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  1. spunky

    Answer to @Dason's question

    Dason asked yesterday: "Dason: Like how would you propose something simpler... like turning the equation for a circle into a pdf: x^2 + y^2 = 1" And because I'm in a procrastinating mood (I've got like a bazillion things to do before the end of the month) I thought about it during the evening...
  2. spunky

    How to remove negative values from a bell curve?

    The half-normal distribution, perhaps?
  3. spunky

    Factor analysis

    I... don't really think I follow what you're asking here. I mean, sure. If there are all these ways to measure spending and all relate to it, perhaps (hopefully) you're going to end up with only 1 or 2 principal components that account for most of the variance. And since they are...
  4. spunky

    The difference between interaction and moderation effects

    We have the same thing in social-science-land where we borrow the language from ANOVA and call a "main effect" the predictor we truly care about and the "moderator" whichever one's levels, we believe, would yield different values for the main effect. But as far as the regression part goes, both...
  5. spunky

    The difference between interaction and moderation effects

    Moderation and interaction effects are the same thing. "Moderation" is more used in social-science land. "Interaction" is what everybody else uses. But it's the same thing.
  6. spunky

    Factor analysis

    For the type of problem you're describing, Principal Component regression seems more appropriate. It's almost like Factor Analysis but Principal Components does exactly what you're interested in doing: takes a large collection of variables and extracts the main 2-4 or so that explain the...
  7. spunky

    Hi from South Africa

    Thank you for dropping by! And welcome! For book recommendations, what would you say is your math level (high school? 1st year college calculus?, etc.)? Or are you looking more for non-technical books written for a lay audience to "re-spark" the interest?
  8. spunky

    Hi from Italy

    Hello Alberto! Welcome! We hope you'll like it around here!
  9. spunky

    LOG10 and SQRT transformation

    Before you transform anything, this might be a useful read for you:
  10. spunky

    Hi everybody

  11. spunky

    Endogeneity and R-squared

    True. since R^{2} is a linear combination of correlations and (standardized) regression coefficients, the bias it experiences depends on the size of the coefficients as well as how many of them are biased and in which direction we would observe the bias. However, the key point is that we don't...
  12. spunky

    Endogeneity and R-squared

    Well... it's not super difficult to show that for OLS regression models of the form Y= \beta_0 + \beta_1X_1 + \beta_2X_2 +...+\beta_pX_p + \epsilon , the R^{2} statistic is a function of the elements of the correlation matrix of the predictors and the vector of correlations between the...
  13. spunky

    Reporting Stats Results in APA format

    Sure thing. The APA Style Manual is the official guide for all this stuff
  14. spunky

    How much of Science is based on Statistics

    Another important search term for your googling adventure: 5 sigma A big chunk of evidence for the discovery of the Higgs Boson by CERN relies on that and when you read the description you realize it really is just a p-value.
  15. spunky

    Please show work

    Check this out to complete your work
  16. spunky

    Hello everyone

    Welcome! Here's a good solution to your problem.
  17. spunky

    Analyze non-normally distr. data from within-subjects-design

    Why would you expect the residuals to be normally distributed? Your dependent variable is bounded from 1 to 5 in discrete intervals. Just look at your quantile plot and see how they move in steps as opposed to a smooth, continuous curve. In any case... you're in one of those cases where I'm...
  18. spunky

    Analyze non-normally distr. data from within-subjects-design

    I think reading through this two would be more informative than me writing a whole rant about it: Normality: residuals or dependent variable? and Analyzing ordinal data with metric models: What could possibly go wrong?
  19. spunky

    Kappa for nonsquare tables

    I've never touched SAS in my life ¯\_(ツ)_/¯
  20. spunky

    Kappa for nonsquare tables

    Do you know that STATA does that it lets you handle it? Is it still fitting everything as if it were a square matrix and applying some sort of 'continuity correction'? I remember some software just throw in a 0.5 if there are 0s anywhere.