Basics of probability and statisticsRandom variables and probability distributionsProperties of probabilitiesThe probability function - the discrete caseThe cumulative probability function - the discrete caseThe probability function - the continuous caseThe cumulative probability function - the continuous caseThe multivariate probability distribution functionCharacteristics of probability distributionsMeasures of central tendencyMeasures of dispersionMeasures of linear relationshipSkewness and kurtosisBasic probability distributions in econometricsThe normal distributionThe t-distributionThe Chi-square distributionThe F-distributionThe simple regression modelThe population regression modelThe economic modelThe econometric modelThe assumptions of the simple regression modelEstimation of population parametersThe method of ordinary least squaresProperties of the least squares estimatorStatistical inferenceHypothesis testingConfidence intervalP-value in hypothesis testingType I and type II errorsThe best linear predictorModel MeasuresThe coefficient of determination (R2)The adjusted coefficient of determination (Adjusted R2)The analysis of variance table (ANOVA)The multiple regression modelPartial marginal effectsEstimation of partial regression coefficientsThe joint hypothesis testTesting a subset of coefficientsTesting the regression equationSpecificationChoosing the functional formThe linear specificationThe log-linear specificationThe linear-log specificationThe log-log specificationOmission of a relevant variableInclusion of an irrelevant variableMeasurement errorsDummy variablesIntercept dummy variablesSlope dummy variablesA model will intercept and slope dummy variableQualitative variables with several categoriesPiecewise linear regressionTest for structural differencesHeteroskedasticity and diagnosticsConsequences of using OLSDetecting heteroskedasticityGraphical methodsStatistical testsRemedial measuresHeteroskedasticity-robust standard errorsAutocorrelation and diagnosticsDefinition and the nature of autocorrelationConsequencesDetection of autocorrelationThe Durbin Watson testThe Durbins h test statisticThe LM-testRemedial measuresGLS when AR(1)GLS when AR(2)Multicollinearity and diagnosticsConsequencesMeasuring the degree of multicollinearityRemedial measuresSimultaneous equation modelsIntroductionThe structural and reduced form equationIdentificationThe order condition of identificationThe rank condition of identificationEstimation methodsIndirect Least Squares (ILS)Two Stage Least Squares (2SLS)
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