Credits: 3 (3-0-0)
Overlaps with: MSL721, HUL315/HUL719
Description
Probability and statistics Basics (Random variables, Population and sample, Parameters and Estimates, Normal distribution, Sampling distributions of estimates, Confidence intervals); Hypothesis testing (z-test, t-tests, chi square tests, p-values, comparison of means tests); Bivariate linear regression model; Multivariate regression model (Gauss Markov Theorem, Inference and Prediction, ANOVA); Model Specification Errors (Omitted Variables, Irrelevant Variables); Dealing with real-world issues (Multicollinearity, Heteroskedasticity, Outliers); Categorical variables in linear regression (Dummy Variables, Logit/ Probit models); Introduction to Time Series Analysis; Introduction to Panel Data Analysis; Correlation vs Causation.