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Gupta / Guttman

Statistics and Probability with Applications for Engineers and Scientists

Medium: Buch
ISBN: 978-1-118-46404-5
Verlag: WILEY
Erscheinungstermin: 31.05.2013
Lieferfrist: bis zu 10 Tage

Introducing the tools of statistics and probability from the ground up

An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences.

Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab(r) and Microsoft(r) Office Excel(r) to analyze various data sets. The book also features:

* Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices

* A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method

* Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology

* A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP (r) routines and results

Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.


Produkteigenschaften


  • Artikelnummer: 9781118464045
  • Medium: Buch
  • ISBN: 978-1-118-46404-5
  • Verlag: WILEY
  • Erscheinungstermin: 31.05.2013
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2013
  • Produktform: Gebunden
  • Gewicht: 2018 g
  • Seiten: 896
  • Format (B x H x T): 203 x 257 x 46 mm
  • Ausgabetyp: Kein, Unbekannt
  • Nachauflage: 978-1-119-51663-7
Autoren/Hrsg.

Autoren

Preface xvii

Chapter 1 Introduction 1

1.1 Designed Experiment 2

1.2 A Survey 5

1.3 An Observational Study 6

1.4 A Set of Historical Data 6

1.5 A Brief Description of What is Covered in This Book 6

PART I

Chapter 2 Describing Data Graphically and Numerically 11

2.1 Getting Started with Statistics 12

2.2 Classification of Various Types of Data 15

2.3 Frequency Distribution Tables for Qualitative and Quantitative Data 17

2.4 Graphical Description of Qualitative and Quantitative Data 25

2.5 Numerical Measures of Quantitative Data 41

2.6 Numerical Measures of Grouped Data 55

2.7 Measures of Relative Position 59

2.8 Box-Whisker Plot 62

2.9 Measures of Association 68

2.10 Case Studies 71

2.11 Using JMP1 73

Review Practice Problems 73

Chapter 3 Elements of Probability 83

3.1 Introduction 84

3.2 Random Experiments, Sample Spaces, and Events 84

3.3 Concepts of Probability 88

3.4 Techniques of Counting Sample Points 93

3.5 Conditional Probability 98

3.6 Bayes's Theorem 100

3.7 Introducing Random Variables 104

Review Practice Problems 105

Chapter 4 Discrete Random Variables and Some Important Discrete

Probability Distributions 111

4.1 Graphical Descriptions of Discrete Distributions 112

4.2 Mean and Variance of a Discrete Random Variable 113

4.3 The Discrete Uniform Distribution 117

4.4 The Hypergeometric Distribution 119

4.5 The Bernoulli Distribution 122

4.6 The Binomial Distribution 123

4.7 The Multinomial Distribution 126

4.8 The Poisson Distribution 128

4.9 The Negative Binomial Distribution 132

4.10 Some Derivations and Proofs (Optional) 135

4.11 A Case Study 135

4.12 Using JMP 135

Review Practice Problems 136

Chapter 5 Continuous Random Variables and Some Important Continuous Probability Distributions 143

5.1 Continuous Random Variables 144

5.2 Mean and Variance of Continuous Random Variables 146

5.3 Chebychev's Inequality 151

5.4 The Uniform Distribution 152

5.5 The Normal Distribution 157

5.6 Distribution of Linear Combination of Independent Normal Variables 165

5.7 Approximation of the Binomial and Poisson Distribution by the Normal Distribution 169

5.8 A Test of Normality 171

5.9 Probability Models Commonly Used in Reliability Theory 175

5.10 A Case Study 191

5.11 Using JMP 192Review Practice Problems 192

Chapter 6 Distribution of Functions of Random Variables 199

6.1 Introduction 200

6.2 Distribution Functions of Two Random Variables 200

6.3 Extension to Several Random Variables 214

6.4 The Moment-Generating Function Revisited 214

Review Practice Problems 218

Chapter 7 Sampling Distributions 223

7.1 Random Sampling 224

7.2 The Sampling Distribution of the Mean 228

7.3 Sampling from a Normal Population 234

7.4 Order Statistics 247

7.5 Using JMP 247

Review Practice Problems 247

Chapter 8 Estimation of Population Parameters 251

8.1 Introduction 252

8.2 Point Estimators for the Population Mean and Variance 252

8.3 Interval Estimators for the Mean m of a Normal Population 262

8.4 Interval Estimators for the Difference of Means of Two Normal Populations 272

8.5 Interval Estimators for the Variance of a Normal Population 280

8.6 Interval Estimator for the Ratio of Variances of Two Normal Populations 284

8.7 Point and Interval Estimators for the Parameters of Binomial Populations 288

8.8 Determination of Sample Size 294

8.9 Some Supplemental Information 298

8.10 A Case Study 298

8.11 Using JMP 299

Review Practice Problems 299

Chapter 9 Hypothesis Testing 307

9.1 Introduction 308

9.2 Basic Concepts of Testing a Statistical Hypothesis 308

9.3 Tests Concerning the Mean of a Normal Population Having Known Variance 312

9.4 Tests Concerning the Mean of a Normal Population Having Unknown Variance 324

9.5 Large Sample Theory 330

9.6 Tests Concerning the Difference of Means of Two