Introduction to Inferential Statistics: What you need to know before you take regression

This course was designed for people who do not have much prior experience with statsitics or who are not totally comfortable with basic statistical concepts like hypothesis testing, p-values, standard errors, distributions, correlation, etc.

It is a one-week course providing a solid foundation for those starting from practically zero who want to work up to taking the course in multiple regression (the most commonly used statistical technique in the social sciences) in the second week.

Day 1
First we discuss basic distributions with a strong emphasis on the normal distribution (otherwise known as the bell curve) but considering others as well. We cover the types of variables and how central tendency (mean, median, mode) and variability (range, variance and standard deviation) can be measured, as these are the essential foundational building blocks of statistical inference.

Day 2
We continue by understanding how standardised scores (such as IQ, SAT, GRE and, most importantly, z-scores) can get us one step closer to comparable statistical estimates used for inference. Then we turn back to the normal distribution to see how the concepts of probability, distributions and standardised scores come together, highlighting the power of both the normal distribution and what it can tell us.

Day 3
We explore why it is not even crucial to have normally distributed variables when doing statistical inference. With our newly gained knowledge we learn to leverage statistical properties of group means and learn how to formulate (and even test) simple hypotheses using statistical inference.

Day 4
We leverage the discoveries of an old brewery employee who also revolutionised the world of statistics by allowing us to move from simple hypothesis testing of situations with too many assumptions (z test) to be realistic to testing hypotheses commonly found in the social sciences (t test and ANOVA). We explore both group comparisons, changes over time and comparisons to some gold standard value.

Day 5
We move to testing relationships between variables using correlations and we introduce bivariate regression which provides the foundation of multiple regression analysis. If time allows we explore another class of statistics which make less assumptions about distributions and learn how to answer different types of research questions with this different type of analytical technique (the Chi-Square test).

NONE – REALLY! If you can remember how to add, subtract, divide and multiply using both negative and positive numbers, you are ready to take this course.

There may be an occasional square and square root that, in this class, we are happy to calculate with a calculator.

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least two hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.

Please check your course format before registering.

Online courses

Live classes will be held daily for two hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.

In-person courses

In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.