Data Analysis For the Busy

 is this data?

is this data?

 
 

So Much Data, So Little Time aka Why Didn't I Learn This Earlier?

We're now 20 years into the 21st century and data, data analysis, data science, data privacy, data about data has taken over our lives, our businesses, our governments.   But most of us didn't get formal or even informal training in understanding and using data.   

In "Data Analysis for the Busy" busy people from all walks of life will learn in a 5 week session the basis of modern data analysis and how to make sense of the world and any business at a reasonable, literate level.  The focus in making everyone comfortable with common analysis techniques, commonly used software and how to interpret the work of others.

Syllabus

Week 1:  What is Data and Why Do I Care?

Here we will set the table on all things data.   By the end of the session you'll be doing some basic analysis and be comfortable using common tools.

Week 2: The Basics of Analysis

The key to analysis is knowing where to start and which techniques to pull out.  A surprising amount of work can be done with some very basic tools.

Week 3:  Gotchas, Lies and Other Fun Tricks

We will review some common ways people lie with data/stats and sometimes how we goof ourselves up with things like bias and type errors.  Again, there are some simple things to learn that will serve you very well in a variety of situations.

Week 4: Collecting Data and Being Not-Completely Silly in Setting Up Experiments

So much data analysis goes wrong because people don't collect the right data or make poor assumptions in setting up data collection.  Most data science is not good because it uses previously collected data with unknown collection methods.   This week we'll learn how not to be a bad data scientist.  

Week 5: Try To Finish or Knowing When to Stop

Like anything interesting in life... it's never clear when the end has come.  Data has no end but at some point you have to move on in life.  This week we learn to say good bye.

Skills Obtained

  • Reading common data analysis charts
  • Understanding survey and poll reports
  • Using Excel and Google Sheets for many things
  • Understanding common statistics and data science vocabulary
  • How to spot bad data analysis
  • Understanding the limits of data science
  • Experimental Design
  • Breaking down a problem into its data components
  • Presenting Data Analisys
  • Confidence with Numbers and Talking to Data Experts
  • Demystification of Mumbo Jumbo

Workload

In class discussion and working sessions, demonstrations and short lectures.

1-2hrs of homework a week leading towards a final project that may take 3-4 hrs.

Grades and Credit

This is all for professional development but I'm happy to give recommendations or nice notes etc.

Dates/Times

Every Tuesday from 7-8pm pacific time starting May 8th.   ends June 5th.

Meets in person and online through ZOOM Conferences.   
In person will take place in Venice, CA.

Enrollment

In person enrollment limited to 10, online enrollment unlimited.

Cost

$125 for entire 5 weeks