SUMMARISING AND PRESENTING DATA

PRESENTING DATA FOR TWO CONTINUOUS MEASUREMENTS

Introduction

So far we have considered only the presentation of results for a single variable. In practice, most studies are concerned with the association between two or more variables.

The appropriate statistical method depends on the situation.

• Two variables measured on the same subject/object (e.g. peoples' heights and weights) - are these related? Usually use correlation or regression;
• One variable measured at selected values of another variable - (e.g. children's heights at different ages) Show simple trend - usually use regression;
• One variable measured at equally spaced times (or distances) but successive values highly correlated or pattern complicated (e.g. stockmarket prices) Use methods of time series analysis.

Scatterplots

A scatterplot is constructed by marking the scales of the two variables, (x, y) along horizontal and vertical axes. Each pair of measurements is plotted with a cross at the point using the measurements as coordinates. The information from a third discrete variable can be incorporated into the plot by using different plotting symbols for each category of the third variable.

The figure below shows a scatterplot of income against age for some hypothetical data. The number 2 is used to indicate a point where two data values coincide.

Scatterplot of Income versus Age

Scatterplot of Income versus Age Classified by Sex

Example - Heights and weights of 6 female STAT101 students

Student	Height(cm)	weight(kg)
1	167	60
2	170	64
3	160	57
4	152	46
5	157	55
6	160	50

First step - draw a scatter plot:

The MINITAB command for a scatter plot is: