This document provides an introduction to statistics, including defining key terms and concepts. It discusses what statistics is, the difference between populations and samples, parameters and statistics. It also outlines the two main branches of statistics - descriptive statistics, which involves organizing and summarizing data, and inferential statistics, which uses samples to draw conclusions about populations. The document then discusses different types of data, such as qualitative vs. quantitative, and the four levels of measurement for quantitative data. Finally, it discusses methods for designing statistical studies and collecting data, such as interviews, questionnaires, observation, and using registration data or mechanical devices.

1. Day 1
Introduction to Statistics
By: Hassan Arslan Khalid
Ph.D. (Scholar) Education
03024144411
Allama Iqbal Open University, Islamabad.

2. Chapter
Outline
An overview of statistics
Data classification
Experimental design

3. Section 1
An overview of Statistics

4. Learning Outcomes
• Define statistics
• Distinguish population and sample
• Distinguish a parameter and a
statistic
• Distinguish descriptive and
inferential statistics

5. What is data?
• Data
consists of information coming from
observations, counts, measurement, or
responses.
• “People who eat three daily servings of the
whole grains have been shown to reduce
their risk of … stroke by 37 %.” (Source:
Whole Grains Council)
• “Seventy percent of the 1500 IT students
playing DOTA 2 and CSGO”

6. What is Statistics?
• Statistics:
Statistics is a branch of knowledge
that deals with facts and figures. The
term statistics refers to a set of
methods and rules for organizing,
summarizing, and interpreting
information. It is a way of getting
information from data.

7. Data Sets
• Population
The collection of all
outcomes, responses,
measurements or counts that are of
interest.
• Sample
A subset of population.

10. Parameter and Statistic
Parameter
• A number that describes
a population
characteristic.
• Average age of all
people in Pakistan.
Statistic
• A number that describes
a sample characteristic.
• Average age of people
from a sample of 2
provinces.

13. Branches of Statistics
• Descriptive Statistics
Involves organizing,
summarizing and displaying
data.
e.g., tables, charts, averages.
• Inferential Statistics
Involves using sample data to
draw conclusions about a
population.

14. Example
• Let’s say there are 20 statistics classes at your
university, and you’ve collected the ages of
students in one class.
Ages of students in your statistics class: 19, 21, 18,
18, 34, 30, 25, 26, 24, 24, 19, 18, 21, 49, 27.
A descriptive question that could be asked about
this data: “What’s the most common age of
student in your statistics class?” The answer of
this would be 18.
An inferential question could be: “Are the ages of
students in this classroom similar to what you
would expect in a normal statistics class at this
university?

15. Section 2
Data Classification

16. Learning
Outcomes
• Distinguish between
qualitative and
quantitative data
• Classify data with
respect to four
levels of
measurement

17. Types of Data
According to Sources
• Primary Data
Refers to information which is directly
gathered from respondents, or which is
based on direct or firsthand experiences.
Example: diary
• Secondary Data
Refers to information which is taken
from published or unpublished data
gathered by other individuals or
agencies.
Example: books, magazines

18. Types of Variables
• Qualitative Variables
Consist of attributes, labels or non-numerical
entries.
Examples: Major, Place of birth, Eye color
• Quantitative Variables
Numerical measurements or counts.
Examples: Temperature, Age, Weight of object.

21. Classification of Quantitative Variables
• A numerical response that arise from a measurement process.
• Example: 1.2 inches, 2.8 cm.
Continuous Data
• Numerical responses that arise from a counting process.
• Example: Number of children in a community.
Discrete Data

22. Levels of
Measurement
• Nominal Level of Measurement
• Qualitative data only
• Categorized using names, labels or
qualities
• No mathematical computations can
be made
• Ordinal Level of Measurement
• Qualitative or quantitative data
• Data can be arranged in order
• Differences between data entries in
not meaningful

25. Levels of
Measurement
• Interval Level of
Measurement
• Quantitative data
• Data can be ordered
• Differences between data entries is
meaningful
• Zero represents a position on scale
(not an inherent zero – zero does not
imply “none”

27. Levels of
Measurement
• Ratio Level of
Measurement
• Similar to interval level
• Zero entry is an inherent zero
(implies “none”)
• A ratio of two data values can be
formed
• One data value can be expressed
as a multiple of other

30. Section 3
Discuss how to design a statistical study
Data Collection Techniques
Sampling Techniques

31. Methods of Data Collection
• Interview Method
• Direct Method: The researcher personally interview the
respondents.
• Indirect Method: The researcher uses a telephone call to
interview the respondents.
• Questionnaire Method
It is a list of well – planned questions written on a paper which can
be either personally administered or mailed by the researcher to
respondents.
• Observation Method
The researcher observes the subject of study which may be an
individual, a group, or any unit of interest.

32. Methods of Data Collection
• Registration Method
Example of data gathered using this method are
those obtained from National Statistics Office
(NSO), Land Transportation, Education Department,
and other Government Agencies.
• Mechanical Devices
Devices that can be used when gathering data for
social and educational researches like camera,
projector, tape recorder etc.

42. Summary