Archive for the ‘Statistics’ Category
Binomial Distribution
Friday, September 18th, 2009Law of Large Numbers
Thursday, September 17th, 2009Law of Large Numbers Explained
Description
A detailed tutorial on the Law of Large Numbers. Step by step tutorial including several examples of the Law of Large Numbers for reference.
Overview
The Law of Large Numbers, or the LLN, is a theorem in probability and statistics that refers to how long the mean of the possible choices for a random variable will remain the same. It is called the “stability” of the mean. Rolling a die is the best example of the Law of Large Numbers; although the numbers on the die are not large, no matter what the outcome is the mean is always the same. Anything with a set amount of possibilities like that, such as flipping a coin, would have the same result with the stability of the mean.
Expected Value
Thursday, September 17th, 2009Definition of Expected Value
Description
A detailed tutorial on the solving of Expected Value. Step by step tutorial including several examples of how to solve Expected Value for reference.
Overview
The expected value of a variable is the integral of the variable with respect to its probability measure. It amounts to either the probability-weighted sum or the probability-weighted integral of all possible values of the variable, depending on whether you are using it for discrete random variables or continuous random variables. The expected value does not exist for all variables, but it is always the limit of a sample mean, or average, of the possible solutions for the variable.
Standard Deviation Formula
Friday, September 11th, 2009How to Solve Problems Using the Standard Deviation Formula
Description
A detailed tutorial on the solving of the standard seviation formula. Step by step tutorial including several examples of how to solve standard deviation for reference.
Overview
Standard deviation is a measure of dispersion in statistics. If this is high, then the results are very scattered, but if this is low, then the results are all about the same. The standard deviation formula is as follows:
Variance
Thursday, September 10th, 2009How to Calculate Variance
Description
A detailed tutorial on the solving of Variance. Step by step tutorial including several examples of how to solve Variance for reference.
Overview
The variance of a random variable or distribution is the expected square deviation of that variable from its expected value or mean. The standard deviation or expected deviation can be used as an indicator of the “spread” of a distribution.
