"Ask for help on your project" open thread

Emile

"Ask for help on your project" open thread — LessWrong

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For the last 30+ days, I've been randomly taking vitamin D before bed and recording sleep data with Zeo as well as my best guess whether it was D or placebo: http://www.gwern.net/Zeo#vitamin-d

But I'm going to finish within the next <10 days, and then it's time for analysis. I would like to do a real statistical analysis, like a 'one-tailed T test', on the ZQ and components like length of REM sleep, but I don't actually know how - I've never used the standard statistical programs or packages like R. (Yes, yes, I know, I should learn real statistics. I haven't yet, though.)

My needs aren't too complex, I'm just asking whether the vitamin D did anything (bad), so maybe there is an easy to use online tool or something which would handle it?

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Matt_Simpson14y20

Badger's solution works, but an alternative is to post a link to the data here and let LW take a crack at it. I can fit a wide variety of models in a matter of minutes in R, and wouldn't mind spending an hour or two doing so and writing up the results.

5Andy_McKenzie14y

My alma mater hosts a widely used web-based tool for statistical procedures that includes t-tests. Find it here. Click on "t-Tests & procedures", then go to "Two-Sample t-Test for Independent or Correlated Samples", then click on "independent samples" (given the description of your set-up above), then enter in the values for each condition, click "calculate", and viola you'll have your results. Cool experiment by the way. Note that if you do multiple tests (like on both ZQ and length of REM), you might want to do a multiple comparisons correction to maintain that familywise error rate.

8badger14y

If you have prior programming experience, R is simple for basic analysis. I don't know of any online tools. The following would be close to sufficient for what you seem to want: mydata <- read.table("c:/sleepdata.csv", header=TRUE, sep=",") # Read in data w/ variable names in header fit <- lm(ZQ ~ guess + placebo, data=mydata) # Compute linear regression summary(fit) # Get estimated coefficients with t-statistics and p-values For cookbook code, see Quick R. If you do use R, the RStudio IDE is very useful.

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