Brainmaker

Nanos gigantium humeris insidentes!
You are currently browsing the Statistics category

how to use rating

  • November 11, 2014 8:27 pm
  • http://www.evanmiller.org/how-not-to-sort-by-average-rating.html
  • http://www.evanmiller.org/bayesian-average-ratings.html
  • http://www.evanmiller.org/ranking-items-with-star-ratings.html

Four Assumptions Of Multiple Regression That Researchers Should Always Test

  • December 9, 2013 11:29 pm

From:http://pareonline.net/getvn.asp?n=2&v=8

  1. VARIABLES ARE NORMALLY DISTRIBUTED.
  2. A LINEAR RELATIONSHIP BETWEEN THE INDEPENDENT AND DEPENDENT VARIABLE(S).
  3. VARIABLES ARE MEASURED WITHOUT ERROR (RELIABLY)
  4. HOMOSCEDASTICITY

Linear Regression, Bridge Regression and Lasso

  • December 6, 2013 12:03 am

Naive Bayes classifier Probabilistic model

  • October 14, 2013 8:08 pm

Abstractly, the probability model for a classifier is a conditional model.
p(C \vert F_1,\dots,F_n)\,
over a dependent class variable C with a small number of outcomes or classes, conditional on several feature variables F_1 through F_n. The problem is that if the number of features n is large or when a feature can take on a large number of values, then basing such a model on probability tables is infeasible. We therefore reformulate the model to make it more tractable.

Probit Models — An Application Example

  • October 14, 2013 6:01 pm

http://www.sts.uzh.ch/past/hs09/em/topic9a_p.pdf

Bayesian inference

  • October 12, 2013 5:21 pm
Statistical inference is the process of drawing conclusions from data that are subject to random variation.
Bayesian inference
Bayesian inference is a method of inference in which Bayes’ rule is used to update the probability estimate for a hypothesis as additional evidence is acquired. Bayesian updating is an important technique throughout statistics, and especially in mathematical statistics.