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:
•To learn and understand the basic statistical intuition behind Ordinary Least Squares
•To be at ease with regression terminology and the assumptions behind Ordinary Least Squares
•To be able to comfortably interpret and analyze complicated regression output from Ordinary Least Squares
•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.
Courses » Teaching & Academics » Social Science » Regression Analysis » Easy Statistics: Linear Regression
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Easy Statistics: Linear Regression
An easy introduction to Ordinary Least Squares regression
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This course contains:
Table of contents
Description
You will learn
✓ To be at ease with regression terminology.
✓ The assumptions and requirements of Ordinary Least Squares (OLS) regression.
✓ To comfortably interpret and analyse regression output from Ordinary Least Squares.
Requirements
• There are no equations in this course!
• “Easy Statistics” is designed for all levels and does not require any knowledge of mathematics or statistics.
• Some Stata knowledge may come in handy but this is not required.
• A genuine interest in understanding quantitative methods.
This course is for
• Practitioners who require quantitative knowledge.
• Business users and managers who engage with quantitative reports.
• Government workers who are involved in policy analysis.
• Anyone who has an interest in, or needs to engage, with statistical regression.
How much does the Easy Statistics: Linear Regression course cost? Is it worth it?
Does the Easy Statistics: Linear Regression course have a money back guarantee or refund policy?
Are there any SCHOLARSHIPS for this course?
Who is the instructor? Is F. Buscha a SCAM or a TRUSTED instructor?
Franz is a Professor of Economics at the University of Westminster. Franz joined the University of Westminster in 2006 after completing his PhD in Economics at Lancaster University.
Franz’s personal research interests are in education economics, labor economics, and applied econometrics. Franz has made scientific contributions to issues such as social mobility, measuring the returns to education, the effect of weather of happiness and identity formation. He has been involved in numerous funded research projects from research councils and government departments.
Franz has contributed to wide range of projects including policy evaluation and bespoke econometric advice to UK government departments. These include the Ministry of Defence, HM Revenue and Customs, the Department for Education and the Department for Business, Innovation and Skills.
He has published in leading journals such as Economics of Education Review, the Oxford Bulletin of Economics and Statistics, the British Journal of Political Science and the British Journal of Sociology. Franz has also contributed to numerous policy reports and his research has been covered by media outlets such as BBC news, BBC Radio 4, The Economist, The Guardian, The Times, and Huffington Post. Franz also has a monthly radio program called Policy Matters on Share Radio.
Franz is an experienced online educator and has published several online courses including LinkedIn Learning.
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