Explaining between and within group differences using Pew Research data on religion/climate change

I am a big fan of Pew Research Center. They collect, share, and summarize data about a wide variety of topics. In addition to providing very accessible summaries of their findings, they also provide more in-depth information about their data collection techniques, including original materials used in their data collection and very through explanations of their methods.

One topic they collect Pew studies is religion and attitudes (religious and secular) held by people of different religions. And it got me thinking that I could use their data in order to explain within and between group differences at the heart of a conceptual understanding of ANOVA.

Specifically, Pew gathered data looking at between-group differences in beliefs in global climate change by religion...

Chart created by Pew Research

...and belief in climate change within just Catholics, divided up by political affiliation.

Chart created by Pew Research

The questionnaires differed slightly for the two surveys. However, both groups were asked whether or not global warming was caused by human activity. The data table illustrates the between group differences between religions and their views on climate change while the bar graphs demonstrate how within one group (Catholics) there is a fair amount of variability in beliefs about climate change, based upon political affiliation.

How to use in class? Well, the Catholics, as a group, report a 45% agreement with the idea that climate change is caused by human activity. Which is pretty different than White Evangelicals, who report a 28% agreement with this statement. So that would be significantly different, right? But wait...62% of Catholic Democrats agree that global climate change is caused by human activity, while only 24% of Catholic Republicans agree with this statement. That is an awful lot of within group variance.

More data on more religion is available from Pew.

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