Learn · Applied Statistics and Econometrics
Lecture 25 of 42Week 7: Classical Linear Regression
Lecture 25: Classical Linear Regression Model (Part-I)
Prof. Deep Mukherjee · IIT Kanpur
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- Applied Statistics and Econometrics, IIT Kanpur (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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All the lectures
- Lecture 1: Introduction to Statistics
- Lecture 2: Introduction to Econometrics
- Lecture 3: Organization & Presentation of Data
- Lecture 4: Summarizing Data through Descriptive Statistics
- Lecture 5: Discrete Random Variable & Probability Distribution
- Lecture 6: Continuous Random Variables & 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 Number (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 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
- Live Session 10-02-2024