JSS2 Third Term Mathematics Lesson Note – Data Presentation

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WEEK 8

TOPIC: DATA PRESENTATION

CONTENT:

• Data and Types of Data
• Presentation of data

(i) Frequency tables: ungrouped and grouped.

(ii) Pie Chart: construction and interpretation.

Data and Types of Data

The word data means information, which is usually given in the form of numbers or facts. Data may be categorized into two major groups, namely;

a) Qualitative / Categorical data. They are non-numerical and are described only in words. Examples are names, places, color, taste, opinions, and brightness.

b) Quantitative data: They are numerical data which are usually given in form of a number or measurement. Examples are number of cars, height of people, number of schools, number of admissions, etc. Quantitative data can be further classified into:

1. i) Discrete data: They are obtained usually by counting and not by measurements. Most often they are whole numbers and not fractions / decimal numbers. The sense is that we can only say we have 6 houses and not 6 ½ houses; we have 4 boys and not Thus, discrete data have certain definite or exact values.
2. ii) Continuous data: They are data which are obtained by measurements. They can take any values within a given range, including fractions and decimals. Continuous data concerns more with precision of figures or numbers’ measurements, perhaps using instrument. Examples of continuous data are heights, distances, temperature, areas, perimeters, volumes, density, mass, angles, etc.  This is so because these may not be whole numbers in most practical situations.

Presentation of Data

Ordered Presentation of data is the arrangement of data in a way that will make them look organized and more presentable. Ordered presentation of data also makes statistical data easy to read, understand and interpret. Data containing numbers can be presented in an ordered format through:

• Sorting
• Use of frequency table

SORTING

This involves arranging data either from the least to the highest (increasing or rank order) and vice versa. When data are not sorted out and not arranged to taste, we say they are still in the raw

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