TAILIEUCHUNG - Exploratory Data Analysis_1

1. Exploratory Data Analysis 1. Exploratory Data Analysis This chapter presents the assumptions, principles, and techniques necessary to gain insight into data via EDA--exploratory data analysis. 1. EDA Introduction 1. What is EDA? 2. EDA vs Classical & Bayesian 3. EDA vs Summary 4. EDA Goals 5. The Role of Graphics 6. An EDA/Graphics Example 7. General Problem Categories 3. EDA Techniques 1. Introduction 2. Analysis Questions 3. Graphical Techniques: Alphabetical 4. Graphical Techniques: By Problem Category 5. Quantitative Techniques 6. Probability Distributions Detailed Chapter Table of Contents References Dataplot Commands for EDA Techniques 4. EDA Case Studies 1. Introduction 2. By. | 1. Exploratory Data Analysis ENGINEERING STATISTICS HANDBOOK hW tools raids search BACK Nixf 1. Exploratory Data Analysis This chapter presents the assumptions principles and techniques necessary to gain insight into data via EDA--exploratory data analysis. 1. EDA Introduction 1. What is EDA 2. EDA vs Classical Bayesian 3. EDA vs Summary 4. EDA Goals 5. The Role of Graphics 6. An EDA Graphics Example 7. General Problem Categories 2. EDA Assumptions 1. Underlying Assumptions 2. Importance 3. Techniques for Testing Assumptions 4. Interpretation of 4-Plot 5. Consequences 3. EDA Techniques 1. Introduction 2. Analysis Questions 3. Graphical Techniques Alphabetical 4. Graphical Techniques By Problem Category 5. Quantitative Techniques 6. Probability Distributions 4. EDA Case Studies 1. Introduction 2. By Problem Category Detailed Chapter Table of Contents References Dataplot Commands for EDA Techniques sematTech rTOOLS Al s SEARCH BACK NEXT http div898 handbook eda 5 1 2006 9 56 13 AM 1. Exploratory Data Analysis ENGINEERING STATISTICS HANDBOOK hW tools raids lỉEÂtCH BACK Nixf 1. Exploratory Data Analysis - Detailed Table of Contents 1. This chapter presents the assumptions principles and techniques necessary to gain insight into data via EDA--exploratory data analysis. 1. EDA Introduction . 1. What is EDA . 2. How Does Exploratory Data Analysis differ from Classical Data Analysis . 1. Model . 2. Focus . 3. Techniques . 4. Rigor . 5. Data Treatment . 6. Assumptions . 3. How Does Exploratory Data Analysis Differ from Summary Analysis . 4. What are the EDA Goals . 5. The Role of Graphics . 6. An EDA Graphics Example . 7. General Problem Categories . 2. EDA Assumptions . 1. Underlying Assumptions . 2. Importance . 3. Techniques for Testing Assumptions . 4. Interpretation of 4-Plot . 5. Consequences . 1. Consequences of Non-Randomness .

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