Curriculum

9 Sections
50 Lessons
Lifetime

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What is Data?
This course gives a short introduction in the world of data. If you are starting your journey into this wonderful land, this course is for you. The course covers basic concepts, different types of data and gives an introduction to machine readable data.
6
Finding Data
Don't know where to start looking for data? This section gives an introduction to data portals and different data sources. Finally we will walk you through how to use one sample data portal.
5
Sort and Filter: The basics of spreadsheets
So you found and downloaded your dataset? What now? Sort and Filter introduces a powerful tool to manage data: Spreadsheets. Based on Google Spreadsheets, this Course introduces the basic functions as well how to sort and filter data to find what you might be interested in…
8
Taming the Fierce Beast – The Math you need to start
Worried about all those numbers? This module will help you to refresh the basic math (don't be afraid it's mainly counting and adding).
10
'But what does it mean?': Analyzing data (spreadsheets continued)
Wonder how to make sense of the data? Basic Analysis will help you to understand what your data might mean. It also introduces spreadsheet formulas and helps you calculate more values out of what you already have.
4
From Data to Diagrams: An introduction to plots and charts
A picture says more than a thousand words – yeah but how do we turn a thousand words into a picture? This section will help you to understand basic data visualization and create them using Google spreadsheets. Visualizing data will help you to better understand the data you are handling.
7
Look Out!: Common Misconceptions and how to avoid them
Not everything is easily understood in dataland. In this course we give a short overview over common pitfalls when talking about data and how to avoid them. It can help you avoid the mistakes made as well as read other peoples claims more carefully. If you want to learn what to watch out for: join in!
9
Tell me a story: Working out what’s interesting in your data
Data alone is meaningless and often boring. To understand it better you will need context. In this section we will talk about how to publish the data we worked on throughout the basic track. We will talk about how to identify key points of your data to help you use data to make your voice heard.
6
Data provenance
To make a credible and sustainable data project, you need to document your steps right from the beginning. This course contains tips and tricks and tools for doing so.
3

Normalizing Data – aka. comparing things

Once we have an idea of what we’re talking about, let’s figure out how we compare things.

Let’s say we want to compare two countries that are quite different in several aspects. If we want to compare their GDPs, for example, we can do so, but it will not tell us anything useful. If, for example, one country is very big and another is very small, the bigger will have the higher GDP. Does that mean it’s more productive? No. We’ll have to compare them on equal footing. Usually this is done using something that tells us how big a country is; in countries, that’s often population.

To compare productivity, we can divide the GDP by the population. This is called normalization. Now we can compare the GDP per capita. This is so commonly done that you will probably have heard of this indicator.

Another way of normalizing values is to use percentages. For example, if you want to compare what countries spend on health, it is great to normalize this by the GDP (e.g. to say this country spends a relatively great amount on health, whereas this other country doesn’t). Or think of elections: we commonly encounter percentages there (e.g. we calculate how many people voted for party A and divide this by the number of valid votes).

How big is the variation in the data?

Data Fundamentals

Curriculum

Normalizing Data – aka. comparing things

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