Lecture 8Distributions

Percentiles and Boxplots

Practical Psychology 1

The Boxplot

Once these values have been calculated, this

information can be used to draw a boxplot: Also known as a “box-and-whisker” plot

Quick and easy method of checking distribution

normality/ skewness.

You need to know how to: draw boxplots by hand

Produce them in SPSS

and interpret them.

Boxplot and shape of distribution:

normal distribution

If data is normallydistributed, the boxplot

issymmetrical (i.e. the MEDIAN line isvery close to the centreof the rectangle):

Boxplot and shape of distribution:

positive skew

Note MEDIAN Position: there is a greater proportion of data on the lower end of the scale

Note MEDIAN Position:there is a greater proportion of data on the upper end of the scale

Boxplot and shape of distribution: negative skew

Boxplots in SPSS

Example: comparing male and female scores

Producing a Boxplot in SPSS

SPSS menu Graphs Legacy Dialogs Boxplot Simple Summaries of groups of cases Define

Drag the continuous

variable to the

“Variable box” and

the categorical

(e.g. gender) to

the “Category

Axis” box.

Each group is represented by a rectangle, in which 50% of the scores lie (this is the interquartile range, IQR)

Y axis = scores (DV)

The central line is the MEDIAN (Q2)

X-axis: (IV) group: males vs. females

Some terminology

H-spread = IQR (i.e., Q3-Q1)

Upper Whisker = largest value

Median (Q2)

Lower Whisker = smallest value

Lower Quartile (Q1) {lower Hinge}

Upper Quartile (Q3) {upper Hinge}

Percentiles in SPSS

Analyze >Descriptive Statistics > Explore

Put the IV (gender) in the factor list and the DV (scores) in the dependent list

Menu on the right: Statistics > tick “Percentiles”

“Continue”

Percentiles Output