Fandom Data Viz
May. 29th, 2018 08:56 pmAt work I get to play with data using SPSS and Prism.
One of the things we do with the data and programmes is Kaplan–Meier analyses.
But at home, I do not have such things, but I like to play about with stats, partly to understand how a measure works, partly because I find it calming.
I was originally going to look at survival times of US Presidents. But it struck me as morbid, and while I can just about do the maths for 2 categories, I had no idea what to do with the Whig presidents and George Washington. (Ideas about how to do deal with either of the above are gratefully accepted, I think I've got a hang on the maths now.)
Then I realised I had access to a whole swatch of data, which easily divides into two groups. Hits on my fics at AO3.
So I divided my fics into shippy and non shippy, and looked to see if any had more than 1000 hits. (1000 was chosen at random.)
Unfortunately, I can only easily get hold of data for the last 12 months and all of the fics that had reached 1000 were more than 12 months old at the beginning.
But I thought, what the hey, it's over time and it gives me a starting point so I plotted the data using the method outlined here - http://www.real-statistics.com/survival-analysis/kaplan-meier-procedure/survival-curve/
Last month, a new fic had achieved 1000 hits (Battalion of Worries, NC-17 rating shippy Torchwood fic).
The Kaplan-Meier curve now looks like this:
First thing to note, the difference is not significant (at a p<0.05 level. p value was 0.164776, thanks to![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png)
ioplokon for noticing that I'd not put it in). (I cheated and used http://www.socscistatistics.com/tests/chisquare/Default.aspx to work out my X-squared values.)
I think the analysis might be clearer if I used the reciprocal to produce a curve that goes upwards not downwards.
I've also found another useful source (Survival analysis in clinical practice: analyze your own data using an Excel workbook by Lucijanić - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4800329/) so there's lots more fun I can have.
One of the things we do with the data and programmes is Kaplan–Meier analyses.
But at home, I do not have such things, but I like to play about with stats, partly to understand how a measure works, partly because I find it calming.
I was originally going to look at survival times of US Presidents. But it struck me as morbid, and while I can just about do the maths for 2 categories, I had no idea what to do with the Whig presidents and George Washington. (Ideas about how to do deal with either of the above are gratefully accepted, I think I've got a hang on the maths now.)
Then I realised I had access to a whole swatch of data, which easily divides into two groups. Hits on my fics at AO3.
So I divided my fics into shippy and non shippy, and looked to see if any had more than 1000 hits. (1000 was chosen at random.)
Unfortunately, I can only easily get hold of data for the last 12 months and all of the fics that had reached 1000 were more than 12 months old at the beginning.
But I thought, what the hey, it's over time and it gives me a starting point so I plotted the data using the method outlined here - http://www.real-statistics.com/survival-analysis/kaplan-meier-procedure/survival-curve/
Last month, a new fic had achieved 1000 hits (Battalion of Worries, NC-17 rating shippy Torchwood fic).
The Kaplan-Meier curve now looks like this:
First thing to note, the difference is not significant (at a p<0.05 level. p value was 0.164776, thanks to
ioplokon for noticing that I'd not put it in). (I cheated and used http://www.socscistatistics.com/tests/chisquare/Default.aspx to work out my X-squared values.)I think the analysis might be clearer if I used the reciprocal to produce a curve that goes upwards not downwards.
I've also found another useful source (Survival analysis in clinical practice: analyze your own data using an Excel workbook by Lucijanić - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4800329/) so there's lots more fun I can have.
