Student Solutions Manual for Essentials of Probability & Statistics for Engineers & Scientists

This manual contains completely worked-out solutions for all the odd-numbered exercises in the text.

Table of Contents:
1. Introduction to Statistics and Probability 1.1 Overview: Statistical Inference, Samples, Populations, and the Role of Probability 1.2 Sampling Procedures; Collection of Data 1.3 Discrete and Continuous Data. 1.4 Probability: Sample Space and Events             Exercises 1.5 Counting Sample Points             Exercises 1.6 Probability of an Event 1.7 Additive Rules             Exercises 1.8 Conditional Probability, Independence, and the Product Rule             Exercises 1.9 Bayes' Rule             Exercises             Review Exercises   2. Random Variables, Distributions, and Expectations 2.1 Concept of a Random Variable 2.2 Discrete Probability Distributions 2.3 Continuous Probability Distributions             Exercises 2.4 Joint Probability Distributions             Exercises 2.5 Mean of a Random Variable             Exercises 2.6 Variance and Covariance of Random Variables.             Exercises 2.7 Means and Variances of Linear Combinations of Random Variables             Exercises             Review Exercises 2.8 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   3. Some Probability Distributions 3.1 Introduction and Motivation 3.2 Binomial and Multinomial Distributions             Exercises 3.3 Hypergeometric Distribution             Exercises 3.4 Negative Binomial and Geometric Distributions 3.5 Poisson Distribution and the Poisson Process             Exercises 3.6 Continuous Uniform Distribution 3.7 Normal Distribution 3.8 Areas under the Normal Curve 3.9 Applications of the Normal Distribution             Exercises 3.10 Normal Approximation to the Binomial             Exercises 3.11 Gamma and Exponential Distributions 3.12 Chi-Squared Distribution.             Exercises             Review Exercises 3.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   4. Sampling Distributions and Data Descriptions 4.1 Random Sampling 4.2 Some Important Statistics             Exercises 4.3 Sampling Distributions 4.4 Sampling Distribution of Means and the Central Limit Theorem             Exercises 4.5 Sampling Distribution of S2 4.6 t-Distribution 4.7 F-Distribution 4.8 Graphical Presentation             Exercises             Review Exercises 4.9 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   5. One- and Two-Sample Estimation Problems 5.1 Introduction 5.2 Statistical Inference 5.3 Classical Methods of Estimation. 5.4 Single Sample: Estimating the Mean 5.5 Standard Error of a Point Estimate 5.6 Prediction Intervals 5.7 Tolerance Limits             Exercises 5.8 Two Samples: Estimating the Difference between Two Means 5.9 Paired Observations             Exercises 5.10 Single Sample: Estimating a Proportion 5.11 Two Samples: Estimating the Difference between Two Proportions             Exercises 5.12 Single Sample: Estimating the Variance             Exercises             Review Exercises 5.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   6. One- and Two-Sample Tests of Hypotheses. 6.1 Statistical Hypotheses: General Concepts 6.2 Testing a Statistical Hypothesis 6.3 The Use of P-Values for Decision Making in Testing Hypotheses             Exercises 6.4 Single Sample: Tests Concerning a Single Mean 6.5 Two Samples: Tests on Two Means 6.6 Choice of Sample Size for Testing Means 6.7 Graphical Methods for Comparing Means             Exercises 6.8 One Sample: Test on a Single Proportion. 6.9 Two Samples: Tests on Two Proportions             Exercises 6.10 Goodness-of-Fit Test 6.11 Test for Independence (Categorical Data) 6.12 Test for Homogeneity 6.13 Two-Sample Case Study             Exercises             Review Exercises 6.14 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   7. Linear Regression 7.1 Introduction to Linear Regression 7.2 The Simple Linear Regression (SLR) Model and the Least Squares Method.             Exercises 7.3 Inferences Concerning the Regression Coefficients. 7.4 Prediction             Exercises 7.5 Analysis-of-Variance Approach 7.6 Test for Linearity of Regression: Data with Repeated Observations             Exercises 7.7 Diagnostic Plots of Residuals: Graphical Detection of Violation of Assumptions 7.8 Correlation 7.9 Simple Linear Regression Case Study.             Exercises 7.10 Multiple Linear Regression and Estimation of the Coefficients             Exercises 7.11 Inferences in Multiple Linear Regression             Exercises             Review Exercises   8. One-Factor Experiments: General 8.1 Analysis-of-Variance Technique and the Strategy of Experimental Design 8.2 One-Way Analysis of Variance (One-Way ANOVA): Completely Randomized Design 8.3 Tests for the Equality of Several Variances             Exercises 8.4 Multiple Comparisons             Exercises 8.5 Concept of Blocks and the Randomized Complete Block Design             Exercises 8.6 Random Effects Models 8.7 Case Study for One-Way Experiment             Exercises             Review Exercises 8.8 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters   9. Factorial Experiments (Two or More Factors) 9.1 Introduction 9.2 Interaction in the Two-Factor Experiment 9.3 Two-Factor Analysis of Variance             Exercises 9.4 Three-Factor Experiments.             Exercises             Review Exercises 9.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters