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This Concept Map, created with IHMC CmapTools, has information related to: Inferential statistics, A Sample generates results containing Errors, Parameters characterize Probability distributions, Probability distributions are characterized by their Expected value, The sample distribution of the mean of x converges to a normal distribution thanks to a result from A Central Limit Theorem, Inferential statistics uses A Sample, A Population contains Parameters, Estimates of parameters allow the analyst to make Inferences, Inferential statistics provides Parametric techniques, Random variables can follow The Binomial Distribution, Inferential statistics provides Non-parametric techniques, Estimates e.g. Point estimates, Parameters are estimated through Sample statistics, A Sample provides information to obtain Estimates, Inferences are carried out through Hypothesis testing, Interval estimates are computed using Confidence intervals, Random variables can follow The Normal Distribution, Inferential statistics is based on the notion of Probability, Probability measures the likehood of Random variables, Estimates e.g. Interval estimates, The Normal Distribution can approximate The Binomial Distribution