Here are some suggestions for you:Ai, C. and E. C. Norton, 2003. Interaction terms in logit and probit models. Economics Letters, 80, 123-129.Hirschberg, J. and J. Lye, 2017. Inverting the indirect - the ellipse and the Boomerang: Visualizing the confi...
Here's a suggested reading list for February:Casey, G. and M. Klemp, 2016. Instrumental variables in the long run. MPRA Paper No. 68696.Coglianese, J., L. W. Davis, L. Kilian, and J. H. Stock, 2016. Anticipation, tax avoidance, and the price elasticity...
There are several tricky things about teaching and understanding the normal distribution, and in this post I’m going to talk about three of them. They are the idea of a model, the limitations of the normal distribution, and the idea … Continue reading →
Every now and then a student will ask me why the formula for the density of a Normal random variable includes the constant, π, or more correctly (2π)-½.The answer is that this term ensures that the density function is "proper" - that is, the integra...
One student of mine coded by mistake an independent Metropolis-Hastings algorithm with too small a variance in the proposal when compared with the target variance. Here is the R code of this implementation: It produces outputs of the following shape which is quite amazing because of the small variance. The reason for the lengthy freezes […]
I've talked a bit about spurious regressions a bit in some earlier posts (here and here). I was updating an example for my time-series course the other day, and I thought that some readers might find it useful.Let's begin by reviewing what is usually m...
Suppose that the random variables X1 and X2 are jointly distributed as bivariate Normal, with means of θ1 and θ2, variances of σ12 and σ22 respectively, and a correlation coefficient of ρ.In this post we're going to be looking at the distribution ...
W. S. Gosset (Student) provided this useful aid to help us remember the difference between platykurtic and leptokurtic distributions:('Student', 1927. Errors of routine analysis. Biometrika, 19, 151-164. See p. 160.)Here, β2 is the fourth standardized...
Consider 2 random variables, and , from the normal distribution , where is unknown. Then the statistic has the distribution . The distribution of does not depend on , so is an ancillary statistic for . Note that, if is unknown, then is not ancillary for .Filed under: Mathematical Statistics, Statistics, Statistics Lesson of the […]
Consider 2 random variables, and , from the normal distribution , where is unknown. Then the statistic has the distribution . The distribution of does not depend on , so is an ancillary statistic for . Note that, if is unknown, then is not ancillary for .Filed under: Mathematical Statistics, Statistics, Statistics Lesson of the […]
