Easy Statistics: Linear and Non-Linear Regression

Explore the world of regression analysis with "Easy Statistics," a comprehensive course designed for anyone needing to understand and apply statistical methodology. This course combines three essential topics: linear regression, non-linear regression, and general regression modelling.

Learn the fundamental principles of statistical modelling without getting bogged down in complex equations. We focus on practical application and interpretation, using animated graphics to illustrate key concepts. No prior statistical knowledge is required!

What You'll Learn:

• Ordinary Least Squares (OLS): Understand the basic statistical intuition behind OLS, its assumptions, and how to interpret its output. Master tips and tricks for effective linear regression analysis.
• Logit and Probit Regression: Learn how Logit and Probit models work to analyze categorical data. Gain the ability to interpret and analyze complex regression output and apply practical techniques.
• Regression Modelling: Discover practical strategies for building robust regression models. We'll address common pitfalls and provide solutions for issues like multicollinearity and missing data.

Key Topics Covered:

• Regression Analysis Fundamentals: Explore different types of regression, including correlation vs. causation and parametric vs. non-parametric lines of best fit.
• OLS in Depth: Delve into the least squares method, R-squared, beta's, standard errors, T-statistics, p-values, and confidence intervals. Understand the Best Linear Unbiased Estimator and Gauss-Markov assumptions.
• Non-Linear Regression: Understand the core concepts of non-linear regression and its applications. Learn about Maximum Likelihood and how to model complex relationships.
• Logit & Probit Models: Master Logit regression, Probit regression, latent variables, and marginal effects. Learn to use dummy variables and interpret odd-ratios.
• Practical Regression Modelling: Gain hands-on experience with functional form, interaction effects, time series analysis, categorical variables, multicollinearity, and missing data.
• Software Demonstration: Practical examples will be demonstrated using Stata software.
• Interpreting and Presenting Regression Output: Learn how to effectively communicate your findings.

Learning Outcomes:

• Understand the statistical intuition behind Ordinary Least Squares.
• Become proficient in general regression terminology and its assumptions.
• Confidently interpret and analyze linear regression output.
• Master non-linear regression concepts.
• Effectively interpret Logit and Probit regression output.
• Develop practical skills in regression modelling.

This course is ideal for anyone needing to engage with quantitative analysis, from students to professionals.

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