Guide to basic Statistical Methods

Statistics doesn't need to be hard. While many natural science students view it as their nemesis, it exists to reveal patterns we might not otherwise see, providing a better understanding of our world. When I help junior students with data analysis, I always look forward to one moment: the smile on their faces when they create their first graph and conduct their first test. Suddenly, incomprehensible data transforms into an easy-to-grasp plot, accompanied by a number validating their findings.

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Unfortunately, teaching statistics is challenging. I applaud any lecturer who can make it understandable and enjoyable, showing students that statistics is not a nemesis but an ally. The biggest hurdle is that students often struggle to remember which test to use for different hypotheses and data types.

To help, my supervisor and I created a small table outlining the most common basic analyses, logically arranged by data type. It also includes explanations of the most common terms.

It is by no means comprehensive. For example, it doesn't cover the assumptions for different types of tests. However, I believe it can be a useful tool for basic orientation in statistical methods.

You can download the template here and modify it to your liking. Or translate it to the language in which you teach! If you do so, please send me the translation so I can publish it on this page. It might be useful for others.

Please don't hesitate to contact me if you find any mistakes in this material or have suggestions for improvement. Let's make statistics less menacing!

Translations

CZECH