Beyond IQ

Talking Back to Statistics

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Math
Instructor: Lisa Fontaine-Rainen
5-10 students
Suggested Age Ranges: 9-12; 11-14
Meets: Mondays at 2:15 pm - 3:15 pm Pacific time

CLASS DESCRIPTION:

What do you mean by those numbers?  Do they say what you're trying to tell me they say?  Are you hiding something?  Where did they come from anyway? 

In a world filled with data, one of the most important skills we can develop is thinking critically about that data - finding the inherent bias in all data.  We are going to interrogate data!

We will look at many example of data in all it stages, mostly real, some crafted to demonstrate the issues that can arise. We will read How to Lie with Statistics by Darrell Huff (available free online). Students will try their hands at the art of data manipulation. Students are not expected to have prior knowledge of statistics – content required to understand manipulation will be taught alongside the actual manipulation, however, the focus of the course is on the bias and manipulation over the content itself, so students who come with no statistics background may find they need to work more outside of class on the material. Students will learn how to collect, analyze, represent, and interpret data, but the focus is on how bias is introduced when we do this, and how to ask questions of data to try to determine what the truth really is.  This class will be heavy in discussion, with accommodations made for students who prefer to take more time to think before responding.  

PrerequisitesNone

 

SYLLABUS:

Week 1: Introduction to statistics, pre-assessment, discussion of “What is fair?” 

Week 2: Questionnaires, leading questions, question order, background information 

Week 3: Sampling methods, why sampling is important, when sampling goes wrong 

Week 4: Science and data gathering – the importance of the control, changing a single variable, basic experimental design 

Week 5:  The concept of “average” – mean median, mode, when to use each, when to be sure which one you’re hearing 

Week 6: Data analysis beyond the average – other methods of crunching the numbers, what they mean, and what they don’t.  Margin of error. 

Week 7:  Graphs week 1 – ways to display those numbers that trick the eyes! 

Week 8:  Graphs week 2 – more ways to make those numbers look all out of whack! 

Week 9 The semi-attached figure – getting people to think what you want by showing them something else. 

Week 10: Post hoc ergo propter hoc – correlation vs. causation 

Week 11: Logical fallacies continued – a look at other logical fallacies and how they can impact thinking about data and statistics. 

Week 12: Statisculation – a review of some of the other nasty things people can do, sometimes without even realizing it! 

Week 13: Summary of talking back to a statistic, development of steps to ensure you have examined a statistic well. A chance to really tackle some good examples! 

Week 14: A week built in to go off on tangents that arise, make-up anything we fall behind on, or explore something the students wish to explore. 

Week 15: Wrap up discussion, sharing of projects.


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