CHAPTER 2
Data Collection, Organization and
Presentation
INTRODUCTION:
In this lesson, we will be discussing the different ways to collect,
organize and present data so that it can be easily understood by the reader.
Data collection, organization and presentation are important processes that you
must learn in order to interpret the data correctly. Furthermore, you will be
learning how to construct frequency distribution and stem and leaf display.
OBJECTIVES:
At the end of this lesson, you should be able to:
1. Identify, compare and contrast the different sources of data;
2. Summarize and present data in different forms; and
3. Construct frequency distribution and stem and leaf display.
Collection of Data
The goal of every statistical study is to collect information which will
be used in making decisions. Decision made from the results of any
statistical study is only as good as the process used to obtain the
information. If the process is flawed, then the resulting decision is
questionable.
Methods of Data Collection
1. Survey - an investigation of one or more characteristics of a population.
Most often, surveys are done by asking questions either thru self-
administered questionnaires or personal interviews. Nowadays, in the
advent of technology online survey becomes prevalent.
Kinds of Survey
a. Census – method of gathering the facts of interest or pertinent data on
every unit of the population.
b. Sample Survey – method by which data from a small but
representative cross-section of the population are scientifically
collected and analyzed.
Advantages of a sample survey over a census:
a. Speed and timeliness – data collected on the sample can be gathered
faster while ensuring uniformity of data gathering procedure.
b. Economy – data gathering and analysis are cheaper.
, of workers (enumerators) are likely to make fewer errors in the
collection and handling of data than a large census force would.
d. Feasibility – for a large population it is difficult or sometimes
impossible to gather all the data from a population. It is more doable
to gather data from a sample compared to a population. e.g. lifetime
of a bulb.
2. Observation. Observation makes possible the recording of behavior
but only at the time of occurrence. It is also employed when the
subjects cannot talk or write. In doing observation, the researchers
make use of their senses and observe the condition in the natural state
rather than communicating with their respondents.
3. Existing records. Data from published materials like reports, personal
files, and historical records will be utilized.
4. Simulation. A simulation is the use of a mathematical or physical
model to reproduce the conditions of a situation or process. Simulations
allow you to study situations that are impractical or even dangerous to
create in real life.
5. Experiment. In performing an experiment, a treatment is applied to
part of a population and responses are observed. Data are obtained
under controlled conditions.
The data collected may either be of two types:
1. Primary data – data that are collected directly from the
subjects/objects of the study. These subjects/objects may be people,
experimental animals, or the environment. Because the data is
collected by the individual who will utilize the data, the individual can
then very precisely collect the information that he wants. He can
specify the operational definitions used and can eliminate, or at least
monitor and record, the extraneous influences on the data as they
are gathered. The collection of primary data, however, is costly and
time-consuming compared to secondary data.
Advantages of Primary Data
✓ Data collected for the first time hence original in character.
✓ The information collected is accurate.
✓ More information may be collected which may prove useful at the
time of analysis and interpretation of results.
✓ Some confidential information can be tactfully collected from the
informants.
Disadvantages of Primary Data
✓ Methods of primary data collection are expensive and time
consuming.
✓ The personal prejudice and bias of the investigator or enumerator
can destroy the purpose of survey.
✓ The data may not be reliable if collected carelessly.
2. Secondary data – these are previously collected data that are found in
, research papers, books, periodicals, pamphlets, computer files, microfilms
or the internet. Secondary data are useful in that
i) They fill a need for a specific reference on some point
ii) They act as reference benchmarks against which other findings may
be tested
iii) They can provide background material on what has already been
done, thereby \providing direction on what further needs be done
iv) They can be used as basis for a research study as in validating a
research methodology or a mathematical model
Advantages of Secondary Data:
1. Secondary data are collected quickly and cheaply.
2. When official statistics are collected, these are most reliable and
acceptable by other agencies
Disadvantages of Secondary Data:
1. Secondary data may not meet one’s specific needs (example: red tide
modeling for which data are not as refined as you would need it)
2. It is difficult in assessing the accuracy of the information.
Oftentimes, definitions and units of measurement will be different
and the timeliness of the data is often questioned.
Data Classification
Classification of data is the process of arranging data in
groups/classes on the basis of certain properties (Sharma, 2011). The
classification of statistical data serves the following purposes:
(i) It condenses the raw data into a form suitable for statistical analysis.
(ii) It removes complexities and highlights the features of the data.
(iii) It facilitates comparisons and drawing inferences from the data. For
example, if university students in a particular course are divided
according to sex, their results can be compared.
(iv) It provides information about the mutual relationships among
elements of a data set. For example, based on literacy and criminal
tendency of a group of people, it can be established whether literacy
has any impact or not on criminal tendency.
(v) It helps in statistical analysis by separating elements of the data set
into homogeneous groups and hence brings out the points of similarity
and dissimilarity.
Basis of Classification
Geographical Classification. In geographical classification, data are
classified on the basis of geographical or locational differences such as—
cities, districts, or villages between various elements of the data set.
The following is an example of a geographical distribution:
Data Collection, Organization and
Presentation
INTRODUCTION:
In this lesson, we will be discussing the different ways to collect,
organize and present data so that it can be easily understood by the reader.
Data collection, organization and presentation are important processes that you
must learn in order to interpret the data correctly. Furthermore, you will be
learning how to construct frequency distribution and stem and leaf display.
OBJECTIVES:
At the end of this lesson, you should be able to:
1. Identify, compare and contrast the different sources of data;
2. Summarize and present data in different forms; and
3. Construct frequency distribution and stem and leaf display.
Collection of Data
The goal of every statistical study is to collect information which will
be used in making decisions. Decision made from the results of any
statistical study is only as good as the process used to obtain the
information. If the process is flawed, then the resulting decision is
questionable.
Methods of Data Collection
1. Survey - an investigation of one or more characteristics of a population.
Most often, surveys are done by asking questions either thru self-
administered questionnaires or personal interviews. Nowadays, in the
advent of technology online survey becomes prevalent.
Kinds of Survey
a. Census – method of gathering the facts of interest or pertinent data on
every unit of the population.
b. Sample Survey – method by which data from a small but
representative cross-section of the population are scientifically
collected and analyzed.
Advantages of a sample survey over a census:
a. Speed and timeliness – data collected on the sample can be gathered
faster while ensuring uniformity of data gathering procedure.
b. Economy – data gathering and analysis are cheaper.
, of workers (enumerators) are likely to make fewer errors in the
collection and handling of data than a large census force would.
d. Feasibility – for a large population it is difficult or sometimes
impossible to gather all the data from a population. It is more doable
to gather data from a sample compared to a population. e.g. lifetime
of a bulb.
2. Observation. Observation makes possible the recording of behavior
but only at the time of occurrence. It is also employed when the
subjects cannot talk or write. In doing observation, the researchers
make use of their senses and observe the condition in the natural state
rather than communicating with their respondents.
3. Existing records. Data from published materials like reports, personal
files, and historical records will be utilized.
4. Simulation. A simulation is the use of a mathematical or physical
model to reproduce the conditions of a situation or process. Simulations
allow you to study situations that are impractical or even dangerous to
create in real life.
5. Experiment. In performing an experiment, a treatment is applied to
part of a population and responses are observed. Data are obtained
under controlled conditions.
The data collected may either be of two types:
1. Primary data – data that are collected directly from the
subjects/objects of the study. These subjects/objects may be people,
experimental animals, or the environment. Because the data is
collected by the individual who will utilize the data, the individual can
then very precisely collect the information that he wants. He can
specify the operational definitions used and can eliminate, or at least
monitor and record, the extraneous influences on the data as they
are gathered. The collection of primary data, however, is costly and
time-consuming compared to secondary data.
Advantages of Primary Data
✓ Data collected for the first time hence original in character.
✓ The information collected is accurate.
✓ More information may be collected which may prove useful at the
time of analysis and interpretation of results.
✓ Some confidential information can be tactfully collected from the
informants.
Disadvantages of Primary Data
✓ Methods of primary data collection are expensive and time
consuming.
✓ The personal prejudice and bias of the investigator or enumerator
can destroy the purpose of survey.
✓ The data may not be reliable if collected carelessly.
2. Secondary data – these are previously collected data that are found in
, research papers, books, periodicals, pamphlets, computer files, microfilms
or the internet. Secondary data are useful in that
i) They fill a need for a specific reference on some point
ii) They act as reference benchmarks against which other findings may
be tested
iii) They can provide background material on what has already been
done, thereby \providing direction on what further needs be done
iv) They can be used as basis for a research study as in validating a
research methodology or a mathematical model
Advantages of Secondary Data:
1. Secondary data are collected quickly and cheaply.
2. When official statistics are collected, these are most reliable and
acceptable by other agencies
Disadvantages of Secondary Data:
1. Secondary data may not meet one’s specific needs (example: red tide
modeling for which data are not as refined as you would need it)
2. It is difficult in assessing the accuracy of the information.
Oftentimes, definitions and units of measurement will be different
and the timeliness of the data is often questioned.
Data Classification
Classification of data is the process of arranging data in
groups/classes on the basis of certain properties (Sharma, 2011). The
classification of statistical data serves the following purposes:
(i) It condenses the raw data into a form suitable for statistical analysis.
(ii) It removes complexities and highlights the features of the data.
(iii) It facilitates comparisons and drawing inferences from the data. For
example, if university students in a particular course are divided
according to sex, their results can be compared.
(iv) It provides information about the mutual relationships among
elements of a data set. For example, based on literacy and criminal
tendency of a group of people, it can be established whether literacy
has any impact or not on criminal tendency.
(v) It helps in statistical analysis by separating elements of the data set
into homogeneous groups and hence brings out the points of similarity
and dissimilarity.
Basis of Classification
Geographical Classification. In geographical classification, data are
classified on the basis of geographical or locational differences such as—
cities, districts, or villages between various elements of the data set.
The following is an example of a geographical distribution:
