Posts Tagged ‘random’
Friday, November 20th, 2009
Definition of an Outlier
Description
A detailed tutorial on the definition of an outlier. Step by step tutorial including several examples of definitions of outliers for reference.
Overview
An outlier is a type of observation of statistical data. It is usually very far away from the other values in the data set, hence the name. Usually it is a number that is much smaller than the other numbers, although it could be much larger than the other numbers as well. Outliers have an equal chance of occuring in any random observation, but they are still rare. Typically when an outlier is found it means there is some sort of mistake, usually a measurement error.
Tags: chance, data, elements, equal, error, larger, measurement, mistake, numbers, observation, outlier, random, set, smaller, statistical, statistics, values
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Thursday, November 12th, 2009
Introduction to the Margin of Error
Description
A detailed tutorial on the margin of error. Step by step tutorial including several examples of the margin of error for reference.
Overview
The margin of error is a statistic that expresses the amount of possible random sampling errors that could end up in the result of a survey. The bigger the margin of error, the less trustworthy the survey is, because it means that everything falling within the margin of error could possibly be wrong and not accurate. However, if the margin or error is small, then the survey should be very accurate.
Tags: accuracy, accurate, error, less, margin, more, random, results, right, sampling, statistics, survey, true, trustworthy, wrong
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Thursday, September 17th, 2009
Law 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.
Tags: average, expected, expected value, law of large numbers, Math, mean, possibilities, probability, random, statistics, value, variable
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Thursday, September 17th, 2009
Definition 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.
Tags: average, continuous, discrete math, expected, expected value, limit, Math, mean, probability, random, sample, solutions, statistics, value, variable
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