DataMedics DataMedics
How Data Actually Works course cover
Course

How Data Actually Works

A gentle, hands-on first course that shows you what data is, how a table is built, how to ask a question data can answer, and how to read a chart without being fooled.

Before you begin

You work in Google Sheets or Microsoft Excel. Both are free to start, and there is nothing to install.

This is guidance, not a gate. You can enrol and start whenever you like.

What you will be able to do

  • Say what data is, in your own words, and spot data in everyday life.
  • Read any simple table: name its rows, columns, cells and variables.
  • Tell the main kinds of data apart (numbers, categories, dates, blanks).
  • Open a real dataset in Google Sheets, sort it, filter it and count things in it.
  • Turn a vague wonder into a clear question that a table can answer.
  • Read a bar chart and a line chart correctly, and make a simple one yourself.
  • Spot five common chart and number tricks, so you are not fooled.
  • Write a short, honest "data story": a question, the evidence, and the answer.

Syllabus

Data is everywhere

What data is: writing down what we notice Rows: one thing, one line Columns and variables: what we notice about each thing Cells and values: one fact in one box Your first spreadsheet: open, look, scroll

Kinds of data

Numbers you count and numbers you measure Categories: labels, not amounts Categories that have an order Dates and times Blanks: when a value is missing A number that is really a label

Asking questions data can answer

From "I wonder" to a clear question Which rows and which columns? Sorting: putting rows in order Filtering: looking at only some rows Counting and adding up Questions a table cannot answer

Reading charts

Why we draw data at all Reading a bar chart Reading a line chart Making your first chart Picking bar or line

How not to be fooled

The axis that does not start at zero Totals versus "per person" The picked time window Averages that hide the spread Together is not the same as because

Your first data story

The three parts of a data story Checking your own work Saying what you found, and what you did not Where to go next