# Recent content by luchins

1. ### Gaussian process and Gaussian regression

Hello, I have some problem understing the Gaussian regression and the way it works. Could you please explain to me some things? The first thing I don't understand is why this regression does it use the joint/multivariate probability to get new value of the Y? The...
2. ### Difference between Mann-Kendall and Pearsons Correlation to obtain p-value

before to make the linear regression why haven't you calculated the pearson index? It would have been wise to calculate the pearson index BEFORE the linear regression
3. ### How can be used time series in sport?

Why don't use a regression model instead of time series analisy?
4. ### How can be used time series in sport?

Hello, noob here in statistics. How can be time series be useful to sport stats modelling? Let's take as an examplem footbal
5. ### What is the difference between sample algorithms and algoritms for estimating parameters?

I have red this in the website: MCMC is a family of sampling algorithms, which means given a distribution, these algorithms return samples according to this distribution. Many problem, bayesian posterior inference for instance, require you compute the posterior distribution P(θ|D), most of...
6. ### Before to making a regression

''However, with large sample size and a larger average counts,'' What do you mean with ''large average counts'' ? sorry not native-english... Can you make an example? Also ''many say around 8 or larger, the Poisson begins to approximate a normal distribution and a linear model can be...
7. ### Weighted avearge mean

Hello here is my problem. I am analizying some tennis matches, and I am able to see the highest odd (bookmaker's odd) reached by that tennis player in N-matches (N is number of matches) Then I take all the highest odds reached by that tennis player during his N-matches , and...
8. ### Before to making a regression

Hello I want to ask you, before to making a regression should we understand which distribution follow the datas? Let's take an example: if the data have a poisson distribution, then I will run a Poisson regression? If the data follow a gaussian then one should use...
9. ### Density probability function considering a subinterval which have different probabilities

Thanks I don't get it what is F(b) and what is F(a)... sorry.... How do I integrate PDF from a to b? Sorry could you make an example? How could I calculate it numerically?
10. ### Density probability function considering a subinterval which have different probabilities

Let's suppose the area was not a rectangular, but a gaussian normal distribution with a mean, a standard deviationetc. How to calculate the odds in that case?
11. ### Standardization of a variable

Example I saw this discussion: https://stats.stackexchange.com/questions/166584/a-regression-to-predict-tennis-players-service-point-win-percentage-which-of This guy asked to stack exange: (My personal question which I would ask to you, are Question n1 and Question n2) '' Hello...
12. ### Don't understand the meaning of ''training a dataset''

Hi, I have a set of data. Those data are based on data mining from my website. I have the number of users per month who go to my website ( X ) , and the time they spent on the website on each webpage ( y ) . Now with this dataset as an example, could you...
13. ### Standardization of a variable

Hello, before making a linear regression, how can I know if I have to standardize a variable?
14. ### analisy of residual

Hi, after a regression is necessary to make an analisy of residuals to know if the model were accurate? ù Noob here, could you explaine me please, why you could do an analisy of residuals and for which purpose does it serve?
15. ### Bernoulli distribution

Thank you, with a Bayesian type of ''prior'' what should I assume? shoud I set as a ''prior'' probability (computed by my personal tought)? sorry if this is a terrible question, I am new