CHAPTER 1: DATA AND STATISTICS
1. Data: are the facts and figures collected, analysed and summarised for presentation and
interpretations.
1.1. Elements, Variables and Observations
1.1.1. Elements: the entities on which data is collected
1.1.2. Variables: characteristics of interests for the elements
1.1.3. Set of measurements obtained for a particular element.
1.2. Scales of Measurement: determines the amount of information contained in the data and it
indicate the most suitable data summarisation and statistical analysis.
2. Types of Scales of Measurement:
2.1. Nominal Scale: data for a variable consists of names or labels which is used to identify an
attribute of an element.
2.2. Ordinal Scale: the data exhibits the properties of nominal data & the order/rank of the data is
meaningful.
2.3. Interval Scale: data that has all properties of ordinal scale & interval between values is expressed
in terms of fixed measurements.
2.4. Ratio Scale: data has all properties of interval data and the ratio of two value is meaningful.
CLASSIFICATION OF DATA: QUANTITIVE & QUALITATIVE DATA
QUANTITAVE DATA QUALITATIVE DATA
Has numerical meaning, i.e. deals with Has no numerical meaning, i.e. deals with
numbers.
words.
Can do calculations with data. Cannot do calculations with data.
SCALES OF MEASUREMENT:
Ratio scale- Data which has decimals. Nominal Data- data classified into
E.g. height and weight. categories. E.g. Category is Sport and
data includes soccer, cricket etc.
Interval scale- Data which is integer only. Ordinal Data- data which has ranking.
E.g. Temperature and class ranking. E.g. High and low etc.
, TYPES OF STATISTICS
Descriptive:
Summarises and describes data which can be:
In a table.
Plotted on a graph.
On a stem and leaf plot
Inferential:
Uses data from a sample to make estimates and test hypothesis about the
characteristics of a population.
Population:
A set of all elements of interest in a particular study.
Sample:
A subset of the population.
1. Data: are the facts and figures collected, analysed and summarised for presentation and
interpretations.
1.1. Elements, Variables and Observations
1.1.1. Elements: the entities on which data is collected
1.1.2. Variables: characteristics of interests for the elements
1.1.3. Set of measurements obtained for a particular element.
1.2. Scales of Measurement: determines the amount of information contained in the data and it
indicate the most suitable data summarisation and statistical analysis.
2. Types of Scales of Measurement:
2.1. Nominal Scale: data for a variable consists of names or labels which is used to identify an
attribute of an element.
2.2. Ordinal Scale: the data exhibits the properties of nominal data & the order/rank of the data is
meaningful.
2.3. Interval Scale: data that has all properties of ordinal scale & interval between values is expressed
in terms of fixed measurements.
2.4. Ratio Scale: data has all properties of interval data and the ratio of two value is meaningful.
CLASSIFICATION OF DATA: QUANTITIVE & QUALITATIVE DATA
QUANTITAVE DATA QUALITATIVE DATA
Has numerical meaning, i.e. deals with Has no numerical meaning, i.e. deals with
numbers.
words.
Can do calculations with data. Cannot do calculations with data.
SCALES OF MEASUREMENT:
Ratio scale- Data which has decimals. Nominal Data- data classified into
E.g. height and weight. categories. E.g. Category is Sport and
data includes soccer, cricket etc.
Interval scale- Data which is integer only. Ordinal Data- data which has ranking.
E.g. Temperature and class ranking. E.g. High and low etc.
, TYPES OF STATISTICS
Descriptive:
Summarises and describes data which can be:
In a table.
Plotted on a graph.
On a stem and leaf plot
Inferential:
Uses data from a sample to make estimates and test hypothesis about the
characteristics of a population.
Population:
A set of all elements of interest in a particular study.
Sample:
A subset of the population.
