Cost $550AUD
For more information see https://www.insightrsa.com/introduction-to-linear-and-logistic-regression

Regression can be seen as one of the core techniques used in statistics, where we are interested in predicting an outcome variable based upon a set of predictor variables. We then have different kinds of regression for predicting different kinds of outcome variables.

In this workshop we will explore the foundation for linear and logistic regression. The workshop will cover:
* the basics of statistics (including concepts such as p-values and the role of statistical tests)
* the fundamental equations for linear and logistic regression
* the assumptions that need to be checked when performing regression (linearity, normality, constant variance, no outliers)
* multiple regression and the effect of confounders
* variable selection (choosing which variables to select for a linear regression model)
* the differences between linear and logistic regression
* interpreting the regression coefficients for logistic regression
* nominal and ordinal regression
* Poisson regression (for count variables)