WEEK 1: INTRODUCTION
TO STATISTICS
By Ms Nur Faridah
Psychology Lecturer
RKL
Learning Outcome(s)
• Define the basic concepts of statistics such as tendency,
data description, sampling and probability.
Content Outline
• Definition of Statistics
• Descriptive and Inferential Statistics
• Types of data
Definition and Purpose of Statistics
• Statistics is a science of collecting and analyzing numerical data.
• It is a branch of applied probability which has a two-fold purpose:
Description and Inference.
• statistical analysis refers to doing something useful with data.
• The two main ways that data is analysed are
a) by bringing out the information it contains. This is part of
descriptive statistics
b) testing or retesting a hypothesis. Hypothesis testing is part
of inferential statistics
Process of Statistics
Identify the
objective
Collect
information
Draw conclusion
Summarize the
information
Descriptive Statistics
• The descriptive statistics presented and summarized the data in a
convenient form which are easy to understand and suitable for use
such as tables, graphs, charts and diagram.
• E.g:
Exam result in school
Abu – 3.0
Faizal – 2.8
Fatima – 2.8
Ain – 2.4
Shahiran – 3.2
Laxman – 1.8
Sajiv – 2.8
Liana – 3.0
Faiza – 3.4
Suraya – 3.4
Herwan – 2.2
Solehin – 3.2
Mean: 2.8
Inferential Statistics
• The data obtained is used to make generalizations, estimations,
decisions or predictions about a population by analyzing the samples
or
• A process of describing the population based on the sample results.
• E.g:
1. Out of 350 people randomly selected in Kuala Lumpur, 280 people
had 5 children.
- Inferential statistics: “80% of all people living in Kuala Lumpur have 5
children.”
Basic Terms in Statistics
POPULATION: a complete
set items that is being
studied.
SAMPLE: a relative small
group of items selected
from a population.
DATA: numbers or
measurements that are
collected. Data may
include number of
individuals that make up
the census of a city or test
scores obtained.
VARIABLES:
characteristics or
attributes that enable us
to distinguish one
individual from another.
• Ex: Age, Test Scores
RANDOM SAMPLE: if
every member in
population has an equal
chance of being selected
for the sample.
CONSTANT: values never
change
Basic Terms (Cont.)
EXPERIMENT: any process or study which results in
the collection of data.
PARAMETER: a value, usually unknown (has to be
estimated), used to represent a certain population
characteristics.
STATISTICS: a value, usually unknown, (has to be
estimated), used to represent a certain sample
characteristics.
Types of Data
Quantitative data
Types of Data
Qualitative data
Quantitative data
Discrete Data
- Data can be measured precisely.
- Sets of data that presented as number.
- E.g: Shoe size – 6, 7, 8, 9
Continuous Data
- The data value cannot be measured to its exact value.
- The data can take any possible values in a range .
- The data based on approximations.
- E.g: Weight
Qualitative data
• The data that is presented not in numerical.
• The data may be presented in term of name, symbol or other
characteristics of the data.
• The data cannot be measured.
• E.g: Colours.
• Question: Is open-ended interview produces Qualitative or
Quantitative data?
Exercise 1: Identifying Descriptive and
Inferential Statistics
Instructions: For each of the following statements, identify whether it
describes descriptive statistics or inferential statistics.
1.
2.
3.
4.
5.
Based on a survey of 100 people, a researcher predicts that 60% of
the population prefers online shopping.
The average test score of students in a classroom is 78%.
A graph shows the distribution of ages in a sample of 200 people.
A doctor estimates that 15% of the population will get the flu this
season based on a study of 500 patients.
The median income of a town’s residents is $45,000.
Exercise 2: Classifying Quantitative Data
Instructions: For each of the following examples, identify whether the
data is quantitative discrete or quantitative continuous.
1.
2.
3.
4.
5.
The time it takes to complete a marathon.
The number of siblings a person has.
The height of students in a class.
The number of goals scored in a soccer match.
The temperature recorded at different times of the day.
Exercise 3: Real Life Scenarios
Instructions: Read each scenario and identify whether the data
described is quantitative discrete, quantitative continuous, or
qualitative.
1.
2.
3.
4.
5.
A survey asks people about their favorite music genre.
A researcher measures the circumference of trees in a forest.
A student counts the number of pencils in their pencil case.
A chef records the amount of sugar (in grams) used in a recipe.
A poll collects information on political party affiliation.