SPSS · Exploratory data analysis and visualization

Introduction

What this guide covers

Comprehensive treatise on exploratory workflow in SPSS: from data matrix architecture and quality auditing, to descriptive statistics, normality assessment, outlier detection, and reasoned graph construction — with syntax, annotated outputs, and step-by-step clinical exercises.

Overview

Topics covered

• Introduction
• Exploratory Data Analysis and Visualization in IBM SPSS Statistics
• Fundamentals of Exploratory Data Analysis
• 1.1 — The four pillars of EDA according to Tukey
• 1. Revelation
• 2. Residuals (Residual)

Related concepts

Main connections

• Skewness & kurtosis
• Variance & standard deviation
• Median & robust location
• Missing data & multiple imputation
• Calculus & differentiation
• Quantiles & percentiles

Compatible notation

Mathematical sample in LaTeX

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