How reproducible are studies with shared data? I collect one more data point in a quest for the answer, and make a side exploration into a linear regression conundrum.

Five alternatives to a broken axis scale for data visualization’s wide scale problem, and a broken line chart tip.

Any investigation into small R² values leads to a different finding about extrapolation.

A study of gender balance in Star Trek dialog leads to an adventure in data cleaning and a smoothing revelation.

Where a more realistic (skeuomorphic) data encoding is less accurate to read.

A study of a map of wine consumption reveals many underlying choices, both cosmetic and substantive.

When a linear fit doesn’t look right, should we use it anyway? Let’s not — here are some alternatives.

That is the question. Or is it about the value of the individual responses versus combined responses? And don’t forget to smooth.

Trying to remake a divorce percentage chart led me learn about the new Census Bureau table query interface to its Public Use Microdata.

Looking at the raw data behind two recent studies of early suicide counts during the Covid-19 pandemic gives me a chance to try out a “moving box plot” since the data is a bit sparse for regular confidence intervals.