Search Results

The reason why plots are universally used to introduce simple regression - a response predicted by a single predictor - is that they aid understanding. However, I believe I can give something of the …

If you think in terms of a discrete-time approximation of the process, the increment in a time interval $\delta t$ will have mean 0 and some variance. If you sum up the contributions in non-overlappi …

"Division" is really very broad because there's all sorts of things we divide by other things, for different reasons, but they just about all have, in some way, something to do with 'scaling' the nume …

I don't think it's necessary if you're just trying to get intuition about the test (though in fact it's pretty straightforward) - if you comprehend the test as "a correlation calculated on the ranks", … you pretty much have most of the useful intuition there. …

There's not really enough information to exploit the likely shortcuts that tend to crop up in particular applications, so if you have more details, please give them. For example, depending on what thi …

In the absence of specific additional information that changes the conditional probability of $A$ or $B$, Bayes rule tells you $P(A|C) = \frac{P(C|A)P(A)}{P(C)}$ and similarly for $P(B|C)$ If $\fra …

I think my comments have grown long enough for an answer... One reason why you might want to look at the multivariate case rather than univariate cases is when there's a lot of dependence between vari …

Due to regression toward the mean, it would (for example) be expected to occur fairly readily if the means of $x$ and $y$ were positive (with $x$ and $y$ positively correlated), and the total least sq …

The numerator of the test statistic is the difference in sample means (representing an estimated difference in population means) But in order to judge whether that's more than would reasonably be see …

$f(0)$ is the density at 0. It is meaningful in several ways. For example, the probability of being within a small distance of $x$ ($\pm \varepsilon/2$) of $x$ is approximately $\varepsilon f(x)$. …

Without equations? Yikes. Let's see: The logistic regression model is literally a model for the $p$ parameter of a binomial distribution; with a continuous predictor, each point can have its own dist …

Some advantages of simulation: you can use it when you don't know how to do the exact calculation you can use it to check you got the exact calculation correct you can generalize the situation and e …

Note that if there were no population effect (the population means were identical at every combination of the regressors), there would still be some estimated effect -- the RegressionSS would be nonze …

the ML estimator results in the value for the parameter which is most likely to occur in the dataset. Given the assumptions, the ML estimator is the value of the parameter that has the best chance o …

While a number of posts on site address various properties of the Cauchy, I didn't manage to locate one that really laid them out together. Hopefully this might be a good place to collect some. I may …