We will start with the concepts variable and data, the difference between population and sample and types of data. Then we will consider the most important measures for centrality (mean, median and mode) and spread (standard deviation and variance). These will be followed by the concepts contingency, correlation and regression. All these statistics make it possible to represent large amounts of data in a clear way, enabling us to spot interesting patterns.
The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work. We will end the course with a short preview of inferential statistics - statistics that help us decide whether the differences between groups or correlations between variables that we see in our data are strong enough to conclude that our predictions were confirmed and our hypothesis is supported.
You will not only learn about all these concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software.