Date: December 13-15 2023, 10.00 AM (2 x 90 min)
Instructor: Levente Littvay (TK PTI)
Location: Centre for Social Sciences - 1097 Budapest, Tóth Kálmán u. 4.,
K.0.13-14. rooms
Number of participants: max. 30 person
Course language: English
Regression
Gain a deeper understanding of regression analysis through this intensive workshop covering the foundations: correlations and simple linear regression, multiple regression, and advanced regression techniques. We will build regression analysis from the ground up through hands-on calculation of correlations and bivariate regressions to ensure a strong foundation. The assumptions underlying regression modeling, including linearity, normality, homoscedasticity, and lack of multicollinearity (things you may be conveniently ignoring when running regression models) will be thoroughly examined to equip participants to apply and interpret results properly. Advanced topics such as general linear models, weights, and models beyond regression basics will be covered to provide you with the skills needed to tackle complex research problems. Join us for this comprehensive workshop and master regression analysis for advanced research and data science applications.
Some modeling examples will be provided in R. No pre-requisite R knowledge is required, although if you want to use what you learned, it is useful if you know how to work with data in R.
Pre-requisites: The workshop is targeting people who have some statistical foundations. Either you are using statistical techniques but feel you are missing important foundations. Or you had an introductory course that has been too long ago and need a review. It is possible to come to this session and learn everything from scratch, but if you are in this situation, email me beforehand as soon as possible, and I will help you get the most out of the workshop. Otherwise, all I will ask of you is to remember basic algebra, addition, subtraction, multiplication, and division, know the order of operations, and put up with the occasional square root.