Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. Statistics for Engineers and Scientists features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.
The text features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly and the use of contemporary real world data sets to help motivate students and show direct connections to industry and ...
Reviews fundamental concepts and applications of probability and statistics. After a general overview, it considers special types of random variables, using examples which illustrate their wide variety of applications. Also...
This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational ...
The book also features: Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and ...
This book provides direction in constructing regression routines that can be used with worksheet software on personal computers.
Statistics for Engineers and Scientists
The text features a unique approach accentuated by an engaging writing style that explains difficult concepts clearly.
Nicholas P. Cheremisinoff, Louise Ferrante. of the estimate . For example , if e , = 0.15 , the scatter ing about the average estimate would have a standard deviation of 10 % of the value . Also , for es = 0.15 , the estimate is ...
Robert M. Bethea ... edited by B. S. Weir Nonlinear Regression Modeling: A Unified Practical Approach, David A. Ratkowsky Attribute Sampling Plans, Tables of Tests and Confidence Limits for Proportions, Robert E. Odeh and D. B. Owen ...
While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.