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Statistical methods for engineers and scientists / Robert M. Bethea, Benjamin S. Duran and Thomas L. Boullion.

By: Bethea, Robert M [author]Contributor(s): Duran, Benjamin S [co-author] | Boullion, Thomas L [co-author]Material type: Text

TextPublication details: New York : Marcel Dekker, Inc., c1984Edition: Second Edition; Revised and Expanded EditionDescription: xxiii, 670 pages ; 23 cmISBN: 082477227XSubject(s): MATHEMATIC STATISTICS | PROBABILITIESLOC classification: QA 276 .B48 1984

Contents:

Chapter 1. Introduction -- Chapter 2. Probability -- Chapter 3. Distributions -- Chapter 4. Descriptive statistics -- Chapter 5. Expected values and moments -- Chapter 6. Statistical inference: estimation -- Chapter 7. Statistical inference: hypothesis testing.

Summary: This text is also useful for professional engineers and scientists especially because of its emphasis on regression, experimental design, analysis of variance, and computerized data reduction and interpretation.

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Item type	Current library	Home library	Collection	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	LRC - Annex	National University - Manila	Secondary Education - Mathematics	Relegation Room	GC QA 276 .B48 1984 c.1 (Browse shelf (Opens below))	c.1	Available		NULIB000006250
Books	LRC - Annex	National University - Manila	Secondary Education - Mathematics	Relegation Room	GC QA 276 .B48 1984 c.2 (Browse shelf (Opens below))	c.2	Available		NULIB000006251

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Previous	GC QA 273 .M35 1971 c.2 Probability, statistics and random processes /	GC QA 276 .12 .W58 1989 Statistics /	GC QA 276 .B48 1984 c.1 Statistical methods for engineers and scientists /	GC QA 276 .B48 1984 c.2 Statistical methods for engineers and scientists /	GC QA 276 .P73 1987 Asymptotic theory of statistical inference /	GC QA 276 .R64 1984 Statistical Inference /	GC QA 303 .B37 1987 c.1 Applied calculus for business and economics life sciences, and social sciences /	Next

Includes index.

This text is also useful for professional engineers and scientists especially because of its emphasis on regression, experimental design, analysis of variance, and computerized data reduction and interpretation.

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