Educational Statistics 8614 AIOU

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