2. Describing data

This week we cover the topic of ‘describing data’ from the perspective that data answer questions.

As scientists, we collect data in order to try and learn something about the natural world (in the case of psychologists, how the mind works). When describing the data we have collected, we must be mindful that our description effectively answers the question of interest. For example:

• When giving descriptive statistics, we must consider how different summary statistics can be interpreted in order to choose the correct ones to report for our particular study.
• When choosing a plot type, we should be mindful of what we want the reader to be able to perceive about the data from the plot (a relationship between two variables? the number of peaks in the distribution? or the difference between a large number of distributions?).

2.1. Tasks for this week

Conceptual material is covered in the lecture. In addition to the live lecture, you can find lecture videos on Canvas.

Please work through the guided exercises in this section (everything except the page labelled “Tutorial Exercises”) in advance of the computer-based tutorial session.

To complete the guided exercises you will need to either:

• open the pages in Google Colab (simply click the Colab button on each page), or
• download them as Jupyter Notbooks to your own computer and work with them locally (eg in Spyder)

If you find something difficult or have questions, you can discuss with your tutor in the computer-based tutoral session.