientist.Reviewtheseessentialideasthatwillbepervasiveinyourworkandraiseyourexpertiseinthefield.commentsByShirleyChen,MSBAinASU|DataAnalyst.Statisticsisaformofmathematicalanalysisthatusesquantifiedmodelsandrepresentationsforagivensetofexperimentaldataorreal-lifestudies.Themainadvantageofstatisticsisthatinformationispresentedinaneasyway.Recently,Ireviewedallthestatisticsmaterialsandorganizedthe8basicstatisticsconceptsforbecomingadatascientist!UnderstandtheTypeofAnalyticsProbabilityCentralTendencyVariabilityRelationshipBetweenVariablesProbabilityDistributionHypothesisTestingandStatisticalSignificanceRegression UnderstandtheTypeofAnalytics DescriptiveAnalytics tellsuswhathappenedinthepastandhelpsabusinessunderstandhowitisperformingbyprovidingcontexttohelpstakeholdersinterpretinformation.DiagnosticAnalytics takesdescriptivedataastepfurtherandhelpsyouunderstandwhysomethinghappenedinthepast.PredictiveAnalytics predictswhatismostlikelytohappeninthefutureandprovidescompanieswithactionableinsightsbasedontheinformation.PrescriptiveAnalytics providesrecommendationsregardingactionsthatwilltakeadvantageofthepredictionsandguidethepossibleactionstowardasolution. Probability Probability isthemeasureofthelikelihoodthataneventwilloccurinaRandomExperiment.Complement:P(A)+P(A’)=1Intersection:P(A∩B)=P(A)P(B)Union:P(A∪B)=P(A)

Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and ... The basic steps of a statistical experiment are: Planning the​ ...StatisticsFromWikipedia,thefreeencyclopediaJumptonavigationJumptosearchStudyofthecollection,analysis,interpretation,andpresentationofdataForotheruses,seeStatistics(disambiguation).StatisticsOutlineStatisticiansGlossaryNotationJournalsListsoftopicsArticlesCategory MathematicsportalvteThenormaldistribution,averycommonprobabilitydensity,usefulbecauseofthecentrallimittheorem.Scatterplotsareusedindescriptivestatisticstoshowtheobservedrelationshipsbetweendifferentvariables,hereusingtheIrisflowerdataset.Statisticsisthedisciplinethatconcernsthecollection,organization,analysis,interpretation,andpresentationofdata.[1][2][3]Inapplyingstatisticstoascientific,industrial,orsocialproblem,itisconventionaltobeginwithastatisticalpopulationorastatisticalmodeltobestudied.Populationscanbediversegroupsofpeopleorobjectssuchas"allpeoplelivinginacountry"or"everyatomcomposingacrystal".Statisticsdealswitheveryaspectofdata,includingtheplanningofdatacollectionintermsofthedesignofsurveysandexperiments.[4]Whencensusdatacannotbecollected,statisticianscollectdatabydevelopingspecificexperimentdesignsandsurveysamples.Representativesamplingassuresthatinferencesandconclusionscanreasonablyextendfromthesampletothepopulationasawhole.Anexperimentalstudyinvolvestakingmeasurementsofthesystemunderstudy,manipulatingthesystem,andthentakingadditionalmeasurementsusingthesameproceduretodetermineifthemanipulationhasmodifiedthevaluesofthemeasurements.Incontrast,anobservationalstudydoesnotinvolveexperimentalmanipulation.Twomainstatisticalmethodsareusedindataanalysis:descriptivestatistics,whichsummarizedatafromasampleusingindexessuchasthemeanorstandarddeviation,andinferentialstatistics,whichdrawconclusionsfromdatathataresubjecttorandomvariation(e.g.,observationalerrors,samplingvariation).[5]Descriptivestatisticsaremostoftenconcernedwithtwosetsofpro

ShareonAbargraphsdisplaysdataincategories.Whenyoufirststartastatisticsclass,you’llbepresentedwiththebasics.Someoftheterms,likebargraphsandlinegraphs,you’llprobablybefamiliarwithfromgradeschoolmathclasses.Otherterms,(likeinterquartilerange)mightbenewtoyou.Thissitehasacomprehensiverangeofarticlescoveringstatisticsbasics.Mostofthearticleshavevideosattached(youcanalwayscheckoutourYouTubechannelforthecompletelistofhundredsofvideos).BasicStatisticsArticlesNeedhelpwithahomeworkquestion?Checkoutourtutoringpage!InterquartileRange:HowtoFindit.DiscreteVariablevsContinuousVariables.HowtoFindaRange.HowtoDetectFakeStatistics.HowtoFindaFiveNumberSummary.HowtoTelltheDifferenceBetweenDifferentSamplingMethods.HowtoFindtheSampleStandardDeviation.HowtoFindthecoefficientofvariation.HowtoFindOutliers.HowtoClassifyaVariableasQuantitativeorQualitative.HowtoFindthePooledSampleStandardError.HowtoTelltheDifferenceBetweenaStatisticandaParameter.HowtoFindtheSampleMean.TypesofVariablesAPStatisticsFormulas.WhatistheCenterofaDistribution?Howtofindthesamplevariance.RegressiontotheMean.HowtoCalculateExpectedValueSignificantDigitsandRoundinginStatistics.Howtofindthemeanmodeandmedian.StatisticsBasics:ChartsandGraphsHowtoMakeaHistogram.HowtomakeaRelativeFrequencyHistogram.HowtoMakeaFrequencyChartandDetermineFrequency.HowtoChooseBinSizesinStatistics.HowtoReadaBoxPlot.HowtoFindaBoxPlotInterquartileRange.HowtoDrawaFrequencyDistributionTable.HowtoMakeaCumulativeFrequencyDistributionTable.HowtoMakeaStemplot.ExcelHowtoFindtheModeinExcel2013.HowtoFindtheMeaninExcel.HowtoFindtheStandardDeviationinExcel.HowtoFindanInterquartileRangeinExcel.HowtoFinda5NumberSummaryinExcel.StatisticsBasics:DefinitionsWhatisanAverage?WhatisanAbsoluteValue?WhatisBiasinStatistics?WhatareCategoricalVariables?WhatisaCensus?WhatisaContinuousVariable?WhatisaDependentEvent?WhatisaDiscreteVariable?WhatisElementaryStatistics?WhatareOutliers?WhatisaParameter?WhatareQuantitativeVariables?WhatisSampleVariance?WhatisStandardDeviation?Statistic

Basic Statistics · Cases, Variables, Types of Variables · Matrix and Frequency Table · Graphs and Shapes of Distributions · Mode, Median and Mean · Range, ...SkiptocontentBasicStatisticsforDataAnalysisWhyStatistics?Statisticalmethodsaremainlyusefultoensurethatyourdataareinterpretedcorrectly.Andthatapparentrelationshipsarereally“significant”ormeaningfulanditisnotsimplyhappenbychance.Actually, thestatisticalanalysishelpstofindmeaningtothemeaninglessnumbers.So,a“statistic”isnothingbutsomenumericalvaluetothatcandescribecertainpropertyofyourdataset.Therearefewwellknowstatisticsaretheaverage(or“mean”)value,andthe“standarddeviation”etc.Standarddeviationisthevariabilitywithinadatasetaroundthemeanvalue.The“variance”isthesquareofthestandarddeviation.Thelineartrendisanotherexampleofadata“statistic”.StepsintheDataAnalysisProcessBeforestaringDataAnalysispipelineyoushouldknowtherearemainlyfivestepsinvolvedintoit. Step1:Decideontheobjectivesor PoseaQuestionThefirststepofthedataanalysispipelineistodecideonobjectives.Theseobjectivesmayusuallyrequiresignificantdatacollectionandanalysis.Step2:WhattoMeasureandHowtoMeasuresMeasurementgenerallyreferstotheassigningofnumberstoindicatedifferentvaluesofvariables.Suppose,throughyourresearchyouaretryingtofind iftherewasarelationshipbetweenheight andweightofhuman,it wouldmakesensetomeasuretheheightandweightofdogs usingascale. Step3:DataCollectionOnceyouknowwhattypesofdatayouneedforyourstatisticalstudythenyoucandeterminewhetheryourdatacanbegatheredfromexistingsources/databasesornot.Ifdataisnotsufficienttheyouhavetocollectnewdata. Evenifyouhaveexistingdata,itisveryimportanttoknowhowthedatawascollected?Thiswillhelpsyoutounderstandyoucadeterminethelimitationsofthegeneralizabilityofresultsandconductaproperanalysis. Themoredatayouhave,themorebettercorrelations,buildingbettermodelsandfindingmoreactionableinsightsiseasyforyou.Especiallydatafrommorediversesourceshelpstodothisjobeasierway.Step4:DataCleaningThisisanothercrucialstepindataanalysispipelineis

This unit covers the basics to statistics, from basic terms and definitions in Chapter 1, to the location and spread of a distribution of data in Chapters 4 and 5,​ ...FundamentalStatisticsSearchthissiteNavigationHomeForewardAbouttheAuthorAcknowledgementsUnit1:TheFundamentalsofStatisticsChapter1:IntroductiontoStatisticsChapter2:FrequencyDistributionsandGraphingChapter3:RankingsinaDistributionChapter4:CentralTendencyChapter5:VariabilityChapter6:StandardScoresChapter7:EstimationandSamplingDistributionsChapter8:ProbabilityUnit2:IntroductiontoHypothesisTestingChapter9:BinomialProbabilityChapter10:IntroductiontoHypothesisTestingChapter11:oneSamplet-testUnit3:BivariateRelationshipsChapter12:BivariateDesignsChapter13:IndependentGroupst-TestChapter14:PairedSamplest-TestChapter15:CorrelationChapter16:RegressionChapter17:IntroductiontoAnalysisofVarianceChapter18:OnewayANOVAUnit4:AdvancedHypothesisTestingandTopicsChapter19:FactorialANOVAChapter20:Chi-SquareChapter21:PowerAnalysisAppendixA:StatisticalTablesTable1(z-Tables)Table2(t-Tables)Table3A(F,df=1)Table3B(F,df=2)Table3C(F,df=3)Table3D(F,df=4)Table3E(F,df=5)Table3F(F,df=10)Table4(StudentizedRange,q))Table5(Chi-Square)Table6(Fisher'srtor')Table7(Factorials)AppendixB:MathReviewAppendixC:MeasuringSkewAppendixD:PowerCalculationsAppendixE:PostHoct-TestingAppendixF:AnswerstoProblemsReferencesUnit1:TheFundamentalsofStatisticsThisunitcoversthebasicstostatistics,frombasictermsanddefinitionsinChapter1,tothelocationandspreadofa distribution ofdatainChapters4and 5,estimatingpopulationparametersfromsamplesinChapter7,andcalculatingprobabilitiesinChapter8.Chapter1: Introducesbasictermsanddefinitionsanddiscusseshowandwhenstatisticsareusedinresearchandreal-life.Chapter2:Coversoneofthebasicusesofstatistics,whichisorganizingrawdatainto something simplerandmoreusefulandunderstandablebycreatingafrequencydistribution.Thischapteralsointroduces howtograph statistical information.Chapter3:Discusseshowtofindwhereascorestandsor'ranks'withindistributi

In general, statistics is a study of data: describing properties of the data, which is called descriptive statistics, and drawing conclusions about a ...SkiptomaincontentContributorLearningObjectivesTolearnthebasicdefinitionsusedinstatisticsandsomeofitskeyconcepts.Webeginwithasimpleexample.TherearemillionsofpassengerautomobilesintheUnitedStates.Whatistheiraveragevalue?Itisobviouslyimpracticaltoattempttosolvethisproblemdirectlybyassessingthevalueofeverysinglecarinthecountry,addupallthosevalues,thendividebythenumberofvalues,oneforeachcar.Inpracticethebestwecandowouldbetoestimatetheaveragevalue.Anaturalwaytodosowouldbetorandomlyselectsomeofthecars,say\(200\)ofthem,ascertainthevalueofeachofthosecars,andfindtheaverageofthose\(200\)values.Thesetofallthosemillionsofvehiclesiscalledthepopulationofinterest,andthenumberattachedtoeachone,itsvalue,isameasurement.Theaveragevalueisaparameter:anumberthatdescribesacharacteristicofthepopulation,inthiscasemonetaryworth.Thesetof\(200\)carsselectedfromthepopulationiscalledasample,andthe\(200\)numbers,themonetaryvaluesofthecarsweselected,arethesampledata.Theaverageofthedataiscalledastatistic:anumbercalculatedfromthesampledata.Thisexampleillustratesthemeaningofthefollowingdefinitions.Definitions:populationsandsamplesApopulationisanyspecificcollectionofobjectsofinterest.Asampleisanysubsetorsubcollectionofthepopulation,includingthecasethatthesampleconsistsofthewholepopulation,inwhichcaseitistermedacensus.Definitions:measurementsandSampleDataAmeasurementisanumberorattributecomputedforeachmemberofapopulationorofasample.Themeasurementsofsampleelementsarecollectivelycalledthesampledata.Definition:parametersAparameterisanumberthatsummarizessomeaspectofthepopulationasawhole.Astatisticisanumbercomputedfromthesampledata.Continuingwithourexample,iftheaveragevalueofthecarsinoursamplewas\($8,357\),thenitseemsreasonabletoconcludethattheaveragevalueofallcarsisabout\($8,357\).Inreasoningthiswaywehavedrawnaninferenceaboutthepopulationbasedoninformationob

Offered by University of Amsterdam. Understanding statistics is essential to understand research in the social and behavioral sciences. In ... Enroll for free.ListBrowseDataScienceProbabilityandStatisticsThiscourseispartoftheMethodsandStatisticsinSocialSciencesSpecializationBasicStatisticsFilledStarFilledStarFilledStarFilledStarHalfFadedStar4.6stars3,825ratings|ThumbsUp96%MatthijsRooduijn+1moreinstructor  EnrollforFreeStartsJun23233,733alreadyenrolledOfferedByAboutInstructorsSyllabusReviewsEnrollmentOptionsFAQMethodsandStatisticsinSocialSciencesSpecializationUniversityofAmsterdamAboutInstructorsSyllabusReviewsEnrollmentOptionsFAQAboutthisCourse224,848recentviewsUnderstandingstatisticsisessentialtounderstandresearchinthesocialandbehavioralsciences.Inthiscourseyouwilllearnthebasicsofstatistics;notjusthowtocalculatethem,butalsohowtoevaluatethem.Thiscoursewillalsoprepareyouforthenextcourseinthespecialization-thecourseInferentialStatistics.Inthefirstpartofthecoursewewilldiscussmethodsofdescriptivestatistics.Youwilllearnwhatcasesandvariablesareandhowyoucancomputemeasuresofcentraltendency(mean,medianandmode)anddispersion(standarddeviationandvariance).Next,wediscusshowtoassessrelationshipsbetweenvariables,andweintroducetheconceptscorrelationandregression.Thesecondpartofthecourseisconcernedwiththebasicsofprobability:calculatingprobabilities,probabilitydistributionsandsamplingdistributions.Youneedtoknowaboutthesethingsinordertounderstandhowinferentialstatisticswork.Thethirdpartofthecourseconsistsofanintroductiontomethodsofinferentialstatistics-methodsthathelpusdecidewhetherthepatternsweseeinourdataarestrongenoughtodrawconclusionsabouttheunderlyingpopulationweareinterestedin.Wewilldiscussconfidenceintervalsandsignificancetests.Youwillnotonlylearnaboutallthesestatisticalconcepts,youwillalsobetrainedtocalculateandgeneratethesestatisticsyourselfusingfreelyavailablestatisticalsoftware.UserLearnerCareerOutcomesCareerdirection38%startedanewcareeraftercompletingthesecoursesCareerBene

Learn statistics and probability for free—everything you'd want to know about descriptive and inferential statistics. Full curriculum of exercises and videos.Ifyou'reseeingthismessage,itmeanswe'rehavingtroubleloadingexternalresourcesonourwebsite.Ifyou'rebehindawebfilter,pleasemakesurethatthedomains*.kastatic.organd*.kasandbox.orgareunblocked.CoursesSearchDonateLoginSignupSearchforcourses,skills,andvideosMaincontentMathStatisticsandprobabilityMathStatisticsandprobabilityCoursesummaryAnalyzingcategoricaldataAnalyzingonecategoricalvariable:AnalyzingcategoricaldataTwo-waytables:AnalyzingcategoricaldataDistributionsintwo-waytables:AnalyzingcategoricaldataDisplayingandcomparingquantitativedataDisplayingquantitativedatawithgraphs:DisplayingandcomparingquantitativedataDescribingandcomparingdistributions:DisplayingandcomparingquantitativedataMoreondatadisplays:DisplayingandcomparingquantitativedataSummarizingquantitativedataMeasuringcenterinquantitativedata:SummarizingquantitativedataMoreonmeanandmedian:SummarizingquantitativedataInterquartilerange(IQR):SummarizingquantitativedataVarianceandstandarddeviationofapopulation:SummarizingquantitativedataVarianceandstandarddeviationofasample:SummarizingquantitativedataMoreonstandarddeviation:SummarizingquantitativedataBoxandwhiskerplots:SummarizingquantitativedataOthermeasuresofspread:SummarizingquantitativedataModelingdatadistributionsPercentiles:ModelingdatadistributionsZ-scores:ModelingdatadistributionsEffectsoflineartransformations:ModelingdatadistributionsDensitycurves:ModelingdatadistributionsNormaldistributionsandtheempiricalrule:ModelingdatadistributionsNormaldistributioncalculations:ModelingdatadistributionsMoreonnormaldistributions:ModelingdatadistributionsExploringbivariatenumericaldataIntroductiontoscatterplots:ExploringbivariatenumericaldataCorrelationcoefficients:ExploringbivariatenumericaldataIntroductiontotrendlines:ExploringbivariatenumericaldataLeast-squaresregressionequations:ExploringbivariatenumericaldataAssess