Since the contestant has chosen Door #1, the host can only show either Door #2 or Door #3. The prior probability that the prize is behind door #1 is \(p(Door_1)=1/3\) and the prior probability that the prize is behind Door #3 \(p(Door_3)\) is also \(1/3\) – without any additional information, each door is equally likely to be the winner. Thus, we are going to compare the probability that the prize is behind Door 1 given that the host has shown that the prize is not behind Door 2 – we’ll call that \(p(Door_1|Show_2)\) – with the probability that the prize is behind Door 3 given that the host has shown Door 2 – \(p(Door_3|Show_2)\).
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Turn off sound pretty good solitaire 9.2 software#
7.4.1 Correcting the Kendall’s \(\tau\) Software Estimate.7.3.2 The Proportionate Reduction in Error ( \(R^2\)).7.3.1 The Least-Squares Regression Line.7.2.1 The Product Moment Coefficient \(r\).7.1.1 …but it Doesn’t Imply NOT Causation either.7.1 Correlation Does Not Imply Causation….6.1.2 The Six (sometimes Five) Step Procedure.6.1.1 Classical Null Hypothesis Testing.6.1 Examples of Classical and Bayesian Analyses.6.0.1 Different Approaches to Analyzing the Same Data.5.3.5 The Connections Between the Normal and the Binomial.
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5.3.4 Percentiles with the Normal Distribution.5.3.3 The Cumulative Normal Distribution.5.3.2 Features of the Normal Distribution.5.2.5 Finding Binomial Probabilities with R Commands.5.2.3 Sufficient Statistics for the Binomial.5.2.2 Features of the Binomial Distribution.5.1 Weirdly-shaped Jars and the Marbles Inside.Barch, reprinted with permission from the author 4.12.2 Excerpts from Statistics for Everybody by D.4.12.1 Why is the factorial of zero equal to one?.4.6 Elementary and Compound (or Composite) Events.4.1 Probability, Statistics, and Scientific Inquiry.3.6 The Worst Data Visualization Ever Made.3.4.11 Alluvial Diagrams ( aka Sankey Plots, aka Riverplots, aka Ribbonplots).3.4.4 Combining Histogram Elements with Bar Chart Elements.3.1.2 Datasets Created for the Figures in This Chapter.3.1.1 Packages Used to Make The Figures in This Chapter.2.5.1 The mathematical link between mean, variance, skewness, and kurtosis.2.3.1 A Brief Divergence Regarding Histograms.2.2.3 Dependent and Independent Variables, Predictor Variables and Predicted Variables.2 Categorizing and Summarizing Information.