Lecture 1 - Introduction to Statistics
Lecture 2 - Introduction to Econometrics
Lecture 3 - Organization and Presentation of Data
Lecture 4 - Summarizing Data through Descriptive Statistics
Lecture 5 - Discrete Random Variable and Probability Distribution
Lecture 6 - Continuous Random Variables and Probability Distribution
Lecture 7 - Normal Distribution
Lecture 8 - Introduction to Statistical Inference
Lecture 9 - Estimation - Part I
Lecture 10 - Estimation - Part II
Lecture 11 - Hypothesis Testing - Part I
Lecture 12 - Hypothesis Testing - Part II
Lecture 13 - Hypothesis Testing - Part III
Lecture 14 - Hypothesis Testing - Part IV
Lecture 15 - Relationship between Qualitative Variables
Lecture 16 - Relationship Between Quantitative Variables
Lecture 17 - Analysis of Variance
Lecture 18 - One Way ANOVA
Lecture 19 - Two Way ANOVA
Lecture 20 - Analysis of Covariance
Lecture 21 - Index Numbers - Part I
Lecture 22 - Index Numbers - Part II
Lecture 23 - Classical Time Series Analysis - Part I
Lecture 24 - Classical Time Series Analysis - Part II
Lecture 25 - Classical Linear Regression Model - Part I
Lecture 26 - Classical Linear Regression Model - Part II
Lecture 27 - Classical Linear Regression Model
Lecture 28 - Hypothesis Testing with CNLRM
Lecture 29 - More on Hypothesis Testing and Model Specification
Lecture 30 - Violations of CLRM Assumptions (Heteroskedasticity)
Lecture 31 - Violations of CLRM Assumptions (Autocorrelation and Multicollinearity)
Lecture 32 - Time Series Regression with Stationary Data
Lecture 33 - Time Series Regression with Non-Stationary Data
Lecture 34 - Regression with Dummy Explanatory Variable
Lecture 35 - Dummy Dependent Variable Models - Part I
Lecture 36 - Dummy Dependent Variable Models - Part II
Lecture 37 - Simultaneous Equations Model
Lecture 38 - Panel Data Regression
Lecture 39 - Program Evaluation
Lecture 40 - Data Analysis and Regression with R
Lecture 41 - Regression Involving Dummy Variables in R
Lecture 42 - Time Series Analysis in R
