Dr. Venoo Kakar

6.1 Effects of Data Scaling on OLS statistics (changing units of measurement)

1.3d What are Panel Data or Longitudinal Data?

7.5b Example of a linear probability model

7.7 Regression with discrete dependent variables

9.2a Using Lagged dependent variables as proxy variables

7.3 Using dummy variables for multiple categories

6.3 Goodness of fit and selection of regressors

10.6 Numerical example on Real vs. Nominal GDP

8.2a Example with robust inference in R

Data Visualization in R (Part 1/2)

11.1c CPI components and measurement issues

9.2 Using Proxy variables for unobserved explanatory variables

R Notation

9.4b Measurement error in an explanatory variable

9.1b Tests against Nonnested Alternatives

Referencing in R Markdown (LaTeX style)

9.2 Example of using a proxy variable

9.4a Measurement error in the dependent variable

9.6 Least Absolute Deviation and Quantile regression

Data Transformation in R (Part 2/2)

Introduction to R for Data Science

R Objects: Vectors, Matrices, Arrays, Lists and Data Frames

Modifying values in R

9.5c Outliers and Influential observations

Data Transformation in R (Part 1/2)

The RStudio environment

9.5c Example of regressions with or without outliers

ARIMA models: Estimation and order selection (Part 6)

2.3 Time Series plots in R

Installing R and RStudio

Basics of R

4.3a Demand: Law of demand, demand schedule, and demand curve

Exponential Smoothing: Simple Exponential Smoothing (Part 2)

7.4a Interactions involving dummy variables

ARIMA models: application in R (Part 8)

Loading, Viewing, working with an R dataset (basics)

6.1a Beta coefficients or Standardized coefficients

7.4c Testing for differences in regression functions across groups: the Chow test or F-test

Exponential Smoothing: Introduction (Part 1)

Tidying Data in R using pivot_longer() and pivot_wider()

9.1 Functional form misspecification

Importing Data in R

9.5ab Nonrandom Sampling and Missing data

Data Visualization in R (Part 2/2)

Creating a simple Quarto document

6.1 Effects of Data Scaling on OLS statistics (changing units of measurement)

2.4 Lag Plots, Autocovariance, Autocorrelation and White Noise Processes in R

7.0 Introduction to Regression analysis with Qualitative information

ARIMA models: stationary vs. non stationary time series (Part 1.1)

9.1a RESET as a general test for Functional form misspecification

11.1b Calculating CPI and CPI inflation (example)