# Content Tagged “Exploratory Data Analysis”

Exploratory data analysis (or descriptive statistics) is used to summarize the collected data. EDA consists of organizing and summarizing the raw data,
discovering important features and patterns in the data and any striking deviations from those patterns, and then interpreting our findings in the context of the problem.

This can be useful for describing the distribution of a single variable (center, spread, shape, outliers), checking data (for errors or other problems), checking assumptions to more complex statistical analyses, and investigating relationships between variables.

## Describing Distributions

Published: Jun 28th, 2013

Features of Distributions of Quantitative Variables Shape (Symmetry/Skewness, Modality) Center Spread Outliers Let’s Summarize CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, […]

## The Big Picture of Statistics

Published: Jun 12th, 2013

View Lecture Slides with Transcript – The Big Picture of Statistics Video (4:59) This document is linked from The Big Picture.

## Linear Relationships – Linear Regression

Published: Dec 24th, 2012

IMPORTANT: The methods covered in this section on linear regression are only applicable for LINEAR relationships.   Summarizing the Pattern of the Data with a Line In General Let’s Summarize CO-4: Distinguish among […]

## Summary (Unit 1)

Published: Aug 21st, 2012

(Optional) Outside Reading:  Look at the Data! (≈1200 words) (Optional) Outside Reading:  Creating Data Files (≈1200 words) This summary provides a quick recap of the material in the Exploratory Data Analysis unit. […]

## Linear Relationships – Correlation

Published: Aug 21st, 2012

IMPORTANT: The methods covered in this section on correlation are only applicable for LINEAR relationships.   Introduction The Correlation Coefficient — r Interpretation Properties of r CO-4: Distinguish among different measurement scales, […]

## Scatterplots

Published: Aug 21st, 2012

Creating Scatterplots Interpreting Scatterplots Direction Form Strength A Labeled (or Grouped) Scatterplot Let’s Summarize CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these […]

## Case Q-Q

Published: Aug 21st, 2012

CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, and interpret the results. LO 4.20: Classify a data analysis situation involving two variables […]

## Case C-C

Published: Aug 21st, 2012

Two Categorical Variables Contingency Tables Finding Conditional (Row and Column) Percents Let’s Summarize CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, […]

## Case C-Q

Published: Aug 21st, 2012

Categorical Explanatory and Quantitative Response Let’s Summarize CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, and interpret the results. LO 4.20: Classify […]

## The “Normal” Shape

Published: Aug 21st, 2012

The Standard Deviation Rule Visual Methods of Assessing Normality Standardized Scores (Z-Scores) CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, and […]