WHAT IS RESEARCH?
The systematic , rigorous investigation of a
situation or problem in order to generate new
knowledge or validate existing knowledge.
It is a careful, critical, disciplined inquiry,
varying in technique and method according to
nature and conditions of the problem identified
toward clarification or resolution of a problem
(Good, p. 464)
3. Fundamental Goals of Research
To satisfy man’s craving for more
To improve his judgement
To add to his power
To reduce the burden of work
To relieve suffering
To increase satisfaction in multitudinous ways
4. Types of Research
1. Basic Research seeks to contribute to knowledge
through the development of a theory or concept.
The main motivation is to expand man’s knowledge,
not to create or invent something. There is no
obvious commercial value to the discoveries that
result from basic research.
2. Applied Research seeks to provide solutions to
problems through the development and evaluation
of processes, policies and other activities that
require specific courses of action.
5. 3. Correlational Research refers to the systematic
investigation or statistical study of relationships
among two or more variables, without necessarily
determining cause and effect.
4. Descriptive Research refers to research that
provides an accurate portrayal of characteristics of a
particular individual, situation or group. This is also
known as statistical research.
5. Ethnographic Research refer to the investigation
of a culture through an in depth study of the
members of the culture ; it involves the systematic
collection, description, and analysis of data for
development of theories of cultural behaviour.
6. 6. Experimental Research is an objective, systematic,
controlled investigation for the purpose of predicting
and controlling phenomena and examining
probability and causality among selected variables.
7. Exploratory Research is a type of research
conducted for a problem that has not been clearly
8. Historical Research is research involving analysis
of events that occurred in the remote or recent past.
9. Phenomenological Research an inductive,
descriptive research approach developed from
phenomenological philosophy; its aim is to describe
an experience as it is actually lived by the person.
7. Research are classified into two groups:
Qualitative research is research dealing with
phenomena that are difficult or impossible to
quantify mathematically, such as beliefs, meanings,
attributes and symbols.
The qualitative methods investigates the why and
how of decision making, not just what, where, and
Quantitative Research refers to the systematic
empirical investigation of any phenomena via
statistical, mathematical or computational
The objective of quantitative research is to
develop and employ mathematical models, theories
and/or hypotheses pertaining to phenomena.
8. RESEARCH OUTLINE
1. Abstract of the Study
1.2 Major hypotheses
9. 2. Chapter 1
2.1 Introduction of the Study
2.2 Background of the Study
Description of the general context in which
the problem is to be viewed and discussed
Description of the situation in and the process by
which the problem arose and developed
Reasons for choosing the topic
2.3 Theoretical/Conceptual Framework
10. Theoretical Framework
It is important that you cite existing theories
and ideas that are relevant to your chosen
topic within the theoretical framework. This
includes defining key terms from your
statement of the problem and research
questions and hypothesis. It consists of
theories that seem to be interrelated.
It can be used to answer descriptive research
questions. (diagram )
11. Conceptual Framework
It is the researcher’s own position on the
problem and gives direction to the study. it
may be an adaptation of a model used in a
previous study, with modifications to suit the
inquiry., through the conceptual framework,
the researcher can be able to show the
relationships of the different constructs that
he wants to investigate. (diagram)
12. 2.4 Statement of the Problem
There should be a general statement of the
whole problem followed by the specific questions or
sub problems into which the general problem is
broken up. It provides direction and focus to the
Consider the ff:
1. The research problem is written in question
form and identifies specific area.
2. The topic is phrased in workable and
13. 3. The scope is limited to realistic parameters
that are not too narrow nor too broad.
4. The words used are unbiased, objective,
and not emotional-laden.
5. The relationship between variables to be
studied are clearly cited.
6. The phrases and wordings are measurable
and can be empirically proven.
7. The problems identify the data and
techniques to answer the questions.
14. Assumptions and Hypotheses
The hypotheses formulated are testable,
that is, they can be accepted or rejected.
Hypotheses are not proved, they are only
determined as true or not.
If the findings from the data do not
conform to the hypotheses, the latter are
rejected. If the findings conform to the
hypotheses, the latter are accepted as true
15. 2.5 Significance of the Study
The importance of the whole study must
contain explanations or discussions of any of
1. The rationale, timeless and relevance
of the study to the existing conditions must be
explained or discussed.
2. Who are to be benefitted and how
they are going to be benefitted.
3. Possible contribution to the fund of
4. Possible implications
16. 2.6 Scope and Limitation
The statement of the research problem
requires a detailed explanation of the study’s
parameters and limitations. It should indicate
study coverage with concrete reference to:
variables, sources of data, methods, analysis,
timeframe and constraints that might be
encountered in the conduct of the study.
17. 2.7 Definition of Terms
Terms should be defined either lexical or
as it is used in the study.
18. Chapter 2 Review of Related Literature and
Thematic approach - literature and studies
organized around a topic or issue, rather
than the progression of time . However
progression of time may still be an important
factor in a thematic review.
19. Chapter 3 Methodology
Research design appears to be the schema that
maps out the sources of data, type of data to
be collected, how the data will be collected,
and the methods to be used in data analysis.
A good research design must also set time
constraints within which the research
problem should be answered.
Sampling is the process of choosing adequate
and representative elements from the
Sampling makes the scope of the study
manageable because of the small number of
respondents to be covered, and increases the
likelihood of obtaining more reliable and
21. The adequate number of elements to be
taken as samples is based on the desired
confidence level (alpha : α) and room for
error (e) in selecting the correct sample. In the
academe, the most common confidence levels
employed in thesis and dissertation sample
size computations are : 0.01 ; 0.05; 0.10.
The higher the confidence level desired, the
bigger sample size should be..
22. Statistics books contain different formulae in
determining the sample size , the common is
Formula : n = N / (1+Ne2)
if N = 350 ; e = .05
n = 187
23. Sampling Designs
Sampling designs are commonly classified into
probability and non probability sampling.
Probability is used when inferences about the
population are required , as in thesis,
dissertation or other academic researches.
Non probability sampling is usually adopted
when immediate information feedback is
needed, as in marketing research studies,
such as product launching.
24. Probability Non – Probability
– Random Quota
– Systematic Judgement
– Stratified Convenience
– Cluster Accidental
– Area Snowball
– Double Purposive
– Multi – Stage
25. Methods of Data Analysis
Data analysis involves the application of the
appropriate statistical tools to generate
results which can be interpreted meaningfully
to answer the research problems posed at the
beginning of the study/investigation.
The most common problem of a researcher at
this stage of the research process is choosing
the most appropriate statistical tools for data
26. HOW IMPORTANT STATISTICS IN
In theory they are very important. Without
statistics it is almost impossible to come to an
informed conclusion in any piece of research.
The use of statistics is wide ranging in the field
of research and without the sue of statistics ,
it is virtually impossible to interpret a true
meaning of what the research shows. Not to
exaggerate ... statistics is the BACKBONE OF
27. Dangers of (mis)using statistics
Statistics, no matter how carefully collected,
can always be flawed e.g. without a sample of
thousands of people (ensuring they are
representative of the whole population), you
cannot be certain that the results can be
Statistical information can be easily
manipulated to show very different results.
28. Levels of Measurement
NOMINAL – uses categories or classifications;
order is meaningless. Categories are mutually
exclusive ; lowest level of data measurement
since data cannot be transformed.
Examples: gender; form of ownership; civil status
INTERVAL – categories are ordered or ranked
using equality of distance. Classes are
mutually exclusive . Higher level of data and
measurement than nominal and ordinal. Zero
point has no true value.
29. Examples: Age; Average monthly income;
number of years
RATIO – categories are exclusive and are in
equidistant orders. Possess the characteristics
of the nominal, ordinal, and interval. Possess
true zero point. Data can be transformed. And
highest level of data measurement.
Examples: net income per year ; return of
investment; average no. of tardiness and
30. Statistical Treatment
Frequency or percentage – usually used to
determine the profile of respondents engage in the
Weighted Mean - summarizing the data in terms
of measures of central tendency. It is a kind of
average. Instead of each data point contributing
equally to the final mean, some data points
contribute more weight than others.
31. Weighted Mean = Sum of weighted terms
Number of Terms
2. Inferential test - use to test the research
- a technique that relies on the
probability distribution, for reaching the
conclusion concerning the reasonableness of
These hypothetical testing are classified into :
32. 1. Parametric Test
if data has an assumption or information about
the population parameter.
the distribution is normal
refers to interval and ratio data
mean is known
the information about the population is
applicable only to variables
33. Tests used are:
1.1 One Sample Mean – test of significant
sample mean and population
1.1.1 Z – test (n >30)
1.1.2 t – test ( n < 30 )
34. 1.2 Two sample Means - two independent
sample means of
1.2.1. t – test
1.2.2 Z – test
1.2.3 Pearson Product Moment
Correlation – to measure strength of
association or relationship between
35. 1.3 k - independent Sample Means
1.3.1 One Way Analysis of Variance ,
1.3.2 Two way Analysis of Variance - two
or more sample variances.
36. 2. Non Parametric Tests
- used in the case of non parametric
- distribution is arbitrary
- the data use nominal and ordinal
- use median as measure of central
- information about the population is
- applicable only to variable and
37. 2.1 One Sample Mean
2.1.1 Chi Square
2.1.2 Kolmogorov – Smirnov
2.2 Two Independent Sample Means
2.2.1 Chi Square
2.2.2 Mann – Whitney / U test
2.2.3 Median Test
38. 2.2.4 Kolmogorov Smirnov
2. 2.5 Kruskal Wallis Test
2.3 Paired Samples
2.3.1 Sign Test
2.3.2 Wilcoxon Test
2..3.3 McNemar Test
2.3.4 Chi Square Test
2.3.5 Cochran’s Q Test
To make a choice between parametric and non
parametric test is not easy for a researcher
conducting statistical analysis. For performing
hypothesis, if the information about the
population is completely known, by way of
parameters, then the test is said to be
parametric test, whereas, if there is no
knowledge about a population and it is needed
to test the hypothesis on population. then the
test conducted is considered as non parametric
40. Parametric Inference
1. To test significance of difference between
1.1 One Sample and Population Mean - t
test ; Z – test
The mean number of students in a day in a
local university is 100. Taguig City University is
one of the local university in Taguig . The
researcher would want to know if the said
university has the same mean as the
population mean in other university in Taguig.
41. Ho : There is no significant differences to the
mean number of students in other city
Ha: There is significant difference to the
mean number of students in other university.
42. 1.2 Two Independent Sample Mean - t test ;
If the researcher would also want to know
if PUP has the same mean number of students
Ho: There is no significant difference between
the mean number of students in TCU and PUP.
Ha: There is a significant difference between
the mean number of students in TCU and PUP.
43. 1.3k - Independent Sample Means - One Way
The manager would want to know if there
is any difference in applying three different
measurements of the fragrance chemical in
the perfume products. A total of 30
formulations were made ( 10 per each
measurement), and 30 prospective customers
were asked to rate the scent of the perfumes.
44. Ho: There is no significant difference in the
mean of the customers on the three
Ha: There is no significant difference in the
mean of the customers on the three
45. Non Parametric Inference
1. To test significance of difference
1.1 One sample mean and population
The marketing manager will pursue the TV
commercial if public acceptability is at least
75%. A sample survey was done to determine
this and a sample population market
acceptability was measured to test the
46. Ho : Proportion of public acceptance is at least
Ha : Proportion of public acceptance is less
than or greater than 75%.
47. 1.2 Proportions of two related or dependent
random samples. McNemar Test ( n>30)
The President of the Philippines wanted to
know if there is any difference in people’s
satisfaction rating after his one year of
presidency. A survey was done among the
people before and after his one year of
presidency whether they are generally
satisfied or not. ( paired nominal data)
48. Ho: The proportion of satisfied people is the
same before and after.
There is no significant difference in the
proportion of satisfied people before and after.
Ha: The proportion of satisfied people after is
significantly different before his one year of
49. 1.3 Proportion of K - dependent random
samples: Cochran’s Q Test
Using the example above :
The president wanted to know the
proportion of satisfied people among the
members of the society: above average ,
average and the poor or below average.
50. 1.4 two independent random samples Mann –
Whitney / U test or Sum of Ranks
A company ranked its salespeople based on
sales and it was noted that many in the top
ranks came from Metro Manila and Visayas.
The sales manager wanted to know if there
was any difference between those from M.M
51. 1.5 k - independent random samples - Kruskal
A company tested its computer product with
three different specifications . Customers
were asked to rate the computer product. the
ratings were then ranked on the overall across
the three different specifications
52. Statistical Treatment of Data
The following statistical tests were used to
analyse the gathered data: frequency and
percentage, weighted mean
Frequency and Percentage. This was used to
describe the profile of the respondents.
The formula is:
% = f x 100
% = percentage,
f = frequency of responses, and
N = total number of respondents
Weighted Mean. This was computed to
determine the average response of the
respondents on the various factors considered
in the study.
54. Formula :
WM = N
WM = weighted mean,
W = weights assigned,
F = frequencies for each option,
∑WF = sum of all weighted scores
obtained by a sample, and
N = number of respondents in the
55. Likert Scale Method
For verbal interpretation of the computed weighted means,
the following intervals was used:
Weight Limits Verbal Interpretation
5 4.50 – 5.00 Strongly Agree SA
4 3.50 – 4.49 Agree A
3 2.50 – 3.49 Moderately Agree MA
2 1.50 – 2.49 Disagree DA
1 1.00 – 1.49 Strongly Disagree SA
56. Pearson Product Moment Correlation. This is used to
determine the significance of relationship among the
given variables such as students’ performance in the
basic education and the teaching competencies of
Analysis of Variance . This is used to test the
difference of means of two or more groups that
are to be determined at one time.
t – Test . This is used to test the significant of
difference between two independent variables.
57. Decision of Hypothesis
If the computed results of the test of statistics
is lower than the critical value of the test
statistics , the null hypothesis is accepted
at 0.05 level of significance.
If the computed results of the test statistics
is greater than the critical value of the test
statistics , the null hypothesis is rejected at
0.05 level of significance.
58. In reporting statistical tests of significance,
include information concerning the value of
the test, the degree of freedom, the
probability level and the direction of the
The findings are compared and contrasted
with that of other previous studies and
interpretations are made thereof.
59. Chapter 4
Analysis, Presentation and Interpretation of
Analysis is the process of breaking up the whole
study into its constituent parts of categories
according to the specific questions under the
statement of the problem.
Presentation the process of organizing data into
logical , sequential and meaningful categories
and classification to make them amenable to
study and interpretation.
60. Textual presentation uses statement with
numerals or numbers to describe data. The
aim is to focus attention to some important
data and to supplement tabular presentation.
61. Chapter 5
Summary of Findings, Conclusions and
Summary of Findings
There should be a brief statement about the main
purpose of the study, the population or respondents,
period of the study, method of research used,
research instrument and sampling design.
The findings should be in textual form . The specific
questions should follow the order they are given
under the SOP.
62. No deduction, nor inference nor
interpretation should be made otherwise it
will be duplicated in the conclusion.
Only important findings, the highlights of the
data, should be included in the summary,
especially those upon which the conclusions
should be based.
Findings are not explained nor elaborated
upon anymore. It should be stated concisely.
No new data should be introduced.
Conclusions are inferences, deductions,
abstractions, implications, interpretations,
general statements and/or generalization
based upon the findings.
They should not contain any numerals
because numerals generally limit the forceful
effect or impact and scope of generalization.
No conclusion should be made that are not
based upon the findings.
64. It should appropriately answer the specific
questions in the SOP
It should be formulated concisely, brief, and
short, to convey all the necessary information
resulting from the study.
It should not be a repetitions of any
statements anywhere in the study.
Recommendations are appeal to people or
entities concerned to solve or help solve the
problem discovered in the inquiry.
No recommendations should be made for a
problem , or any thing that has not been
discovered or discussed in the study.
It should aim for the ideal but they must be
feasible, practical and attainable and should
be logical and valid.
66. It should be addressed to the persons,
entities, agencies or offices who or which are
in position to implement them.
Last, there should be recommendation for
further research on the same topic in other
places and other variables to verify, amplify or
negate the findings of the study.
This contains a complete list of references
used in the study.
The format is APA Manual of 1964.
This contains all the supplementary materials of
68. QUALITIES OF A GOOD RESEARCH