Sampling Theory
Approximate Unbiasedness
Bias Magnitude
MSE Components
Efficiency Comparisons
Linear Regression Estimator
Auxiliary Variable Requirements
Assumptions and Conditions
Bias and Variance Properties
Comparison with Ratio Estimation
Efficiency Gains
Multiple Regression Extensions
Difference Estimator Definition
Appropriate Use Cases
Bias Properties
Variance Characteristics
Comparison with Other Methods
Hybrid Approaches
Optimal Combinations
Practical Applications
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4. Estimation from Samples
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6. Sample Size Determination