David Levine, Patricia Ramsey, Robert Smidt

Applied Statistics for Engineers and Scientists

Using Microsoft Excel & Minitab

• Broschiertes Buch

Produktbeschreibung

For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.

Produktdetails

• Verlag: Pearson Education (US)
• United States ed
• Seitenzahl: 736
• Erscheinungstermin: 10. Oktober 2000
• Englisch
• Abmessung: 267mm x 207mm x 32mm
• Gewicht: 1551g
• ISBN-13: 9780134888019
• ISBN-10: 0134888014
• Artikelnr.: 24533322

Inhaltsangabe

1. Introduction to Statistics and Quality Improvement.
What Is Statistics? Why Study Statistics? Statistical Thinking:
Understanding and Managing Variability. Variables, Types of Data, and
Levels of Measurement. Operational Definitions. Sampling. Statistical and
Spreadsheet Software. Introduction to Quality. A History of Quality and
Productivity. Themes of Quality Management. The Connection between Quality
and Statistics. Appendix 1.1: Basics of the Windows User Interface.
Appendix 1.2: Introduction to Microsoft Excel. Appendix 1.3: Introduction
to MINITAB.
2. Tables and Charts.
Introduction and the History of Graphics. Some Tools for Studying a
Process: Process Flow Diagrams and Cause-and-Effect Diagrams. The
Importance of the Time-Order Plot. Tables and Charts for Numerical Data.
Checksheets and Summary Tables. Concentration Diagrams. Graphing
Categorical Data. Tables and Charts for Bivariate Categorical Data.
Graphical Excellence. Appendix 2.1: Using Microsoft Excel for Tables and
Charts. Appendix 2.2: Using MINITAB for Tables and Charts.
3. Describing and Summarizing Data.
Introduction: What's Ahead. Measures of Central Tendency, Variation, and
Shape. The Box-and-Whisker Plot. Appendix 3.1: Using Microsoft Excel for
Descriptive Statistics. Appendix 3.2: Using MINITAB for Descriptive
Statistics.
4. Probability and Discrete Probability Distributions.
Introduction. Some Rules of Probability. The Probability Distribution. The
Binomial Distribution. The Hypergeometric Distribution. The Negative
Binomial and Geometric Distributions. The Poisson Distribution. Summary and
Overview. Appendix 4.1: Using Microsoft Excel for Probability and
Probability Distributions. Appendix 4.2: Using MINITAB for Probability and
Probability Distributions.
5. Continuous Probability Distributions and Sampling Distributions.
Introduction to Continuous Probability Distributions. The Uniform
Distribution. The Normal Distribution. The Standard Normal Distribution as
an Approximation to the Binomial and Poisson Distributions. The Normal
Probability Plot. The Lognormal Distribution. The Exponential Distribution.
The Weibull Distribution. Sampling Distribution of the Mean. Sampling
Distribution of the Proportion. Summary. Appendix 5.1: Using Microsoft
Excel for Continuous Probability Distributions and Sampling Distributions.
Appendix 5.2: Using MINTAB for Continuous Probability Distributions and
Sampling Distributions.
6. Process Control Charts I: Basic Concepts and Attribute Charts.
Introduction to Control Charts and Their Applications. Introduction to the
Theory of Control Charts. Introduction to Attributes Control Charts. np
and p Charts. Area of Opportunity Charts (c Charts and u Charts). Summary.
Appendix 6.1: Using Microsoft Excel for Attribute Control Charts. Appendix
6.1: Using Microsoft Excel for Attribute Control Charts. Appendix 6.2:
Using MINITAB for Attribute Control Charts.
7. Statistical Process Control Charts II: Variables Control Charts.
Introduction to Variables Control Charts. Rational Subgroups and Sampling
Decisions. Control Charts for Central Tendency (X Charts) and Variation (R
and s Charts). Control Charts for Individual Values (X Charts). Special
Considerations with Variable Charts. The Cumulative Sum (CUSUM) and
Exponentially Weighted Moving Average (EWMA) Charts. Process Capability.
Summary. Appendix 7.1: Using Microsoft Excel for Variables Control Charts.
Appendix 7.2: Using MINITAB for Variables Control Charts.
8. Estimation Procedures.
Introduction. Properties of Estimators. Confidence Interval Estimation of
the Mean. Confidence Interval Estimation for the Variance. Prediction
Interval Estimate for a Future Individual Value. Tolerance Intervals.
Confidence Interval Estimation for the Proportion. Summary. Appendix 8.1:
Using Microsoft Excel for Confidence Interval Estimation. Appendix 8.2:
Using MINITAB for Confidence Interval Estimation.
9. Introduction to Hypothesis Testing.
Introduction. Basic Concepts of Hypothesis-Testing. One-Sample Tests for
the Mean. t Test for the Difference between the Means of Two Independent
Groups. Testing for the Difference between Two Variances. The Repeated
Measures or Paired t Test. Chi-Square Test for the Differences among
Proportions in Two or More Groups. X2 Test of Hypothesis for the Variance
or Standard Deviation (Optional Topic). Wilcoxon Rank Sum Test for the
Difference between Two Medians (Optional Topic). Summary. Appendix 9.1:
Using Microsoft Excel for Hypothesis Testing. Appendix 9.2: Using MINITAB
for Hypothesis Testing.
10. The Design of Experiments: One Factor and Randomized Block Experiments.
Introduction and Rationale. Historical Background. The Concept of
Randomization. The One-Way Analysis of Variance (ANOVA). The Randomized
Block Model. Kruskal-Wallis Rank Test for Differences in c Medians
(Optional Topic). Appendix 10.1: Using Microsoft Excel for the Analysis of
Variance. Appendix 10.2: Using MINITAB for the Analysis of Variance.
11. The Design of Experiments: Factorial Designs.
Two-Factor Factorial Designs. Factorial Designs Involving Three or More
Factors. The Fractional Factorial Design. The Taguchi Approach. Summary and
Overview. Appendix 11.1: Using Microsoft Excel for the Two-Factor Factorial
Design. Appendix 11.2: Using MINITAB for the Two-Factor Factorial Designs.
12. Simple Linear Regression and Correlation.
Introduction. Types of Regression Models. Determining the Simple Linear
Regression Equation. Measures of Variation in Regression and Correlation.
Assumptions of Regression and Correlation. Residual Analysis. Inferences
about the Slope. Confidence and Prediction Interval Estimation. Pitfalls in
Regression and Ethical Issues. Computations in Simple Linear Regression.
Correlation—Measuring the Strength of the Association. Appendix 12.1: Using
Microsoft Excel for Simple Linear Regression and Correlation. Appendix
12.2: Using MINITAB for Simple Linear Regression and Correlation.
13. Multiple Regression.
Developing the Multiple-Regression Model. Residual Analysis for the
Multiple-Regression Model. Testing for the Significance of the
Multiple-Regression Model. Inferences Concerning the Population Regression
Coefficients. Testing Portions of the Multiple-Regression Model. The
Quadratic Curvilinear Regression Model. Dummy-Variable Models. Using
Transformations in Regressions Models. Collinearity. Model-Building.
Pitfalls in Multiple Regression. Appendix 13.1: Using Microsoft Excel for
Multiple-Regression Models. Appendix 13.2: Using MINITAB for Multiple
Models Regression.
Appendices.
Appendix A: Tables. Appendix B: Statistical Forms. Appendix C:
Documentation for the Data Files. Appendix D: Installing the PHStat
Microsoft Excel Add-In. Appendix E: Answers to Selected Odd Problems.
Index.