Book description
Understand the concepts and techniques of analysis while learning to reason statistically.
Being an effective analyst requires that you know how to properly define a problem and apply suitable statistical techniques, as well as clearly and honestly communicate the results with information-rich visualizations and precise language. Being a well-informed consumer of analyses requires the same set of skills so that you can recognize credible, actionable research when you see it.
Robert Carver's Practical Data Analysis with JMP, Second Edition uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. It enables you to discriminate among and to use fundamental techniques of analysis, enabling you to engage in statistical thinking by analyzing real-world problems. “Application Scenarios†at the end of each chapter challenge you to put your knowledge and skills to use with data sets that go beyond mere repetition of chapter examples, and three new review chapters help readers integrate ideas and techniques. In addition, the scope and sequence of the chapters have been updated with more coverage of data management and analysis of data.
The book can stand on its own as a learning resource for professionals or be used to supplement a standard college-level introduction-to-statistics textbook. It includes varied examples and problems that rely on real sets of data, typically starting with an important or interesting research question that an investigator has pursued. Reflective of the broad applicability of statistical reasoning, the problems come from a wide variety of disciplines, including engineering, life sciences, business, economics, among
Practical Data Analysis with JMP, Second Edition introduces you to the major platforms and essential features of JMP and will leave you with a sufficient background and the confidence to continue your exploration independently.
This book is part of the SAS Press program.
Table of contents
- About This Book
- About The Author
- Chapter 1 Getting Started: Data Analysis with JMP
- Chapter 2 Data Sources and Structures
- Chapter 3 Describing a Single Variable
- Chapter 4 Describing Two Variables at a Time
-
Chapter 5 Review of Descriptive Statistics
- Overview
- The World Development Indicators
- Questions for Analysis
- Applying an Analytic Framework
- Preparation for Analysis
- Univariate Descriptions
- Explore Relationships with Graph Builder
- Further Analysis with the Multivariate Platform
- Further Analysis with Fit Y by X
- Summing Up: Interpretation and Conclusions
- Visualizing Multiple Relationships
-
Chapter 6 Elementary Probability and Discrete Distributions
- Overview
- The Role of Probability in Data Analysis
- Elements of Probability Theory
- Contingency Tables and Probability
- Discrete Random Variables: From Events to Numbers
- Three Common Discrete Distributions
- Simulating Random Variation with JMP
- Discrete Distributions as Models of Real Processes
- Application
- Chapter 7 The Normal Model
- Chapter 8 Sampling and Sampling Distributions
- Chapter 9 Review of Probability and Probabilistic Sampling
- Chapter 10 Inference for a Single Categorical Variable
- Chapter 11 Inference for a Single Continuous Variable
- Chapter 12 Chi-Square Tests
- Chapter 13 Two-Sample Inference for a Continuous Variable
- Chapter 14 Analysis of Variance
- Chapter 15 Simple Linear Regression Inference
- Chapter 16 Residuals Analysis and Estimation
- Chapter 17 Review of Univariate and Bivariate Inference
- Chapter 18 Multiple Regression
- Chapter 19 Categorical, Curvilinear, and Non-Linear Regression Models
- Chapter 20 Basic Forecasting Techniques
- Chapter 21 Elements of Experimental Design
- Chapter 22 Quality Improvement
- Appendix A Data Sources
- Appendix B Data Management
- Bibliography
- Index
Product information
- Title: Practical Data Analysis with JMP, Second Edition, 2nd Edition
- Author(s):
- Release date: July 2014
- Publisher(s): SAS Institute
- ISBN: 9781629592657
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