#### (Slide 1)

# Lecture 3: Displaying Data

#### Chapter 2, Whitlock and Schulter, 2nd Ed

### Key questions:

## What makes a good graph?

## What makes a bad graph?

## Types of graphs for types of different data

#### (Slide 2)

# Basics Rules of plotting data

## 1) Show the raw data if possible

## 2) Show distributional info if possible

## 3) ALWAYS Include error bars around means

## 4) ALWAYS Include error bars around means

## 5) Make patterns in the data easy to see

## 6) Represent magnitude honestly

## 7) Draw graphical elements clearly

## 8) Include a legend and label things clearly

#### (Slide 3)

# Plotting Rule #1: Show the raw data

#### Compare the information content of these two graphs

#### (Slide 3.5)

# Plotting Rule #1: Show the Data

#### Multiple datasets can result in the exact same barplot & errorbars

#### Bar plots – even with error bars – therefore reveals very little about the data

#### (slide 4)

# Plotting Rule #3 & 4: Alwys use error bars for means

#### Means MUST always have an estimate of uncertainty around them

#### The range doesn’t count!

#### Typically use “standard error” OR “confidence interval”

#### Rarely use “standard deviaiton”

#### (Slide 6)

# Plotting Rule #5: Make Patterns Easy to See

## Keep it as simple as possible

## Add labels, annotations etc.

## Use both color AND pattern/shape to distinguish groups

## Avoid 3D

## Use color-blind friendly palettes

## Don’t use most of the fancy stuff in Excel!

#### (Slide 6.5)

# Plotting Rule #5: Make Patterns Easy to See example

#### (Slide 7)

# Plotting Rule #6: Represent Magnitudes Honestly

#### This plot emphasizes a certain aspect of data

#### Some critics think this is desceptive