Types of data
Categorial data: A set of data is said to be categorical if the values or observations belonging to it can be sorted according to category. Each value is chosen from a set of non-overlapping categories. For example, shoes in a cupboard can be sorted according to colour: the characteristic 'colour' can have non-overlapping categories 'black', 'brown', 'red' and 'other'.
Nominal data: Set of data is said to be nominal if the values / observations belonging to it can be assigned a code in the form of a number where the numbers are simply labels. You can count but not order or measure nominal data.
Ordinal data: A set of data is said to be ordinal if the values / observations belonging to it can be ranked (put in order) or have a rating scale attached. You can count and order, but not measure, ordinal data.
Discrete data: A set of data is said to be discrete if the values / observations belonging to it are distinct and separate, i.e. they can be counted (1,2,3,....).
Continuous data: A set of data is said to be continuous if the values / observations belonging to it may take on any value within a finite or infinite interval. You can count, order and measure continuous data. For example height, weight, temperature.
frequency: The ratio of the number of occurrences of some event to the number of opportunities for its occurrence.
Ratio: The relation between two quantities expressed as the quotient of one divided by the other:
The ratio of 7 to 4 is written 7:4 or 7/4.
population risk: A population is any entire collection of people, animals, plants or things from which we may collect data. It is the entire group we are interested in, which we wish to describe or draw conclusions about.
Data displays
Bar graphs
A bar graph is a visual display used to compare the amounts or frequency of occurrence of different characteristics of data. This type of display allows us to:
There are many characteristics of bar graphs that make them useful. Some of these are that:
- They make comparisons between different variables very easy to see.
- They clearly show trends in data, meaning that they show how one variable is affected as the other rises or falls.
- Given one variable, the value of the other can be easily determined.
A bar graph (or chart) is used to display categorial (nominal) information. Bar graphs can have horizontal bars or vertical bars. consider the bar chart below. Note there is no scale on the axis showing the categories (horizontal in this case). gaps are left between the bars to emphasise that we are not dealing with continuous data. Since the dependent variable has a natural zero point (i.e., absolute or ratio), all of the bars are anchored to the horizontal axis, giving a common point of measurement.We can simply read values from the graph; for example, 21 000 of the defect cars are produced from factory A.
When reading a bar graph there are several things we must pay attention to: the graph title, two axes, including axes labels and scale, and the bars. Since bar graphs are used to graph frequencies or amounts of data in discrete groups, we will need to determine which axis is the grouped data axis, as well as what the specific groups are, and which is the frequency axis.
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