01:14:15

Importing Data in R

01:13:16

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

52:39

Data Transformation in R (Part 1/2)

54:51

Data Transformation in R (Part 2/2)

37:54

Data Visualization in R (Part 2/2)

42:25

Data Visualization in R (Part 1/2)

22:12

Introduction to R for Data Science

11:27

Creating a simple Quarto document

01:07:45

Modifying values in R

40:48

R Notation

49:55

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

40:31

Basics of R

16:24

9.6 Least Absolute Deviation and Quantile regression

09:31

9.5c Example of regressions with or without outliers

06:50

9.5c Outliers and Influential observations

14:28

9.5ab Nonrandom Sampling and Missing data

13:57

9.4b Measurement error in an explanatory variable

08:08

9.4a Measurement error in the dependent variable

07:04

9.2a Using Lagged dependent variables as proxy variables

06:17

9.2 Example of using a proxy variable

13:56

9.2 Using Proxy variables for unobserved explanatory variables

07:23

9.1b Tests against Nonnested Alternatives

05:43

9.1a RESET as a general test for Functional form misspecification

09:07

9.1 Functional form misspecification

07:29

8.5 Linear Probability Model and Heteroskedasticity

03:23

8.3c White test for Heteroskedasticity

04:18

8.3b Example of B-P test in R

10:21

8.3a Testing for Heteroskedasticity (B-P test)

06:00

8.2b Example with robust inference in R (F test)

07:00

8.2a Example with robust inference in R

14:36

8.2 Heteroskedasticity Robust inference after OLS

08:51

8.1 Consequences of Heteroskedasticity for OLS

06:08

8.0 Introduction to Heteroskedasticity

18:32

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

16:27

7.4b Interactions involving dummy variables: allowing for different slopes

10:38

7.5b Example of a linear probability model

08:23

7.6 Policy analysis and program evaluation

06:35

7.5a The Linear Probability model

06:04

7.7 Regression with discrete dependent variables

07:16

7.4a Interactions involving dummy variables

11:47

7.3 Using dummy variables for multiple categories

16:48

7.2 A Single Dummy Independent variable

16:10

7.3a Incorporating ordinal information using dummy variables

07:17

7.1 Describing Qualitative Information

04:24

7.0 Introduction to Regression analysis with Qualitative information

13:04

6.2c Regression model with Interaction terms

07:55

6.3 Goodness of fit and selection of regressors

16:29

6.2b Regression Model with Quadratic terms

16:56

6.2a Regression model with Logarithmic Functional forms

12:44

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

09:52

6.1a Beta coefficients or Standardized coefficients

30:03

4.5 Testing multiple Linear restrictions using the F test

06:19

4.4 Testing Hypotheses about a Single Linear Combination of the parameters

06:25

4.3 Confidence Intervals

12:48

4.2d p-Values for t-tests

07:30

4.2f Economic, Practical vs. Statistical significance

17:53

4.2a Examples of Testing against one sided alternatives

13:39

4.2b Two sided Alternatives

05:48

4.2c Example of testing hypotheses about population parameter equalling a constant

03:55

4.2c Testing hypotheses about population parameter equalling a constant