Easy Statistics: Non-Linear Regression | Franz Buscha | Skillshare

# Easy Statistics: Non-Linear Regression

#### Franz Buscha

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23 Lessons (1h 4m)

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• ### 23. Stata - Applied Logit and Probit Examples

18:27
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An easy introduction to Logit and Probit regression.

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, classÂ that focuses on the basic principles of statistical methodology.

This classÂ will focus on the concept of Non-Linear regression, specifically Logit and Probit regression.

This classÂ will explain what non-linear regression is and how Logit and Probit regression works. It will do this without equations or mathematics. The focus of this classÂ is on application and interpretation of regression. The learning on this classÂ is underpinned by animated graphics that demonstrate particular statistical concepts.

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

The main learning outcomes are:

1. To learn and understand the basic statistical intuition behindÂ Non-Linear regression

2. To learn and understand how Logit and Probit models work

3. To be able to comfortably interpret and analyze complicated regression output from Logit and Probit regression

4. To learn tips and tricks around Non-Linear Regression analysis

Specific topics that will be covered are:

• What kinds of Non-Linear regression analysis exist

• How does Non-Linear regression work?

• Why is Non-Linear regression useful?

• What is Maximum Likelihood?

• The Linear Probability Model
• Logit and ProbitÂ regression

• Latent variables

• Marginal effects

• Dummy variables in Logit and Probit regression

• Goodness-of-fit statistics

• Odd-ratios for Logit models

• Practical Logit and Probit model building in Stata

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

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