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Probability and Statistics : With Integrated Software Routines.

By: Publisher: Burlington : Elsevier Science & Technology, 2005Copyright date: ©2006Description: 1 online resource (707 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780080480381
Subject(s): Genre/Form: Additional physical formats: Print version:: Probability and Statistics : With Integrated Software RoutinesDDC classification:
  • 519.2
LOC classification:
  • QA273.19.E4D44 2006
Online resources:
Contents:
Front Cover -- Probability and Statistics -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- Chapter 1. Introduction to Probability -- 1.0 Introduction -- 1.1 Interpretations of Probability -- 1.2 Sets -- 1.3 Probability Parlance -- 1.4 Probability Theorems -- 1.5 Conditional Probability and Independence -- 1.6 Bayes's Rule -- 1.7 Counting the Ways -- 1.8 Summary -- Chapter 2. Random Variables, Moments, and Distributions -- 2.0 Introduction -- 2.1 Random Variables -- 2.2 Distributions -- 2.3 Moments -- 2.4 Standardized Random Variables -- 2.5 Jointly Distributed Random Variables -- 2.6 Independence of Jointly Distributed Random Variables -- 2.7 Covariance and Correlation -- 2.8 Conditional Densities Functions -- 2.9 Moment Generating Functions -- 2.10 Transformation of Variables -- 2.11 Summary -- Chapter 3. Special Discrete Distributions -- 3.0 Introduction -- 3.1 Discrete Uniform -- 3.2 Bernoulli Distribution -- 3.3 Binomial Distribution -- 3.4 Multinomial Distribution -- 3.5 Hypergeometric Distribution -- 3.6 Geometric Distribution -- 3.7 Negative Binomial Distribution -- 3.8 Poisson Distribution -- 3.9 Summary -- Chapter 4. Special Continuous Distributions -- 4.0 Introduction -- 4.1 Continuous Uniform Distribution -- 4.2 Gamma Function -- 4.3 Gamma Family (Exponential, Chi-Square, Gamma) -- 4.4 Exponential Distribution -- 4.5 Chi-Square Distribution -- 4.6 Normal Distribution -- 4.7 Student t Distribution -- 4.8 Beta Distribution -- 4.9 Weibull Distribution -- 4.10 F Distribution -- 4.11 Summary -- Chapter 5. Sampling, Data Displays, Measures of Central Tendencies, Measures of Dispersion, and Simulation -- 5.0 Introduction -- 5.1 Data Displays -- 5.2 Measures of Location -- 5.3 Measures of Dispersion -- 5.4 Joint Distribution of X-and S2 -- 5.5 Simulation of Random Variables -- 5.6 Using Monte Carlo for Integration.
5.7 Order Statistics -- 5.8 Summary -- Chapter 6. Point and Interval Estimation -- 6.0 Introduction -- 6.1 Unbiased Estimators and Point Estimates -- 6.2 Methods of Finding Point Estimates -- 6.3 Interval Estimates (Confidence Intervals) -- 6.4 Prediction Intervals -- 6.5 Central Limit Theorem (Revisited) -- 6.6 Parametric Bootstrap Estimation -- 6.7 Summary -- Chapter 7. Hypothesis Testing -- 7.0 Introduction -- 7.1 Terminology in Statistical Tests of Hypotheses -- 7.2 Hypothesis Tests: Means -- 7.3 Hypothesis Tests: Proportions -- 7.4 Hypothesis Tests for Difference between Two Means: Small Samples (n < 30) a2 Known -- 7.5 Hypothesis Test with Paired Samples -- 7.6 Hypothesis Tests: Variances -- 7.7 Hypothesis Tests for Independence, Homogeneity, and Goodness of Fit -- 7.8 Summary -- Chapter 8. Regression -- 8.0 Introduction -- 8.1 Review of Joint and Conditional Densities -- 8.2 Simple Linear Regression -- 8.3 Distribution of Estimators with Inference on Parameters -- 8.4 Variation -- 8.5 Residual Analysis -- 8.6 Convertible Nonlinear Forms for Linear Regression -- 8.7 Polynomial Regression -- 8.8 Multiple Linear Regression -- 8.9 Multiple Regression Techniques -- 8.10 Correlation Analysis -- 8.11 Summary -- Chapter 9. Analysis of Variance -- 9.0 Introduction -- 9.1 Single-Factor Analysis -- 9.2 Two-Way ANOVA without Replication -- 9.3 Two-Way ANOVA with Replication -- 9.4 Multiple Comparisons of Treatment Means -- 9.5 ANOVA and Regression -- 9.6 Analysis of Means (ANOM) -- 9.7 Summary -- Chapter 10. Nonparametric Statistics -- 10.0 Introduction -- 10.1 The Sign Test -- 10.2 Nonparametric Bootstrap Estimation -- 10.3 The Sign Test for Paired Data -- 10.4 The Wilcoxon Signed-Rank Test -- 10.5 Wilcoxon-Mann-Whitney (WMW) Rank Test for Two Samples -- 10.6 Spearman Rank Order Correlation Coefficient -- 10.7 Kendall's Rank Correlation Coefficient (τ).
10.8 Nonparametric Tests for Regression -- 10.9 Nonparametric Tests for ANOVA -- 10.10 Runs Test -- 10.11 Randomization Tests -- 10.12 Summary -- Appendix A: Introduction to the Software Environment -- Appendix B: Statistical Tables -- References -- Index.
Summary: Probability & Statistics with Integrated Software Routines is a calculus-based treatment of probability concurrent with and integrated with statistics through interactive, tailored software applications designed to enhance the phenomena of probability and statistics. The software programs make the book unique. The book comes with a CD containing the interactive software leading to the Statistical Genie. The student can issue commands repeatedly while making parameter changes to observe the effects. Computer programming is an excellent skill for problem solvers, involving design, prototyping, data gathering, testing, redesign, validating, etc, all wrapped up in the scientific method. See also: CD to accompany Probability and Stats with Integrated Software Routines (0123694698) * Incorporates more than 1,000 engaging problems with answers * Includes more than 300 solved examples * Uses varied problem solving methods.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Ebrary Ebrary Afghanistan Available EBKAF00016998
Ebrary Ebrary Algeria Available
Ebrary Ebrary Cyprus Available
Ebrary Ebrary Egypt Available
Ebrary Ebrary Libya Available
Ebrary Ebrary Morocco Available
Ebrary Ebrary Nepal Available EBKNP00016998
Ebrary Ebrary Sudan Available
Ebrary Ebrary Tunisia Available
Total holds: 0

Front Cover -- Probability and Statistics -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- Chapter 1. Introduction to Probability -- 1.0 Introduction -- 1.1 Interpretations of Probability -- 1.2 Sets -- 1.3 Probability Parlance -- 1.4 Probability Theorems -- 1.5 Conditional Probability and Independence -- 1.6 Bayes's Rule -- 1.7 Counting the Ways -- 1.8 Summary -- Chapter 2. Random Variables, Moments, and Distributions -- 2.0 Introduction -- 2.1 Random Variables -- 2.2 Distributions -- 2.3 Moments -- 2.4 Standardized Random Variables -- 2.5 Jointly Distributed Random Variables -- 2.6 Independence of Jointly Distributed Random Variables -- 2.7 Covariance and Correlation -- 2.8 Conditional Densities Functions -- 2.9 Moment Generating Functions -- 2.10 Transformation of Variables -- 2.11 Summary -- Chapter 3. Special Discrete Distributions -- 3.0 Introduction -- 3.1 Discrete Uniform -- 3.2 Bernoulli Distribution -- 3.3 Binomial Distribution -- 3.4 Multinomial Distribution -- 3.5 Hypergeometric Distribution -- 3.6 Geometric Distribution -- 3.7 Negative Binomial Distribution -- 3.8 Poisson Distribution -- 3.9 Summary -- Chapter 4. Special Continuous Distributions -- 4.0 Introduction -- 4.1 Continuous Uniform Distribution -- 4.2 Gamma Function -- 4.3 Gamma Family (Exponential, Chi-Square, Gamma) -- 4.4 Exponential Distribution -- 4.5 Chi-Square Distribution -- 4.6 Normal Distribution -- 4.7 Student t Distribution -- 4.8 Beta Distribution -- 4.9 Weibull Distribution -- 4.10 F Distribution -- 4.11 Summary -- Chapter 5. Sampling, Data Displays, Measures of Central Tendencies, Measures of Dispersion, and Simulation -- 5.0 Introduction -- 5.1 Data Displays -- 5.2 Measures of Location -- 5.3 Measures of Dispersion -- 5.4 Joint Distribution of X-and S2 -- 5.5 Simulation of Random Variables -- 5.6 Using Monte Carlo for Integration.

5.7 Order Statistics -- 5.8 Summary -- Chapter 6. Point and Interval Estimation -- 6.0 Introduction -- 6.1 Unbiased Estimators and Point Estimates -- 6.2 Methods of Finding Point Estimates -- 6.3 Interval Estimates (Confidence Intervals) -- 6.4 Prediction Intervals -- 6.5 Central Limit Theorem (Revisited) -- 6.6 Parametric Bootstrap Estimation -- 6.7 Summary -- Chapter 7. Hypothesis Testing -- 7.0 Introduction -- 7.1 Terminology in Statistical Tests of Hypotheses -- 7.2 Hypothesis Tests: Means -- 7.3 Hypothesis Tests: Proportions -- 7.4 Hypothesis Tests for Difference between Two Means: Small Samples (n < 30) a2 Known -- 7.5 Hypothesis Test with Paired Samples -- 7.6 Hypothesis Tests: Variances -- 7.7 Hypothesis Tests for Independence, Homogeneity, and Goodness of Fit -- 7.8 Summary -- Chapter 8. Regression -- 8.0 Introduction -- 8.1 Review of Joint and Conditional Densities -- 8.2 Simple Linear Regression -- 8.3 Distribution of Estimators with Inference on Parameters -- 8.4 Variation -- 8.5 Residual Analysis -- 8.6 Convertible Nonlinear Forms for Linear Regression -- 8.7 Polynomial Regression -- 8.8 Multiple Linear Regression -- 8.9 Multiple Regression Techniques -- 8.10 Correlation Analysis -- 8.11 Summary -- Chapter 9. Analysis of Variance -- 9.0 Introduction -- 9.1 Single-Factor Analysis -- 9.2 Two-Way ANOVA without Replication -- 9.3 Two-Way ANOVA with Replication -- 9.4 Multiple Comparisons of Treatment Means -- 9.5 ANOVA and Regression -- 9.6 Analysis of Means (ANOM) -- 9.7 Summary -- Chapter 10. Nonparametric Statistics -- 10.0 Introduction -- 10.1 The Sign Test -- 10.2 Nonparametric Bootstrap Estimation -- 10.3 The Sign Test for Paired Data -- 10.4 The Wilcoxon Signed-Rank Test -- 10.5 Wilcoxon-Mann-Whitney (WMW) Rank Test for Two Samples -- 10.6 Spearman Rank Order Correlation Coefficient -- 10.7 Kendall's Rank Correlation Coefficient (τ).

10.8 Nonparametric Tests for Regression -- 10.9 Nonparametric Tests for ANOVA -- 10.10 Runs Test -- 10.11 Randomization Tests -- 10.12 Summary -- Appendix A: Introduction to the Software Environment -- Appendix B: Statistical Tables -- References -- Index.

Probability & Statistics with Integrated Software Routines is a calculus-based treatment of probability concurrent with and integrated with statistics through interactive, tailored software applications designed to enhance the phenomena of probability and statistics. The software programs make the book unique. The book comes with a CD containing the interactive software leading to the Statistical Genie. The student can issue commands repeatedly while making parameter changes to observe the effects. Computer programming is an excellent skill for problem solvers, involving design, prototyping, data gathering, testing, redesign, validating, etc, all wrapped up in the scientific method. See also: CD to accompany Probability and Stats with Integrated Software Routines (0123694698) * Incorporates more than 1,000 engaging problems with answers * Includes more than 300 solved examples * Uses varied problem solving methods.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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