About this course
Drop-in Sessions
1
Introduction to Quantitative Analysis
1.1
Seminar
1.1.1
Getting Started
1.1.2
RStudio
1.1.3
Courseware Setup
1.1.4
Console
1.1.5
Functions
1.1.6
Getting Help
1.1.7
The Assignment Operator
1.1.8
Sequences
1.1.9
Scripts
1.1.10
data frames
1.1.11
Plots
1.1.12
Exercises
1.2
Solutions
1.2.1
Exercise 3)
1.2.2
Exercise 4)
1.2.3
Exercise 5)
1.2.4
Exercise 6)
1.2.5
Exercise 7)
1.2.6
Exercise 8)
1.2.7
Exercise 9)
1.2.8
Exercise 10)
1.2.9
Exercise 11)
2
Descriptive Statistics
2.1
Seminar
2.1.1
Loading data
2.1.2
Central Tendency
2.1.3
Factor Variables
2.1.4
Dispersion
2.1.5
Visualizing Data
2.1.6
Additional Resources
2.1.7
Exercises
2.2
Solutions
2.2.1
Exercise 2
2.2.2
Exercise 3
2.2.3
Exercise 4
2.2.4
Exercise 5
2.2.5
Exercise 6
2.2.6
Exercise 7
2.2.7
Exercise 8
2.2.8
Exercise 9
2.2.9
Exercise 10
2.2.10
Exercise 11
2.2.11
Exercise 12
2.2.12
Exercise 13
3
T-test for Difference in Means and Hypothesis Testing
3.1
Seminar
3.1.1
Loading Dataset in CSV Format
3.1.2
T-test (one sample hypothesis test)
3.1.3
T-test (difference in means)
3.1.4
Exercises
3.1.5
Optional Exercises that require reading Extra Info below
3.1.6
Advanced Exercises
3.1.7
Extra Info
3.2
Solutions
3.2.1
Optional Exercises that require reading Extra Info below
3.2.2
Advanced Exercises
4
Bivariate linear regression models
4.1
Seminar
4.1.1
Packages
4.1.2
Fitted values
4.1.3
Additional Resources
4.1.4
Exercises
4.2
Solutions
5
Multiple linear regression models (I)
5.1
Seminar
5.1.1
Loading, Understanding and Cleaning our Data
5.1.2
Estimating a Bivariate Regression
5.1.3
Multivariate Regression
5.1.4
Joint Significance Test (F-statistic)
5.1.5
Predicting outcome conditional on institutional quality
5.1.6
Additional Resources
5.1.7
Exercises
5.1.8
Midterm Preparation
5.2
Solutions
6
Interactions, Non-Linearities, Fixed Effects
6.1
Seminar
6.1.1
Loading Data
6.1.2
Interactions: Continuous and Binary
6.1.3
Non-Linearities
6.1.4
Fixed Effects
6.1.5
Exercises
6.1.6
Extra Info: Dummy Variables Repetition
6.2
Solutions
6.2.1
Question 1
6.2.2
Question 2
6.2.3
Question 3
6.2.4
Question 4
6.2.5
Question 5
6.2.6
Question 6
6.2.7
Question 7
6.2.8
Question 6
7
Regression Assumptions
7.1
Seminar
7.1.1
Required Packages
7.1.2
Omitted Variable Bias
7.1.3
Detecting non-linearity
7.1.4
Heteroskedasticity
7.1.5
Exercises
7.2
Solutions
8
Binary Dependent Varible Models (I)
8.1
Seminar
8.1.1
Required Packages
8.1.2
Loading Data
8.1.3
Linear regression with a Binary Dependent Variable
8.1.4
Logistic Regression Model
8.1.5
Odds-ratios
8.1.6
Predicted probabilities
8.1.7
Exercises
8.2
Solutions
9
Binary Dependent Variable Models (II)
9.1
Seminar
9.1.1
Loading Data
9.1.2
Models with Binary Dependent Variables and Interactions
9.1.3
Predicted Probabilities and Predictive Power
9.1.4
Joint hypothesis testing
9.1.5
Exercises
9.1.6
Final Preparation
9.2
Solutions
Optional Material
Central Limit Theorem
Visualizing Distributions
Linear Regression
Resources
Downloading R and RStudio
Online Learning
Graphics and Visualizations
Documentation
Other Resources
R Humor
Datasets
Seminars and Assignments
R Packages
Governmental and Nongovernmental Organizations
Collections
Books
Frequently Asked Questions
Exporting a Plot from R
Introduction to Quantitative Methods
Frequently Asked Questions
Exporting a Plot from R
Saving a plot in RStudio is easy. In the plot window, click on
Export
and choose
“Save as Image”
.
