Learning and applying new statistical techniques can often be a daunting experience.

"Easy Statistics" is designed to provide you with a compact, and easy to understand, course that focuses on the basic principles of statistical methodology.

This course will focus on the concept of linear regression, specifically Ordinary Least Squares.

This course will explain what regression is and how Ordinary Least Squares (OLS) works. It will do this without any equations or mathematics. The focus of this course is on application and interpretation of regression. The learning on this course is underpinned by animated graphics that demonstrate particular statistical concepts.

No prior knowledge is necessary and this course is for anyone who needs to engage with quantitative analysis.

The main learning outcomes are:

1. To learn and understand the basic statistical intuition behind Ordinary Least Squares

2. To be at ease with regression terminology and the assumptions behind Ordinary Least Squares

3. To be able to comfortably interpret and analyze complicated regression output from Ordinary Least Squares

4. To learn tips and tricks around regression analysis

Specific topics that will be covered are:

• What kinds of regression analysis exist

• Correlation versus causation

• Parametric and non-parametric lines of best fit

• The least squares method

• R-squared

• Beta's, standard errors

• T-statistics, p-values and confidence intervals

• Best Linear Unbiased Estimator

• The Gauss-Markov assumptions

• Bias versus efficiency

• Homoskedasticity

• Collinearity

• Functional form

• Zero conditional mean

• Regression in logs

• Practical model building

• Understanding regression output

• Presenting regression output

The computer software Stata will be used to demonstrate practical examples.