Statistical Inference & Hypothesis Testing Concepts
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Parametric Inference Fundamentals
The probability distribution of the population under study is known, except for a finite number of parameters. Its goal is to estimate those parameters. Examples include the T-test and ANOVA.
Non-Parametric Inference Basics
The distribution of the population is not known. It is used to test the assumptions of parametric methods, for example, to check if the population distribution is normal.
What is a Statistic?
A random variable function of the sample that does not depend on the unknown parameter.
Understanding Estimators
A statistic whose values are acceptable for estimating an unknown parameter.
Unbiasedness in Estimation
We do not allow systematic overestimation or underestimation of the parameter, which would result... Continue reading "Statistical Inference & Hypothesis Testing Concepts" »