Type II Error
In hypothesis testing, a type II error is due to a failure of rejecting an invalid null hypothesis. The probability of avoiding a type II error is called the power of the hypothesis test, and is denoted by the quantity 1  β .
In the following tutorials, we demonstrate how to compute the power of a hypothesis test based on scenarios from our previous discussions on hypothesis testing. The approach is based on a parametric estimate of the region where the null hypothesis would not be rejected. The probability of a type II error is then derived based on a hypothetical true value.
 Type II Error in Lower Tail Test of Population Mean with Known Variance
 Type II Error in Upper Tail Test of Population Mean with Known Variance
 Type II Error in TwoTailed Test of Population Mean with Known Variance
 Type II Error in Lower Tail Test of Population Mean with Unknown Variance
 Type II Error in Upper Tail Test of Population Mean with Unknown Variance
 Type II Error in TwoTailed Test of Population Mean with Unknown Variance
R Tutorials
 R Introduction
 Elementary Statistics with R
 Qualitative Data
 Quantitative Data
 Numerical Measures
 Probability Distributions
 Interval Estimation
 Hypothesis Testing
 Lower Tail Test of Population Mean with Known Variance
 Upper Tail Test of Population Mean with Known Variance
 TwoTailed Test of Population Mean with Known Variance
 Lower Tail Test of Population Mean with Unknown Variance
 Upper Tail Test of Population Mean with Unknown Variance
 TwoTailed Test of Population Mean with Unknown Variance
 Lower Tail Test of Population Proportion
 Upper Tail Test of Population Proportion
 TwoTailed Test of Population Proportion
 Type II Error
 Type II Error in Lower Tail Test of Population Mean with Known Variance
 Type II Error in Upper Tail Test of Population Mean with Known Variance
 Type II Error in TwoTailed Test of Population Mean with Known Variance
 Type II Error in Lower Tail Test of Population Mean with Unknown Variance
 Type II Error in Upper Tail Test of Population Mean with Unknown Variance
 Type II Error in TwoTailed Test of Population Mean with Unknown Variance
 Inference About Two Populations
 Goodness of Fit
 Analysis of Variance
 Nonparametric Methods
 Simple Linear Regression
 Multiple Linear Regression
 Logistic Regression
 GPU Computing with R
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