Glossary¶

All concepts tracked across the site. Click any keyword to see every occurrence with full context.

01. Introduction to RStudio¶

15 new

softwarerrstudiorstudio cloudgssr packagessteps of using rstudiocopy the coderstudio consolewaithighlighting and runningrstudio interfacefiles tabplots tabviewer tab

02. Introduction to data and scripting¶

27 new

terminologiessurvey terminologyquestionnairerespondentsdatadatasetdata terminologyquestion wordingvariable namevariable labelvaluevalue labelresponse categoryusing r script filesr script fileoutline viewcommentingsave r script fileworking spacepasting variable nameshow to work with codesmodel codeworking codefind this working code in the r script filekeyboard shortcutshand and finger positionsmouse shortcuts

03. Descriptive statistics¶

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variablecontent of the variabledemographic variablescontextual variablestypes of the variablecategoricalbinarynominalordinalcontinuoussummary statisticsfrequency tablebar graphdescriptive tablehistogram graphmeanstandard deviation

04. Recoding variables¶

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recodingreasons for recodingmerging valuesreversing valuestransforming continuous variables into groupscategoricalfrequency tablefrequency table for recoded variableordinalcontinuousdescriptive tablerecoding model codescommon recoding issues and troubleshootingdifferent recoding codes for different variablesuse the recoded (new) variable in analysesrecoded variables are always categoricaluse a model coderefresh gss data if variables are misplacedrun the recoding codes to create a new variable

05. Computing variables¶

7 new + 5 recurring

computingindex variablerecodingreversing valuescategoricalcontinuousdescriptive tabledescriptive table for index variablecommon computing issues and troubleshootinguse the new (recoded) variables in computing codecomputed variables are always continuousrun the computing codes to create a new variable

06. Chi-square analysis¶

8 new + 2 recurring

chi-squarecategoricalvariablefunctions of the variableoutcome variablefactor variablestatistical significancep-valueis my p-value less than 0.05?check asterisks

07. T-test analysis¶

1 new + 8 recurring

t-teststatistical significancep-valueis my p-value less than 0.05?factor variablebinaryoutcome variablecontinuousmerging values

08. Probabilistic sampling¶

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sampling conceptspopulationsamplesamplingrandomnessdescriptive tablesampling methodsnon-probability samplingnon-random samplingprobability samplingsimple random samplingsystematic random samplingdata creation

09. Visualization¶

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stacked bar graph for multiple variablescategoricalstacked bar graph by groupsfactor variableoutcome variable

10. Correlation analysis¶

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correlation analysisp-valuer-valuesignificance of correlationnonsignificant correlationsignificant correlationdirection of correlationpositive correlationnegative correlationstrength of correlationweak correlationmoderate correlationstrong correlationconfounding variablebivariate correlationcorrelation tablescatterplot graphmultivariate correlationcorrelation table matrixscatterplot graph matrix

11. Linear regression basics¶

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regressionfactor variableoutcome variablecorrelation analysistypes of regression modeling based on outcome variablelinear regressioncontinuouslogistic regressionbinarytypes of regression modeling based on modeling typeexplanatory modelingpredictive modelingdescriptive modelingcoefficientstandard errorstandardized coefficientp-valueadjusted r-squaredconfounding variablelinear regression interpretation specificsreporting of coefficientsunit of analysisreporting of standardized coefficientsreporting of adjusted r-squared

12. Dummy variables¶

3 new + 4 recurring

dummy variableomitting dummy variablecomparison dummy variablelinear regressionfactor variableoutcome variableadjusted r-squared

13. Logistic regression basics¶

3 new + 7 recurring

logistic regressionoutcome variablebinarydummy variableodds ratiostandard errorstandardized odds ratiop-valuetjur r-squaredfactor variable

14. Modeling exercises¶

0 new + 4 recurring

logistic regressionfactor variableoutcome variabletjur r-squared

15. Regression assumptions and diagnostics¶

11 new + 7 recurring

linear regression assumptionshomoscedasticityheteroscedasticitymulticollinearitylinearitycurvilinear relationshipnormal distributionnonnormal distribution10% of the casescomputingindex variablerecodingdummy variablelinear regressionperformance diagnosticvifscatterplot graph matrixfrequency table