Udemy course The STATA OMNIBUS: Regression and Modelling with STATA by F. Buscha
The STATA OMNIBUS: Regression and Modelling with STATA is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the Business category. Therefore, if you are looking to improve your Business skills we recommend that you download The STATA OMNIBUS: Regression and Modelling with STATA udemy course.
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Course data:
- Author: F. Buscha
- Course rating: 4.5
- Category: Business
- Modality: Online
- Status: Available
- Idiom: English
Abouth F. Buscha
Check out my twitter feed for regular promo codes.
What the udemy The STATA OMNIBUS: Regression and Modelling with STATA course teaches?
What you’ll learn The theory behind linear and non-linear regression analysis. 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. To learn and understand how Logit and Probit models work. To learn tips and tricks around Non-Linear Regression analysis. Practical examples in Stata Tips for building regression models An introduction to Stata Data manipulation in Stata Data visualisation in Stata Data analysis in Stata Regression modelling in Stata Simulation in Stata Survival analysis Count Data analysis Categorical Data analysis Panel Data Analysis Epidemiology Instrumental Variables Power Analysis Difference-in-Differences Show more Show less
4 COURSES IN 1! Includes introduction to Linear and Non-Linear Regression, Regression Modelling and STATA. Updated Freq.
More information about the course The STATA OMNIBUS: Regression and Modelling with STATA
Make sure to check out my twitter feed for promo codes and other updates (easystats3). 4 COURSES IN ONE! Learn everything you need to know about linear regression, non-linear regression, regression modelling and STATA in one package. Linear and Non-Linear 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, course that focuses on the basic principles of statistical methodology. This course will focus on the concept of linear regression and non-linear regression. Specifically Ordinary Least Squares, Logit and Probit Regression. This course will explain what regression is and how linear and non-liner regression works. It will examine how Ordinary Least Squares (OLS) works and how Logit and Probit models work. It will do this without any complicated 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 general regression terminology and the assumptions behind Ordinary Least Squares To be able to comfortably interpret and analyze complicated linear regression output from Ordinary Least Squares To learn tips and tricks around linear regression analysis To learn and understand the basic statistical intuition behind non-linear regression To learn and understand how Logit and Probit models work To be able to comfortably interpret and analyze complicated regression output from Logit and Probit regression To learn tips and tricks around non-linear 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 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 Probit 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. Regression Modelling Understanding how regression analysis works is only half the battle. There are many pitfalls to avoid and tricks to learn when modelling data in a regression setting. Often, it takes years of experience to accumulate these. In these sessions, we will examine some of the most common modelling issues. What is the theory behind them, what do they do and how can we deal with them? Each topic has a practical demonstration in Stata. Themes include: Fundamental of Regression Modelling – What is the Philosophy? Functional Form – How to Model Non-Linear Relationships in a Linear Regression Interaction Effects – How to Use and Interpret Interaction Effects Using Time – Exploring Dynamics Relationships with Time Information Categorical Explanatory Variables – How to Code, Use and Interpret them Dealing with Multicollinearity – Excluding and Transforming Collinear Variables Dealing with Missing Data – How to See the Unseen The Essential Guide to Stata Learning and applying new statistical techniques can be daunting experience. This is especially tr…
