scoopuf.blogg.se

5.6 Using the t-Statistic in Regression When the Sample Size Is Small.Computation of Heteroskedasticity-Robust Standard Errors.Should We Care About Heteroskedasticity?.A Real-World Example for Heteroskedasticity.5.4 Heteroskedasticity and Homoskedasticity.5.3 Regression when X is a Binary Variable.5.2 Confidence Intervals for Regression Coefficients.5.1 Testing Two-Sided Hypotheses Concerning the Slope Coefficient.5 Hypothesis Tests and Confidence Intervals in the Simple Linear Regression Model.4.5 The Sampling Distribution of the OLS Estimator.Assumption 3: Large Outliers are Unlikely.Assumption 2: Independently and Identically Distributed Data.Assumption 1: The Error Term has Conditional Mean of Zero.4.2 Estimating the Coefficients of the Linear Regression Model.3.7 Scatterplots, Sample Covariance and Sample Correlation.3.6 An Application to the Gender Gap of Earnings.3.5 Comparing Means from Different Populations.3.4 Confidence Intervals for the Population Mean.Hypothesis Testing with a Prespecified Significance Level.Calculating the p-value When the Standard Deviation is Unknown.Sample Variance, Sample Standard Deviation and Standard Error.Calculating the p-Value when the Standard Deviation is Known.3.3 Hypothesis Tests Concerning the Population Mean.Large Sample Approximations to Sampling Distributions.