The r2 (r-squared) values indicate how much the models (2 variables) relate to each other account for or explain the full nature of what’s going on (variance). The r-squared values are low (not always bad). This suggests that there’s more to this than these factors alone.
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A better analysis is to examine something like the Australian Election Study and use a more thorough model to control for more variables. We might find these relationships wash away (or are strengthened) when more information is included.
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There’s no certainty in statistics. Making claims using simplistic models about people (individuals) can cause real harm to communities. Beware what you take from these data.
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Replying to @DrDemography
thanks Liz, I have tried to emphasise as much as possible that this is about the characteristics of electorates rather than actual voter decisions... but possibly I should put in more of an explanation about the r values and strength of correlation?
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Replying to @NickEvershed @DrDemography
It might be good to add a bit about the strength of correlation, to someone without any stats understanding it might look like all the graphs show the same level of association
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Replying to @NickEvershed @DrDemography
Might also be cool to include a model with all the values. Looks like you get an R^2 of about 6, and the things that are still significant with all the controls are coal mines, engagement, migrancy, income/home, and youthpic.twitter.com/4q0jLGzIhC
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(P.S. it is FANTASTIC that you included a Google Doc with all the data, this is great I'm going to have a proper play around when I get a second)
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Replying to @GidMK @DrDemography
No worries, I should make an update actually - I excluded ages 0 - 17 initially which was a mistake, and also looked at some stuff on population density last night based on feedback from
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also I think a measurement approximating "campaign effort" would be important as well, might be do-able with SMH promise tracker: https://www.smh.com.au/federal-election-2019/porkathon-at-26k-per-voter-20190514-p51n4j.html … or by coding the ads we scraped into electorates
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Might be interesting to put the minor party vote proportion and also the wasted votes as other variables, that'd give you some info on voter dissatisfaction . Could look at the AIHW reports for things like healthcare also that might make the model a lot stronger
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