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Parameter

By Jim Frost

Parameters are the unknown values of an entire population, such as the mean and standard deviation. Samples can estimate population parameters but their exact values are usually unknowable.

Parameters are also the constant values that appear in probability functions. These parameters define the shape of probability distributions. Parameters are typically denoted using Greek symbols to distinguish them from sample statistics.

For example, the parameters of the normal distribution are μ ( mu = population mean) and σ (sigma = population standard deviation).

Related

Related Articles:
  • How to Interpret P-values and Coefficients in Regression Analysis
  • How Hypothesis Tests Work: Significance Levels (Alpha) and P values
  • Curve Fitting using Linear and Nonlinear Regression
  • How to Identify the Distribution of Your Data
  • Overfitting Regression Models: Problems, Detection, and Avoidance

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