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Statistical Inference/Analysis of Variance and Regression
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Statistical Inference
Revision as of 11:34, 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
1
Oneway Analysis of Variance
1.1
Model and Distribution Assumptions
1.2
The Classic ANOVA Hypothesis
1.3
Inferences Regarding Linear Combinations of Means
1.4
The ANOVA F Test
1.5
Simultaneous Estimation of Contrasts
1.6
Partitioning Sums of Squares
2
Simple Linear Regression
2.1
Least Squares: A Mathematical Solution
2.2
Best Linear Unbiased Estimators: A Statistical Solution
2.3
Models and Distribution Assumptions
2.4
Estimation and Testing with Normal Errors
2.5
Estimation and Prediction at a Specified
x = x0
2.6
Simultaneous Estimation and Confidence Bands
Oneway Analysis of Variance
Model and Distribution Assumptions
The Classic ANOVA Hypothesis
Inferences Regarding Linear Combinations of Means
The ANOVA F Test
Simultaneous Estimation of Contrasts
Partitioning Sums of Squares
Simple Linear Regression
Least Squares: A Mathematical Solution
Best Linear Unbiased Estimators: A Statistical Solution
Models and Distribution Assumptions
Estimation and Testing with Normal Errors
Estimation and Prediction at a Specified
x = x0
Simultaneous Estimation and Confidence Bands
Categories
:
Statistics
Statistical Inference