Chapter 4 Displaying Quantitative Data

*histograms*stem-and-leaf plots

*dotplot*shape, center, spread

Histogram

• displays the distribution of QUANTITATIVE data in bins

• the height of each bin represents the count of data values

• bins have to have equal size intervals• there should be NO spaces between the bins

Examples of Histograms

How to Make a Histogram• Slice up the entire span of values covered by the

quantitative variable into equal width piles called bins (remember they need to be equal intervals)

• Count the number of values that fall into each bin– data values that fall on the boarder of bins go in the higher

bin

• Be sure to label each axis (variable names and scales)

• The bins and the count in each bin give the distribution of the quantitative variable

Stem-and-Leaf Plots

Key: 5|3 = 5.3

Stem – and – Leaf Plots

• Always make a key• Write numbers the same size and equally

spaced (area principle)

• More on stem-and-leaf plots coming Friday

Dotplots

• simple display• place a dot along an axis for each case in the

data

Quantitative Data Condition

• The data are values of a quantitative variable whose units are known

• Always check before making a histogram, stem-and-leaf plot, or a dotplot

Describing Data• Shape: – how many bumps are there?

• Bumps are called MODES (unimodal (1 bump), bimodal (2), multimodal ( > 3)

• are there no bumps? Flat tops are called uniform

– Is there symmetry?• symmetric – fold in half• skewed – tails to one side (skewed in that direction)

– Any thing unusual?• outliers – any points that stand away from the rest of the

data • gaps

Describing Data (cont)

• Center– If you had to pick a single number to describe all the data

• for now these are just estimates

• Spread– Is the data tightly clustered around the center?

• for now this will be described informally

VARIATION MATTERS!!!!