# 1. Introduction to Statistics (1)

```Introduction to Statistics
Notes Prepared by Nurul Emyza Zahidi
INTRODUCTION TO STATISTICS
Statistics
Study of how information is collected, presented,
analysed and interpreted for use in making decisions.
Descriptive Statistics
Summarizing data in the form of graphs, charts
or table and techniques for obtaining numerical
summaries such as mean, median, mode,
variance and standard deviation.
Inferential Statistics
Techniques used to make or draw
the selected samples.
Primary
Data which gathered by the researcher
himself.
Data
Observation or information
that have been recorded or
collected.
Secondary
Ordinal Scale
Use ranks to give
ordering to data of
this type of scale.
*Qualitative data
Nominal Scale
Classifies data in the
form of labels or
categories.
*Qualitative data
Interval Scale
Ordered scale in
which the difference
between
measurements is
meaningful.
*Quantitative data
Scales of
measurements
Ratio Scale
Ordered scale with
meaningful
difference between
measurement and
exists a true or fixed
zero point.
*Quantitative data
NEZ/ASAH/NAK/SBS/ISS
1
Introduction to Statistics
Notes Prepared by Nurul Emyza Zahidi
SAMPLING TECHNIQUE
Probability Sampling
 Every elements in a pop. has an equal chances of being selected
 Sampling frame easily obtained
1. Simple Random Sampling
 Sample is drawn randomly from a population.
 2 basic methods:
1. Lottery Method
2. Random Number Table
Very easy to use
A very unrepresentative sample may result
if the population is not homogeneous
The numbering of the population may prove
very laborious and cumbersome
Requires only the least knowledge about a
2. Systematic Sampling

Sample is drawn systematically selected from a population.
Systematic samples can be chosen much
May results in systematic bias
more speedily
Simple and easy to draw samples and
May results in unrepresentative sample if
hence widely used
the population is not homogeneous
3. Stratified Sampling

Population is divided into group (strata) and sample is selected from each of the
group(strata)
Stratified samples can represent the
If stratified lists are not available, they can
population since from each stratum there
be costly to prepare
are representatives
A respective study can also be done on
Requires accurate information on
elements within the same strata
proportion in each stratum
4. Cluster Sampling

Population is divided into group (cluster) and sample consists of all elements
from selected group(cluster)
The cost of data collection is low if the
clusters are geographically defined
May result in an unrepresentative sample if
the chosen clusters do not consist of all the
subgroups in a population
Requires the listing of all clusters but of
May have prior knowledge of all the clusters
individuals only within cluster
5. Multi-stage Sampling
 Divide large population into stages to make the sampling process more
practical.
This technique is suitable especially if the
population of interest is very large
Cost of sampling can be reduced with little
lost information
Sampling process may become complex
Little loss of information cannot be avoided
NEZ/ASAH/NAK/SBS/ISS
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Introduction to Statistics
Notes Prepared by Nurul Emyza Zahidi
Non-probability Sampling
 Sampling frames difficult to obtained
 Generalisation about the population is not the main issue
1. Convenience Sampling

Researcher select the easiest population members from which to obtain a data.
Very widely use in studies because of its
Introduces bias in researcher’s
convenience, easy and inexpensive
classification of samples
2. Judgment Sampling
 Researcher use his/her judgement to select population members who are
good prospects for accurate information.
The cost is moderate, and sample
Introduces bias in researcher’s
guaranteed to meet a specific objective
classification of samples
3. Quota Sampling
 Researcher prescribes number of people in each of several categories
The procedure does not require any
sampling frame
Sampling process is simpler compared to
other techniques of sampling
The procedure is not random
Interviewer bias cannot be avoided
Personal Interview
Interviewer asking questions to one or more
respondents in face-to-face situation.
The interviewer can clarify any terms that are not
understood by respondents
Very costly and time consuming
Interviewer are assigned
at a strategic location to
observe and record
respondents’ behaviour.
Telephone Interview
to one or more respondents
through telephone.
Faster results since there is
no travel time between
consecutive interviews
Only limited to respondents
who have telephone facilities
Observation
Data Collection
Techniques
Observation avoids
interviewer-interviewee
bias
The observers may
wrongly interpret what the
respondent are doing
NEZ/ASAH/NAK/SBS/ISS
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Introduction to Statistics
Notes Prepared by Nurul Emyza Zahidi
Designing a
good
questionnaire
Questions must be in order
Questions must be short and simple
Try to minimize the use of openended questions
Avoid very personal questions and
confusing questions
Questions are very brief and
understandable
Avoid vague/ambiguous words and