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Statistical Methods and Data Analysis (E-Book)

An Introduction to Statistical Methods
and Data Analysis

Fifth Edition
R. Lyman Ott
Michael Longnecker
Texas A&M University

Introduction: 

An Introduction to Statistical Methods and Data Analysis, Fifth Edition, is a textbook for advanced undergraduate and graduate students from a variety of disciplines. It is intended to prepare students to deal with solving problems encountered in research projects, decision making based on data, and general life experiences beyond the classroom and university setting. We presume students using this book have a minimal mathematical background (high school algebra) and no prior coursework in statistics. The first eleven chapters present the material typically covered in an introductory statistics course. However, we have provided case studies and examples that connect the statistics concepts to problems of a very practical nature. The remaining chapters cover regression modeling and design of experiments. We develop and illustrate the statistical techniques and thought process needed to design a research study or experiment and then analyze the data collected using an intuitive and proven four-step approach.

Major Features
Learning from Data We approach the study of statistics by using a four-step process to learn from data:
1. Design the data collection process.
2. Prepare the data for analysis.
3. Analyze the data.
4. Communicate the results of the data analysis.
Case Studies To demonstrate the relevance and importance of statistics in solving real-world problems, we introduce the major topic of most chapters using a case study. This approach aims to assist in overcoming the natural initial perception held by many people that statistics is ‘‘just another math course.’’ Introducing major topics with case studies provides a focus of the central nature of applied statistics. We hope these case studies on a wide variety of research- and businessrelated topics will give the reader an enthusiasm for the broad applicability of statistics and the four-step statistical thought process that we have found and used throughout many years of teaching, consulting, and R&D management. The following case studies from the text are typical of those used throughout.

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