I’ve just finished a solid first-draft of a post that I’m planning on submitting to main, and I’m looking for someone analytical to look over a few of my calculations. I’m pretty sensitive, so I’d be embarrassed if I posted something with a huge mistake in it to LW. The post is about the extent to which castration performed at various ages extends life expectancy in men, and was mainly written to inform people interested in life extension about said topic, though it might also be of interest to MtF trans people.
All of my calculations are in an excel spreadsheet, so I’ll email you the text of the post, as well as the excel file, if you’re interested in looking over my work. I’m mainly focused on big-picture advice right now, so I’m not really looking for someone to, say, look for typos. The only thing I’m really worried about is that perhaps I’ve done something mathematically unsavory when trying to crudely use mean age-at-death actuarial data from a subset of the population that existed in the past to estimate how long members of that same subset of the population might live today.
Being able to use math to build the backbone of a scientific paper might be a useful skill for any volunteers to have, though I don’t suspect that any advanced knowledge of statistics is necessary. Thanks!
Thanks for the offer! I’ve just emailed Vaniver (since I already know him), and I’ll re-evaluate how confident I feel about my post after I chat with him, and then send you a note if I think that I’m not quite where I want to be with the post by then.
All of my calculations are in an excel spreadsheet, so I’ll email you the text of the post, as well as the excel file, if you’re interested in looking over my work.
One of the trends I’ve seen happening that I’m a fan of is writing posts/papers/etc. in R, so that the analysis can be trivially reproduced or altered. In general, spreadsheets are notoriously prone to calculation errors because the underlying code is hidden and decentralized; it’s much easier to look at a python or R script and check its consistency than an Excel table.
(It’s better to finish this project as is than to delay this project until you know enough Python or R to reproduce the analysis, but something to think about for future projects / something to do if you already know enough Python or R.)
Spreadsheets can be reproduced and altered just as any code. I think the purpose of writing a post in code is mainly about keeping the code in sync with the exposition. But this was the purpose of MS Office before R even existed.
I am skeptical of spreadsheets, but is there any evidence that they are worse than any other kind of code? Indeed
These error rates, although troubling, are in line with those in programming and other human cognitive domains.
(I am not sure what that means. If the per-cell error rate is the same as the per-line rate of conventional programming, that definitely counts as spreadsheets being terrible. But I think the claim is 0.5% per-cell error rate and 5% per-line error rate.)
Even if there were evidence that spreadsheets are worse than other codebases, I would be hesitant to blame the spreadsheets, rather than the operators. It is true that there are many classes of errors that they make possible, but they also have the positive effect of encouraging the user to look at intermediate steps in the calculation. I suspect that the biggest problem with spreadsheets is that they are used by amateurs. People see them as safe and easy, while they see conventional code as difficult and dangerous.
I’ve just finished a solid first-draft of a post that I’m planning on submitting to main, and I’m looking for someone analytical to look over a few of my calculations. I’m pretty sensitive, so I’d be embarrassed if I posted something with a huge mistake in it to LW. The post is about the extent to which castration performed at various ages extends life expectancy in men, and was mainly written to inform people interested in life extension about said topic, though it might also be of interest to MtF trans people.
All of my calculations are in an excel spreadsheet, so I’ll email you the text of the post, as well as the excel file, if you’re interested in looking over my work. I’m mainly focused on big-picture advice right now, so I’m not really looking for someone to, say, look for typos. The only thing I’m really worried about is that perhaps I’ve done something mathematically unsavory when trying to crudely use mean age-at-death actuarial data from a subset of the population that existed in the past to estimate how long members of that same subset of the population might live today.
Being able to use math to build the backbone of a scientific paper might be a useful skill for any volunteers to have, though I don’t suspect that any advanced knowledge of statistics is necessary. Thanks!
I can take a look, send me a PM if you like.
Thanks for the offer! I’ve just emailed Vaniver (since I already know him), and I’ll re-evaluate how confident I feel about my post after I chat with him, and then send you a note if I think that I’m not quite where I want to be with the post by then.
I can take a look; you know my email.
One of the trends I’ve seen happening that I’m a fan of is writing posts/papers/etc. in R, so that the analysis can be trivially reproduced or altered. In general, spreadsheets are notoriously prone to calculation errors because the underlying code is hidden and decentralized; it’s much easier to look at a python or R script and check its consistency than an Excel table.
(It’s better to finish this project as is than to delay this project until you know enough Python or R to reproduce the analysis, but something to think about for future projects / something to do if you already know enough Python or R.)
Spreadsheets can be reproduced and altered just as any code. I think the purpose of writing a post in code is mainly about keeping the code in sync with the exposition. But this was the purpose of MS Office before R even existed.
I am skeptical of spreadsheets, but is there any evidence that they are worse than any other kind of code? Indeed
(I am not sure what that means. If the per-cell error rate is the same as the per-line rate of conventional programming, that definitely counts as spreadsheets being terrible. But I think the claim is 0.5% per-cell error rate and 5% per-line error rate.)
Even if there were evidence that spreadsheets are worse than other codebases, I would be hesitant to blame the spreadsheets, rather than the operators. It is true that there are many classes of errors that they make possible, but they also have the positive effect of encouraging the user to look at intermediate steps in the calculation. I suspect that the biggest problem with spreadsheets is that they are used by amateurs. People see them as safe and easy, while they see conventional code as difficult and dangerous.
The key word missing here is inspected, which seems like the core difference to me.
I agree with this.