This document discusses various aspects of data gathering and analysis for research. It covers collecting primary and secondary data, using different sampling methods like probability and non-probability sampling, managing data through categorization and analysis. The key steps in research like administering instruments, recording observations, and using documentation are outlined. Common sampling techniques like random, stratified, cluster and convenience sampling are defined. The document also discusses managing data responses and analyzing data through calculating frequencies.

1. Data Gathering,
Sampling, Data
Management And Data
Integrity
Villanueva, Ryan Cloyd Q.
BA-Political Science 4

2. DATA GATHERING
Data are collection of numbers, quantities, facts,
or records used as bases for drawing conclusions or
making inferences. Data are what the researcher is
searching for and which are subjected to analysis
using statistical procedures, and interpretations, so
that the interferences, principles of generalization
are drawn.

3. Basic Steps:
Administering the research instrument. If you are using
a questionnaire, describe how you are going to proceed.
Recording Observations. Additional data may be
collected through systematic recording of observations. It
could also aid in a more accurate and interesting
interpretation of data.
Use of Records and Documentation. Records and
documents are very important sources of additional
information.

4. Sources of Data
Primary Data. Primary data are those gathered
from primary sources. The primary sources are as follows:
• Individual Persons
• Organized Group or Organization such as fraternities,
associations, schools, community, etc.
• Established practices such as marriage, religious rites,
legal system, and economic system.

5. Secondary Data are those gathered from
secondary sources. The secondary resources are as follows:
• Books including dictionaries, encyclopedia, almanac, etc.
• Articles published in professional journals, magazines,
newspapers and other publications.
• Unpublished thesis and dissertation and other studies.
• Monographs and manuscripts.
• All other second hand sources (verbal or written)

6. Research Instrument
Observation involves the researcher watching the
research situation.
Interview is feasible when a personal interaction is
available.
Questionnaire is a set of questions, arranged in
sequence and designed to be self-administered.

7. SAMPLING METHOD
According to Amante, sampling means selecting a given
number of persons, objects or events called subset from a
given population by specified selection process. Sampling
also refers to strategies of picking up a subgroup from a
larger group to be used as a basis for making judgements
about the larger group. The sub-group is the sample while
the larger group is the population.

8. Importance of Sampling
The extent to which generalizations can be made from the
results of a research depends much on the sampling
techniques used and how appropriate it is. If the research
findings are not generalizable to some degree beyond the
sample used in the study, then the research cannot provide
new knowledge, cannot advance education as a science and
is largely a waste of time. Sampling should be carefully
designed for satisfactory.

9. General Types Of Sampling
Probability Sampling – the sample is a portion
(a certain percent) of the population and such sample is
selected from the population by means of some way in
which every element of the population has a chance of
being included in the sample.
Non-probability Sampling – the sample is not
a proportion of the population and there is no system in
selecting the sample. The selection depends upon the
population.

10. Types of Probability Sampling
Pure Random Sampling – this type is one in which
everyone in the population of the inquiry has an equal
chance of being selected to be included in the sample.
Systematic Sampling – this is the technique of sampling in
which every nth name is a list may be selected to be
included in a sample.

11. Stratified Random Sampling – is the process of selecting
randomly samples from the different strata of the
population used in the study.
Purposive Sampling – is determining the target
population those to be included in the study.
Cluster Sampling – or multistage sampling is used
when the population is too big or the geographical area
the research is large.

12. Types of Non-probability Sampling
Accidental Sampling – there is no system of selection but
only those whom the researcher or interviewer meet by
chance are included in the study.
Quota Sampling – specified numbers of persons of certain
types are in the sample.
Convenience Sampling – it is a process of picking out
people in the most convenient and to immediately get their
reaction to a certain hot and controversial issue.

13. DATA MANAGEMENT
• Category Response - the age and gender questions are
examples of category response questions.
• Quantity or Information Response - the questionnaire/s
is encrypted with questions that aims to ask important
information’s to the respondents of the study that could
be useful on the further study of the research.
• List Response - it may be that the respondent actually had
multiple responsibilities and this would be particularly
useful to know.

14. • Rating Scale Response - questions which ask
respondents to rate their feelings or attitudes against a
prepared scale are the mainstay of questionnaire
• Ranking Response - these questions require
respondents to rank a number of options in a
order.
• Open Response - open response questions are a must
for questionnaire surveys if only as a ‘catch-all’ at the
to give respondents the opportunity to reveal any
ideas/comments/ suggestions they have been harboring
and not had the opportunity to articulate.

15. DATA ANALYSIS
Calculating Frequencies
The frequency (f) of a particular observation is the number
of times the observation occurs in the data.
The distribution of a variable is the pattern of frequencies
of the observation. Frequency distributions are portrayed
as frequency tables, histograms, or polygons.
Frequency distributions can show either the actual
number of observations falling in each range or the
percentage of observations. In the latter instance, the
distribution is called a relative frequency distribution.

16. Thank You
for
LISTening