Statistics for Science and Engineering
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BeschreibungStatistics for Science and Engineering was written for an introductory one or two semester course in probability and statistics for junior or senior level students. It is an introduction to the statistical analysis of data that arise from experiments, sample surveys, or other observational studies. It focuses on topics that are frequently used by scientists and engineers, particularly the topics of regression, design of experiments, and statistical process control. Graphs and Statistics, Random Variables and Probability Distributions, Estimation and Hypothesis Testing, Simple Linear Regression-Summarizing Data with Equations, Multiple Linear Regression, Design of Science and Engineering Experiments, Statistical Process Control For all readers interested in statistics for science and engineering.
Inhaltsverzeichnis1. Graphs and Statistics. Sampling. What is Statistics About? What Happens When We Take Samples? Some Graphic Displays of Samples. The Variance. A Look Ahead. Chapter Summary. 2. Random Variables and Probability Distributions. Introduction. An Example of Random Sampling. Permutations and Combinations. Distribution of Sample Means. Probability. Conditional Probability and Independence. Random Variables and Probability Distributions. Binomial Random Variable. Normal Probability Density Function. Normal Approximation to the Binomial. The Central Limit Theorem. Chi-Squared Distribution. Bivariate Random Variables. Chapter Review. 3. Estimation and Hypothesis Testing. Introduction. Maximum Likelihood. Confidence Intervals. Student t Distribution. Difference Between Proportions. Confidence Intervals for the Variance. The F Distribution. Hypothesis Testing. Confidence Intervals and Tests of Hypotheses. Tests on Unknown. Tests on Proportions and Variances. Constructing Best Tests: Neyman-Pearson Lemma. Tests on Two Samples. Sample Size and Type II Errors. Tests for Categorical Data. Chapter Summary. 4. Simple Linear Regression- Summarizing Data with Equations. Introduction. Least Squares. A Linear Model. Properties of Least Squares Estimators. A Test for Linearity. Correlation. Estimation and Prediction. Regression Through the Origin. Influential Observations. Testing for Normality. Checking the Assumptions. Fitting Other Linear Models. Chapter Review. 5. Multiple Linear Regression. Introduction. Two Predictors. Analysis of Variance. Variances, Covariances, Confidence Intervals, and Tests. Correlation and the Coefficient of Determination. Polynomial and Other Regression Models. The General Case. Significant Variables and Influential Observations. Model Building- Stepwise Regression. Response Surfaces. Chapter Review. 6. Design of Science and Engineering Experiments. Introduction. An Example. Some Weighing Designs. One-Way Classification. Blocking. Two-Way Classifications. Factorial Experiments. Latin Square Designs. Balanced Incomplete Block Diagrams. Fractional Factorial Designs. Chapter Review. 7. Statistical Process Control. Introduction. Example 1. Control Chart for X Bar. Control Charts for R and s. Control Charts for Attributes. Some Characteristics of Control Charts. Cumulative Sum Control Charts. Acceptance Sampling. Chapter Review.
Untertitel: Sprache: Englisch.
Verlag: ADDISON WESLEY PUB CO INC
Erscheinungsdatum: November 2001
Seitenanzahl: 488 Seiten