Beginning Concepts / Skills

Jumping In: Big ideas about statistics

In order to teach students about data, we have to start by thinking like a statistician. Remember that one statistics class you suffered through? No? That’s because this can be, in the wrong hands, a bit…er…dry. In short – here are a few key points to keep in mind (modified from Data Literacy Partners):

  • Scientists and engineers usually make observations and collect data with a clear question in mind.
  • As you work to answer your question, collect data from more than one example – from as many examples as you reasonably can.  
  • When measuring more than one sample, expect that the samples will vary.
  • Show variability in a graph and describe the patterns you see. 
  • Try to make sense of why the data vary the way they do.

To get students thinking about these points, try modifying this interactive powerpoint from Data Literacy Partners. 

Translating the jargon: how to talk about data.

Talking the talk in science is very important – but can be a challenge when introducing new terminology to students. Check out this handy reference sheet from the Data Literacy Project to help you navigate the world of data jargon that goes far beyond mean, median, and mode.

Speaking of mean, median, and mode…your students may be masters of defining these terms, but not so great at putting them to use. Middle school teachers might modify this quick powerpoint to spur discussion about what we really mean by “middle”. 

Getting to know your data: Cases, Attributes, Quantities, oh my!

Whether it’s a Weatherblur dataset, or data you are interpreting from another source, approaching a big bank of numbers can be intimidating. Students (and, let’s be honest, us!) need support in how to begin to analyze and explore data. Guiding students through a series of questions with more and more complex datasets will give them confidence in working with messy data. Which is a good thing – because data seems to be getting messier and messier!

Try using this simple template from our partners at Tuva to help students explore datasets. Use sample datasets on Tuva, your own Weatherblur data, or any other source of datasets (we suggest the recent sports stats..or, if the pandemic is still around..some historical sports stats!). 

We also LOVE the resources coming out of the United Kingdom and their Barefoot Computing Program. It does require registering, but we think you’ll find it more than worth it. Here is an example of a great lesson plan for students introducing basic data concepts, such as attributes, in a fun and interactive way.

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