2. Origin and Development
The history of statistics can be traced back at
least to the Biblical times in ancient Egypt,
Babylon, and Rome. As early as 3500 years
before the birth of Christ, statistics had been
used in Egypt in the form of recording the
number of sheep or cattle owned, the amount of
grain produced, and the number of people living
in a particular city.
3. Origin and Development
In 3800 B.C., Babylonian government used
statistics to measure the number of men under a
king’s rule and the vast territory that he
occupied. It was his belief that the more men
under his command and the more lands he
conquered, the more powerful his kingdom would
become.
In 700 B.C., Roman empires used statistics by
conducting registration to record population for
the purpose of collecting taxes.
4. Origin and Development
In the modern times, statistical methods have
been used to record and predict such things as
birth and death rates, employment and inflation
rates, sports achievements, and other economic
and social trends. They have even been used to
assess opinions from polls and unlock secret
codes from a game of chance.
5. Origin and Development
Modern statistics is said to have begun with
John Graunt (1620 – 1674), an English
tradesman. Graunt collected published records
called “bills of mortality” that included
information about the numbers and causes of
deaths in the city of London. Graunt analyzed
more than fifty years of data and created the
first mortality table, a table showing how long a
person may be expected to live after reaching a
certain age.
6. Origin and Development
There were so many other great men who made
important contributions to statistics.
One of them was Karl Friedrich Gauss (1777 –
1855), the brilliant German mathematician who
used statistical methods in making predictions
about the positions of the planets in our solar
system.
7. Origin and Development
Adolphe Quetelet (1796 – 1874), a Belgian
astronomer developed the idea of the “average
man” from his studies of the Belgian census. He
was also known as the “Father of Modern
Statistics.”
Karl Pearson (1857 – 1936), an English
mathematician made important links between
probability and statistics.
8. Origin and Development
In the 20th
century, the British statistician Sir
Ronald Aylmer Fisher developed the F-tool in
inferential statistics. This tool has been very
useful in testing improvements of production
from agricultural experiments and improvement
of precision of results from medical, biological,
industrial experimentation.
The American George Gallup (1901 – 1984) was
instrumental in making statistical polling, a
common tool in political campaigns.
9. Definition
STATISTICS refers to a field of study in which
quantitative data are collected, presented,
analyzed and interpreted.
Today, statistics and statistical analysis are used
in every profession. Statistics have become a
most valuable tool in business, economics,
management, psychology, health, education and
many others.
10. Definition
The word statistik comes from the Italian
word statista which means “statesman”. It
was first used by Gottfried Achenwall (1719 –
1772), a professor at Marlborough and
Gottingen, while Dr. E.A.W. Zimmerman
introduced it in England. It was popularized
by Sir John Sinclair in his work, Statistical
Account of Scotland (1791 – 1799). However,
people had been recording and using data
long before the 18th
century.
12. For example, in education,
statistics can be used to
assess students’
performance and correlate
factors affecting teaching
and learning processes to
improve quality of
education.
Uses of
Statistics
13. Uses of Statistics
In Psychology, statistics is
used to determine attitudinal
patterns, the causes and
effects of misbehavior.
14. Uses of Statistics
In business and economics,
statistics is used to analyze a wide
range of data like sales, outputs,
price indices, revenues, costs,
inventories, accounts, and the like.
This is to monitor status of
customers, employees, orders, and
production
15. Uses of Statistics
In research and experimentation, statistics is used
to validate or test a claim or inferences about a
group of people or object, or a series of events.
16. ►In the field of medicine,
statistics is used to collect
information about
patients and diseases and
to make decisions about
the use of new drugs or
treatment.
Uses of
Statistics
17. Uses of Statistics
Another important use of statistics is
in demographics, the study of the size,
vital characteristics of the population,
and how they might change over time.
Perhaps most familiar to us are the
statistics reported in the news media
about important issues.
18. Fields of Statistics
Desciptive statistics is concerned with the
methods of collecting, organizing, and presenting
data appropriately and creatively to describe or
assess group characteristics.
Inferential statistics is concerned with inferring
or drawing conclusions about the population
based from pre-selected elements of that
population.
19. Variables
A variable is a characteristic that changes or
varies over time and/or for different
individuals or objects under consideration.
Examples
1.The number of ton coal consumption is a
variable that changes from power plant to
power plant;
2.The tonnage distributed by a brokerage firm
20. Qualitative and Quantitative
Variables
Qualitative variables measure a quality or
characteristic on each individual or object.
Examples
1.Color of cars: red, blue, yellow, gray, black;
2.T-shirt size: extra small, small, medium, large,
extra large.
21. Qualitative and Quantitative
Variables
Quantitative variables measure a numerical
quality or amount on each individual or object,
often represented by x.
Examples
1.Let x represent the height of male students in
a university;
2.Let x represent the number of batteries
produced by a manufacturing company.
22. Discrete and Continuous Variables
A discrete variable can assume only a finite or
countable number of values.
Examples
1.Let x represent the number of washers
produced by a company;
2.Let x represent the number of bolts produced
by a machine.
23. Discrete and Continuous Variables
A continuous variable can assume the infinitely
many values corresponding to the point on a
line interval.
Examples
1.Let x represent the height (in meters) of
college students;
2.Let x represent the length of cable (in meters)
installed by Meralco in Metro Manila.
24. Classification of Variables
A. According to functional relationship
•Independent variable. This is sometimes
termed as predictor variable.
•Dependent variable. This is sometimes called
criterion variable.
For example, academic achievement is
dependent on I.Q. IQ is the independent variable
and academic achievement is the dependent
variable.
25. Classification of Variables
B. According to scale of measurements
•Nominal variable. This property allows one to
make statements of similarities or differences.
•Ordinal variable. This variable refers to a
property whereby members of a group are
ranked.
26. Classification of Variables
B. According to scale of measurements
3.Interval variable. This property allows one to
make statements of equality of intervals.
4.Ratio variable. This property permits making
statements of equality of ratios.
27. Constants
Constants refer to the fundamental quantities
that do not change in value.
Fixed costs and acceleration due to gravity are
examples of such.
28. Data and Information
Data usually refers to facts concerning things
such as status in life of people, defectiveness of
objects or effect of an event to the society.
Information is a set of data that have been
processed and presented in a form suitable for
human interpretation, usually with a purpose
of revealing trends or patterns about the
population.
29. Sources of Data
There are two sources of obtaining data.
One is called the primary source from which a
firsthand information is obtained usually by
means of personal interview and actual
observation.
30. Sources of Data
On the other hand, the secondary source of
information is taken from other’s works, news
reports, readings, and those that are kept by
the National Statistics Office, Securities and
Exchange Commission, S.S.S., and other
government and private agencies.
31. Sources of Data
Data are said to be an asset of a company if they
are accurate, updated, and available when
needed.
Hence, any institution or business organization
must have a database called Management
Information System where all information
about their business are made available in
order to facilitate verification of claims and to
come up with wise decisions.
32. Methods of Collecting Data:
Its Advantages and Disadvantages
1. Direct or Interview Method – is a person-to-
person interaction between an interviewer and
an interviewee. Tape recorded or written
interviews will help the researcher obtain
exact information from the interviewee.
33. Methods of Collecting Data: Its Advantages and Disadvantages
1. Direct or Interview Method
Advantages:
Precise and consistent
answers can be obtained
by modifying or rephrasing
the questions especially to
illiterate respondents or to
children under study.
Disadvantages:
It is time, money, and
effort consuming and it
will be applicable only for
small population, except
when conducting a census.
34. Methods of Collecting Data: Its Advantages and Disadvantages
2. Indirect or Questionnaire Method – is an
alternative method for the interview method.
Written responses are obtained by disturbing
questionnaires (a list of questions intended to
elicit answers to a given problem, must be
given in a logical order and not too personal) to
the respondents through mail or hand-carry.
35. Methods of Collecting Data: Its Advantages and Disadvantages
2. Indirect or Questionnaire Method
Advantages:
Lesser time, money, and
efforts are consumed.
Disadvantages:
Many respondents may not
be consistent due to the
poor construction of the
questionnaire. The
meaning of the questions
may be different from each
respondent. Inconsistent
responses can no longer be
modified; it reduces valid
number of respondents.
36. Methods of Collecting Data: Its Advantages and Disadvantages
3. Registration Method – is enforced by private
organizations or government agencies for
recording purposes.
37. Methods of Collecting Data: Its Advantages and Disadvantages
3. Registration Method
Advantages:
Organized data from an
institution can serve as
ready references for future
study or for personal
claims of people’s records.
Disadvantages:
Problem arises only when
an agency doesn’t have a
Management Information
System and if the system
or process of registration is
not implemented well.
38. Methods of Collecting Data: Its Advantages and Disadvantages
4. Observation Method – is a scientific method of
investigation that makes possible use of all
senses to measure or obtain outcomes /
responses from the object of the study.
39. Methods of Collecting Data: Its Advantages and Disadvantages
4. Observation Method
Advantages:
Observation method is
usually applied to
respondents that cannot be
asked or need not speak,
especially when behaviors
of persons / culture of
organizations /
performance outcomes of
employees / students are to
be considered.
Disadvantages:
Subjectivity of information
sought cannot be avoided.
40. Methods of Collecting Data: Its Advantages and Disadvantages
5. Experimentation – is used when the objective
is to determine the cause-and-effect of a
certain phenomenon under some controlled
conditions.
41. Methods of Collecting Data: Its Advantages and Disadvantages
5. Experimentation
Advantages:
There is objectivity of
information since a
scientific method of inquiry
is used. An equal number of
respondents with relatively
similar characteristics are
being examined to obtain
the different effects of
something applied to the
experimental group.
Disadvantages:
It’s too difficult to find
respondents with almost
similar characteristics. The
whole method must be
repeated if the desired
outcome is not reached.
42. Methods of Collecting Data: Its Advantages and Disadvantages
Data that are collected by these methods are
usually referred to as raw data. Responses out
from taped interviews, answered
questionnaires, furnished registration forms,
recorded observations, and results from an
experiment are considered raw data since they
are not yet organized and presented in a form
ready for interpretation. These data can only
be understood if appropriate forms of
presentation are adopted.
43. VARIABLES
QUALITATIVE QUANTITATIVE
• Dependent
• Independent
• Dichotomous
• Trichotomous
• Multinomous
• Discrete
• Continuous
DATA
SOURCES
• Primary
• Secondary
METHODS
• Interview
• Questionnaire
• Registration
• Observation
• Experimentation
SCALES OF
MEASUREMENT
• Nominal
• Ordinal
• Interval
• Ratio
PRESENTATION
• Textual
• Tabular
• Graphical /
Chart
• Line Graph
• Bar Graph
• Pie Graph
• Pictograph
• Map /
Cartogram
• Scatter
Point
Diagram
Fig. 1.1 Classification of Variables and Data
44. ►In your own word, what is
the uses of Statistics?
