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Statistical Inference/Point Estimation
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Statistical Inference
Revision as of 12:19, 4 August 2018 by
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Statistical Inference
Probability Theory
Transformations and Expectations
Common Families of Distributions
Multiple Random Variables
Properties of a Random Sample
Principles of Data Reductions
Point Estimation
Hypothesis Testing
Interval Estimation
Asymptotic Evaluations
Analysis of Variance and Regression
Regression Models
Contents
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1
Methods of Finding Estimators
1.1
Method of Moments
1.2
Maximum Likelihood Estimators
1.3
Bayes Estimators
1.4
The EM Algorithm
2
Methods of Evaluating Estimators
2.1
Mean Squared Error
2.2
Best Unbiased Estimators
2.3
Sufficiency and Unbiasedness
2.4
Loss Function Optimality
Methods of Finding Estimators
Method of Moments
Maximum Likelihood Estimators
Bayes Estimators
The EM Algorithm
Methods of Evaluating Estimators
Mean Squared Error
Best Unbiased Estimators
Sufficiency and Unbiasedness
Loss Function Optimality
Categories
:
Statistics
Statistical Inference