Chapter Overview and Learning Objectives4.1 Statistics and Sampling Distributions4.1.1 Sampling from a Normal Distribution4.1.2 Sampling from a Bernoulli Distribution4.1.3 Sampling from a Poisson Distribution4.2 Point Estimation of Process Parameters4.3 Statistical Inference for a Single Sample4.3.1 Inference on the Mean of a Population, Variance Known4.3.2 The Use of P-Values for Hypothesis Testing4.3.3 Inference on the Mean of a Normal Distribution, Variance Unknown4.3.4 Inference on the Variance of a Normal Distribution4.3.5 Inference on a Population Proportion4.3.6 The Probability of Type II Error and Sample Size Decisions4.4 Statistical Inference for Two Samples4.4.1 Inference for a Difference in Means, Variances Known4.4.2 Inference for a Difference in Means of Two Normal Distributions, Variances Unknown4.4.3 Inference on the Variances of Two Normal Distributions4.4.4 Inference on Two Population Proportions4.5 What If There Are More Than Two Populations? The Analysis of Variance4.5.1 An Example4.5.2 The Analysis of Variance4.5.3 Checking Assumptions: Residual Analysis4.6 Linear Regression Models4.6.1 Estimation of the Parameters in Linear Regression Models4.6.2 Hypothesis Testing in Multiple Regression4.6.3 Confidance Intervals in Multiple Regression4.6.4 Prediction of New Observations4.6.5 Regression Model Diagnostics