This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings.
Este curso forma parte de Programa especializado: Data Science Foundations: Statistical Inference

Acerca de este Curso
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
Qué aprenderás
Identify characteristics of “good” estimators and be able to compare competing estimators.
Construct sound estimators using the techniques of maximum likelihood and method of moments estimation.
Construct and interpret confidence intervals for one and two population means, one and two population proportions, and a population variance.
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
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Programa - Qué aprenderás en este curso
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Point Estimation
Maximum Likelihood Estimation
Large Sample Properties of Maximum Likelihood Estimators
Confidence Intervals Involving the Normal Distribution
Acerca de Programa especializado: Data Science Foundations: Statistical Inference

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