Statistics for Engineering and the Sciences Student Solutions Manual / Edition 6

Statistics for Engineering and the Sciences Student Solutions Manual / Edition 6

ISBN-10:
1498731821
ISBN-13:
9781498731829
Pub. Date:
09/20/2016
Publisher:
Taylor & Francis
ISBN-10:
1498731821
ISBN-13:
9781498731829
Pub. Date:
09/20/2016
Publisher:
Taylor & Francis
Statistics for Engineering and the Sciences Student Solutions Manual / Edition 6

Statistics for Engineering and the Sciences Student Solutions Manual / Edition 6

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Overview

A companion to Mendenhall and Sincich's Statistics for Engineering and the Sciences, Sixth Edition, this student resource offers full solutions to all of the odd-numbered exercises.


Product Details

ISBN-13: 9781498731829
Publisher: Taylor & Francis
Publication date: 09/20/2016
Edition description: Solution M
Pages: 458
Product dimensions: 6.90(w) x 9.90(h) x 0.60(d)

About the Author

William Mendenhall was a professor emeritus in the Statistics Department and the first chairman of the department at the University of Florida. Dr. Mendenhall published articles in top statistics journals and was a prolific author of statistics textbooks.

Terry L. Sincich is an associate professor in the Information Systems Decision Sciences Department at the University of South Florida, where he teaches introductory statistics at the undergraduate level and advanced statistics courses at the doctoral level. He has won numerous teaching awards, including the Kahn Teaching Award and Outstanding Teacher Award. Dr. Sincich is a member of the American Statistical Association and the Decision Sciences Institute. His research interests include applied statistical analysis and statistical modeling.

Table of Contents

Introduction. Descriptive Statistics. Probability. Discrete Random Variables. Continuous Random Variables. Bivariate Probability Distributions and Sampling Distributions. Estimation Using Confidence Intervals. Tests of Hypotheses. Categorical Data Analysis. Simple Linear Regression. Multiple Regression Analysis. Model Building. Principles of Experimental Design. The Analysis of Variance for Designed Experiments. Nonparametric Statistics. Statistical Process and Quality Control. Product and System Reliability.
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