Practical Data Analysis with JMP,Third Edition
Authors: Robert Carver
ISBN-10: 1642956104
ISBN-13: 9781642956108
Edition 版本: 3
Released: 2019-10-11
Print Length 页数: 442 pages
Book Description
Master the concepts and techniques of statistical analysis using JMP
Practical Data Analysis with JMP,Third Edition,highlights the powerful interactive and visual approach of JMP to introduce readers to statistical thinking and data analysis. It helps you choose the best technique for the problem at hand by using real-world cases. It also illustrates best-practice workflow throughout the entire investigative cycle,from asking valuable questions through data acquisition,preparation,analysis,interpretation,and communication of findings.
The book can stand on its own as a learning resource for professionals,or it can be used to supplement a college-level textbook for an introductory statistics course. It includes varied examples and problems using real sets of data. Each chapter typically starts with an important or interesting research question that an investigator has pursued. Reflecting the broad applicability of statistical reasoning,the problems come from a wide variety of disciplines,including engineering,life sciences,business,and economics,as well as international and historical examples.
Application Scenarios at the end of each chapter challenge you to use your knowledge and skills with data sets that go beyond mere repetition of chapter examples.
New in the third edition,chapters have been updated to demonstrate the enhanced capabilities of JMP,including projects,Graph Builder,Query Builder,and Formula Depot.
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
Chapter 6: . Elementary Probability and Discrete Distributions
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
Bibliography
Index
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