# Search results

1. ### Derivation of Vasicek Entropy Estimator

Hey All - I am trying to solve a problem that should be really easy (at least every paper I read says the step is!) I'm trying to understand where the Vasicek entropy estimator comes from: I can write the differential entropy of a system as: H(f) = -\int^{\infty}_{-\infty} f(x)log(f(x))dx...
2. ### Difference between Renewal Process and Poisson Processes

Hey All, Can someone please explain to me the difference between a Poisson Process and a Renewal Process ? is it just that the Holding times for Poisson processes are exponential and Holding times for Renewal Processes are any kind of probability distribution (as the wiki page seems to imply)...
3. ### Difference between Power Sets and Sample Space

Hey All, In my probability theory class we have just started learning about how a probability space is defined by a sample space (which contains all possible events), events and a measure. We briefly went over the idea of the Power Set, which seems to be the set of all subsets in your...
4. ### Why can t statistic deal with small numbers ?

Hi, I've been trying to get my head around z and t statistics. and I almost have a matra in my head that "when the sample are small, use the t test, when the samples are big, use either the t or the z test". Now As I understand it, the z test requires a large number of samples, because it...
5. ### Random vs fixed effects in ANOVA

hmmm ... is it as simple as: 'between subject factors' = fixed variable 'within subject factors' = random variable ?
6. ### Random vs fixed effects in ANOVA

I am having a lot of trouble conceptually understanding the idea of a random effect in ANOVA testing - more specifically identifying whether a factor is random or fixed Thanks, Thrillhouse86

8. ### Importance of homogenity of variance

Hey all, When performing parametric statistical tests (especially t tests and ANOVA), why is the homogenity of variance important ? I mean why do these tests care if the samples have significantly different variance ? Is it because the methods used to determine the test statistics require...
9. ### P value from z statistic

Thank you both d3t3rt & SW VandeCarr. With my incorrect z score: am I incorrect because the quantity you divide the \bar{X} - \mu by is not the standard deviation of the population, but the standard error of my sample mean ?
10. ### P value from z statistic

thanks guys - the statistics picture is starting to become clearer. just at a very core conceptual level can someone explain this to me: I have a sample (lets say a collection of IQ tests in a suburb) and I want to test whether the mean IQ of these kids is higher than average. So H_0 = the...
11. ### P value from z statistic

Hey SW VandeCarr, yep I know what a pdf is - and I am comfortable with the idea that if you integrate between bounds of a pdf that it gives you the probability of your random variable being between those bounds. As I understood it you get this thing called a z statistic from that formula...
12. ### P value from z statistic

Hey All, Can someone please explain to me why the p value is obtained by taking the integral under the z curve from the z statistic you calculate to the end of the tail ? Thanks
13. ### Biased and unbiased estimators

cool thanks D H
14. ### Biased and unbiased estimators

So does that mean you never really want a biased estimator, but sometimes practical issues force you to work with one ?
15. ### Biased and unbiased estimators

Hey All, I am comfortable with the idea of biased and unbiased estimators, but what I don't understand is why you would ever want to use a biased estimator ? at the end of the day doesn't it mean that the sample statistic is different from the population statistic you are trying to estimate ?
16. ### Unbiased estimator of variance

Hey all, In Schaum's outline it claims that the sample variance of s^2 is a biased estimate of the population variance because its mean is given by: \mu_{s^{2}} = \frac{N-1}{N}\sigma^{2} which I am cool with. It then says that the modified variance given by: \hat{s} =...