Research Data Interpretation
RESEARCH
DATA
INTERPRE
T
A
TION
By
Dr. Zaryab Khalid
Class: BS Botany
Semester: 7
th
Subject: Research Methodology
2
‘All
meanings,
we
know,
depend
on
the
key
of
interpretation.’
-George
Eliot
Principles
of Analysis
and
Interpretation
Data
,
as
used
in
behavioral research,
means
research
results
from
which
inferences
are
drawn:
usually
numerical
results,
like scores
of
tests
and
statistics such as
means,
percentages,
and
correlation
coefficients.
Analysis
means
the
categorizing, ordering,
manipulating,
and summarizing of
data
to
obtain
answers
to
research
questions.
Interpretation
takes
the results
of
analysis,
makes
inferences
pertinent
to
the
research
relations
studied, and
draws
conclusions
about
these
relations.
Methods
of
data
interpretation
Direct visual
observations of
raw
data
After
organizing
the
data
in
tables
After
making Graphical
representations
After
calculations
using numerical
/
statistical
methods
After
mathematical
modelling
D
AT
A
Data
is
known
to
be
crude
information
and not
knowledge by
itself.
The
sequence from
data
to
knowledge
is:
from Data
to
Information,
from
Information
to
Facts,
and
finally,
from
Facts
to
Knowledge.
D
AT
A
Data
becomes
information,
when
it
becomes
relevant
to
your
decision
problem.
Information
becomes
fact,
when
the
data
can
support
it.
Facts
are
what
the
data
reveals.
However
the
decisive
instrumental (i.e.,
applied)
knowledge
is
expressed
together
with
some statistical
degree
of
confidence.
Fact
becomes
knowledge,
when
it
is
used in the
successful completion
of a decision
process.
massive
amount of facts
are
integrated
as
knowledge.
Usefulness
and
utility
of
research
findings
lie
in
proper
interpretation.
Interpretation
is
a
basic
component
of
research.
After
collecting
and
analyzing
the
data,
the
researcher
has
to
accomplish
the task
of
drawing inferences
followed
by report
writing.
This
has
to
be done
very
carefully,
otherwise
mis
conclusions
may
be
drawn
and
the
whole
purpose
of
doing
research
may
get
vitiated.
It
is
only
through
interpretation
that
the
researcher
can
expose
relations
and
processes
that
underlie
his
findings.
Meaning
of
Interpretation
Interpretation
refers
to
the
task
of
drawing inferences
from
the
collected
facts
after
an
analytical
and or
experimental
study.
In
fact,
it
is
a
search
for
broader
meaning
of
research
findings.
The
task
of
interpretation
has
two
major
aspects
viz.,
the
effort
to
establish
continuity
in
research
through
linking the results
of a
given
study
with
those
of
another,
and
the
establishment
of
some
explanation
concepts.
“I
n one sense,
interpretation
is
concerned
with
relationships within
the
collected
data,
partially
overlapping
analysis.
Interpretation
also
extends
beyond
the
data
of
the
study
to
inch
the
results
of
other
research,
theory
and
hypotheses.
”
Interpenetration
is the
device
Thus, interpenetration
is the
device through
which
the
factors
that
seem
to
explain
what
has
been observed
by
researcher
in the
course
of
the
study
can
be
better
understood
and
it
also
provides
a
theoretical
conception
which
can serve
as a guide
for
further
researches.
Why
Interpretation?
Interpretation
is
essential
for
the
simple
reason
that the usefulness
and
utility
of
research
findings
lie
in
proper
interpretation.
It
is
being
considered
a
basic
component
of
research
process
because
of
the
following
reasons:
Through
interpretation
It
is
through interpretation
that the
researcher
can
well
understand
the
abstract
principle
that
works
beneath
his
findings.
Through
this he can
link
up
his
findings
with
those of other
studies,
having
the same
abstract
principle,
and
thereby
can predict
about the
concrete
world
of
events.
Fresh
inquiries
can
test
these
predictions
later
on.
This
way
the
continuity
in
research
can
be
maintained.
Interpretation
of
the
findings
The
interpretation
of the
findings
of
exploratory
research
study often results
into hypotheses
for
experimental
research
and as
such
interpretation
is
involved
in the
transition
from exploratory
to
experimental
research.
Since
an
exploratory
study does
not
have
a
hypothesis
to
start
with,
the
findings
of
such
a
study
have
to
be
interpreted
on a
post
factum
basis
in
which
case
the
interpretation
is
technically
described as
‘post
factum’
interpretation.
Technique
of
Interpretation
The
task of
interpretation
is not an easy
job,
rather
it
requires
a
great
skill
and
dexterity
on
the
part
of
researcher.
Interpretation
is
an
art
that
one
learns
through
practice
and
experience.
The
researcher
may,
at
times,
seek
the
guidance
from
experts for
accomplishing
the task of
interpretation.
The technique of
interpretation
The
technique
of
interpretation
often
involves
the
following
steps:
■
1.
Researcher
must
give
reasonable explanations
of the
relations which he/she has found
and he/she
must
interpret
the
lines
of
relationship
in
terms
of the
underlying
processes
and
must
try
to
find
out
the
thread
of
uniformity
that
lies
under the
surface
layer
of
his diversified
research
findings.
■
In fact, this is the
technique
of
how
generalization
should be
done
and
concepts
be
formulated.
2.
Extraneous
information, if
collected
during
the
study,
must
be
considered
while interpreting
the
final
results
of
research
study,
for
it
may
prove
to
be a
key
factor
in understanding the
problem
under
consideration.
3.
It
is advisable,
before
embarking upon
final
interpretation,
to
,
consult
someone
having
insight
into
the
study
and
who
is
frank
and
honest
and will
not hesitate
to
point out
omissions
and
errors
in logical argumentation.
Such a
consultation
will
result
in
correct
interpretation
and,
thus,
will
enhance
the utility
of
research
results.
4.
Researcher
must
accomplish
the task
of
interpretation
only
after considering
all
relevant
factors affecting the
problem
to
avoid
false
generalization.
He
/she
must be in no
hurry
while interpreting results,
for
quite often
the
conclusions,
which
appear
to
be
all
right
at
the
beginning,
may
not
at
all
be
accurate.
Precautions
in
Interpretation
One
should
always
remember that
even
if
the
data
are
properly
collected
and
analyzed,
wrong
interpretation
would
lead
to
inaccurate
conclusions.
It
is, therefore,
absolutely
essential
that
the
task
of ,
interpretation
be
accomplished
with
patience
in an
impartial manner
and
also
in
correct
perspective.
For
correct
interpretation
Researcher
must
pay
attention
to
the
following
points
for
correct
interpretation:
(i)
At
the
outset,
researcher
must
invariably
satisfy
himself
that
(a)
the
data
are
appropriate,
trustworthy
and
adequate
for
drawing
inferences;
(b)
the data
reflect
good
homogeneity;
and
that
(c)
proper
analysis
has
been
done
through
statistical
methods.
(ii)
The
researcher
must
remain
cautious
about
the
errors that can possibly arise
in
the
process
of
interpreting
results.
Errors
can
arise
due
to
false
generalization
Errors can arise due
to
false
generalization
and/or due
to
wrong interpretation
of
statistical
measures,
such
as
the application
of findings
beyond
the
range
of
observations, identification
of
correlation
with
causation
. and
the
like.
Another
major
pitfall
is
the
tendency
to
affirm
that
definite relationships
exist on
the basis
of
confirmation
of
particular
hypotheses.
Researcher
must remain
vigilant
In
fact,
the
positive
test
results
accepting
the
hypothesis
must
be
interpreted
as “being in
accord”
with
the
hypothesis, rather
than as
“confirming
the
validity
of the
hypothesis”.
The
researcher
must remain vigilant
about
all
such
things
so
that
false
generalization
may
not
take
place.
He/she
should
be
well
equipped
with
and
must
know
the
correct
use
of
statistical
measures
for
drawing
inferences concerning
his
study.
Researcher
must
always
keep
in
view
that the
task of
interpretation
is
very
much intertwined
with
analysis
and
cannot
be
distinctly
separated.
As
such
he
must
take
the
task
of
interpretation
as
a special
aspect
of
analysis
and
accordingly
must
take
all
those
precautions
that one
usually
observes
while
going
through
the
process
of
analysis
viz., precautions
concerning
the
reliability
of
data, computational checks,
validation
and
comparison
of
results.
Data Interpretation
Methods
Data
interpretation
may
be
the
most
important
key
in
proving
or
disproving
your
hypothesis.
It
is
important
to
select
the
proper
statistical
tool
to
make
useful
interpretation
of
your
data.
If
you
pick
an
improper
data
analysis
method,
your
results
may
be
suspect
and lack
credibility.
Visually
scanning the
data
Before
doing
any
statistical
analyses
of
the
data
you
have
collected,
look
closely
at the
data
to
determine
the best
method
of
organizing
it
.
By
visually
scanning the
data
and
reorganizing
it,
you
may
be able
to
spot
trends
or
other
anomalies
that
may
help
you
in
your
analysis
of
the
data.
STATISTICS
Statistics
is
a
science
assisting
you
to
make
decisions
under
uncertainties
(based on
some
numerical
and
measurable
scales).
Decision
making
process
must be based
on
data
neither
on
personal
opinion
nor
on
any
belief.
What
is
Statistical
Data
Analysis?
Data
are
not
information!
To
determine
what
statistical data
analysis
is,
one
must
first
define
statistics.
Statistics
is a set of
methods
that
are
used
to
collect, analyze,
present,
and
interpret
data.
Statistical
methods
Statistical methods
are
used in a
wide
variety
of
occupations
and
help people
identify,
study,
and
solve
many
complex
problems.
In the business and
economic
world,
these
methods
enable
decision
makers
and
managers
to
make
informed and
better
decisions
about
uncertain
situations.
Using
statistics
to
determine
relationships
is
paramount
to
the
success
of
good
research.
Using tools
such as
ANOVA,
correlations,
Fisher
Exact
Tests,
regression,
etc.
can
predict
whether
or
not
your
research hypothesis
is
satisfied.
But,
REMEMBER
to
select
your
p-value
before
you
begin
your
research
project.
Doing
this
will
add
credibility
to
your
research.
One other important
point
to
remember
when
doing
data
analysis
is
to
use
parametric
statistics
instead
of
nonparametric
statistics
whenever
possible.
Remember
that
parametric
statistics
relies
on
the
assumptions of
normality,
which
gives
greater
power
than
nonparametric
testing.
Both parametric
and
nonparametric
statistical
tests
are
used
for
interpretation.
Statistics consists
of
Statistics
consists
of
the
principles
and
methods
for
Designing
studies
Collecting
data
Presenting
and
analysing
data
Interpreting
the
results
Statistics has
been described
as
Turning
data
into
information
Data-based decision
making.
Scientists
interpret
data
based
on
their
background
Scientists
interpret
data based
on
their
background
knowledge
and
experience;
thus,
different
scientists
can
interpret
the
same
data
in
different
ways.
By publishing their
data
and
the
techniques
they
used
to
analyze
and
interpret
those data,
scientists
give
the community the
opportunity
to
both
review
the
data
and
use
them
in
future
research.
Principles and methods of data interpretation in research, transitioning from data to knowledge through analysis and inference. Importance of proper interpretation for drawing accurate conclusions and enhancing the value of research findings.
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Presentation Transcript
RESEARCH DATA INTERPRETATION By Dr. Zaryab Khalid Class: BS Botany Semester: 7th Subject: Research Methodology
All meanings, we know, dependon the key of interpretation. -GeorgeEliot 2
Principles of Analysis and Interpretation Data, as used in behavioral research, means research results from which inferences aredrawn: usually numerical results, like scores of tests and statistics such as means, percentages, and correlationcoefficients. Analysis means the categorizing, ordering, manipulating, and summarizing of data toobtain answers to researchquestions. Interpretation takes the results of analysis,makes inferences pertinent to the research relations studied, and draws conclusions about these relations.
Methods of data interpretation Direct visual observations of rawdata Afterorganizingthedataintables After making Graphicalrepresentations After calculations using numerical/ statistical methods After mathematicalmodelling
DATA Data is known to becrude information and not knowledge byitself. The sequence from datato knowledge is: from Data toInformation, from Information to Facts, andfinally, from Facts toKnowledge.
DATA Data becomes information, when itbecomes relevant to your decisionproblem. Informationbecomesfact,whenthedatacan supportit. Factsarewhatthedatareveals. However the decisive instrumental (i.e.,applied) knowledge is expressed togetherwith some statistical degree ofconfidence.
Fact becomes knowledge, when itis used in the successful completion of a decisionprocess. massive amount of factsare integrated asknowledge.
Usefulnessand utilityof research findings lie inproper interpretation. Interpretationisabasiccomponentof research. Aftercollectingandanalyzing thedata, theresearcher has to accomplish the task of drawing inferences followed by reportwriting. This has to be done very carefully, otherwise mis conclusionsmaybedrawnand thewholepurposeof doing research may getvitiated. It is only through interpretation that the researcher can expose relations and processes that underlie his findings.
Meaning of Interpretation Interpretationreferstothetaskof drawing inferences from the collected facts after an analytical and or experimentalstudy. In fact, itisasearch forbroadermeaningof research findings. Thetaskof interpretation hastwomajoraspectsviz., theefforttoestablishcontinuityinresearch through linking the results of a given study with those of another,and theestablishmentof someexplanation concepts.
In one sense, interpretation is concerned with relationships within the collected data,partially overlappinganalysis. Interpretation also extends beyond the data of the study to inch the results of other research, theory andhypotheses.
Interpenetration is the device Thus, interpenetration is the device through which the factors that seem to explain what has been observed by researcher in the courseof thestudycan bebetterunderstood and it also provides a theoretical conception which can serve as a guide for further researches.
Why Interpretation? Interpretation is essential for thesimple reason that the usefulness and utility of research findings lie in proper interpretation. Itis beingconsideredabasiccomponentof research process because of the following reasons:
Through interpretation It is through interpretation that the researcher can well understand the abstract principle that works beneath hisfindings. Through this he can link up his findings with those of other studies, having the same abstract principle, and thereby can predict about the concrete world of events. Fresh inquiries cantest these predictions lateron. Thiswaythecontinuityinresearchcanbe maintained.
Interpretation of the findings The interpretation of the findings of exploratory research study often results into hypotheses for experimental research and assuch interpretation is involved in the transition from exploratory to experimentalresearch. Since an exploratory study does not have a hypothesistostartwith, thefindingsof sucha study have to be interpreted on a post factum basisinwhichcasetheinterpretationis technically described as postfactum interpretation.
Technique of Interpretation The task of interpretation is not an easy job, ratheritrequiresagreatskillanddexterityonthe part of researcher. Interpretationisanartthatonelearnsthrough practice andexperience. Theresearchermay,attimes,seektheguidance from experts for accomplishing the task of interpretation.
The technique of interpretation The technique of interpretationoften involves the followingsteps: 1. Researcher must give reasonable explanations of the relations which he/she has found and he/she must interpret the lines of relationship in terms of the underlying processes and must trytofindoutthe threadof uniformitythatlies under the surface layer of his diversified researchfindings. In fact, this is the techniqueof how generalization should be done and concepts beformulated.
2. Extraneous information, if collected during the study, must be considered while interpreting the final results of research study, for it may prove to be a key factor in understanding theproblem underconsideration.
3.It is advisable, before embarking upon final interpretation, to,consultsomeonehaving insightintothestudyand who is frank and honest and will not hesitate to point out omissions and errors in logical argumentation. Such a consultation will result in correct interpretation and, thus, will enhance the utility of researchresults. 4. Researcher must accomplish the task of interpretationonly after considering all relevant factors affecting the problem to avoid false generalization. He /she must be in no hurry while interpreting results, for quite often the conclusions, whichappeartobeall rightatthebeginning, maynotatall beaccurate.
Precautions in Interpretation One should always remember that even if thedataareproperlycollectedandanalyzed, wrong interpretation would lead to inaccurateconclusions. It is, therefore, absolutely essential thatthe task of , interpretation be accomplished with patience in an impartial manner and also in correctperspective.
For correct interpretation Researchermustpayattentiontothefollowing points for correctinterpretation: (i)Attheoutset,researchermustinvariablysatisfy himself that (a) thedataareappropriate, trustworthyand adequate for drawinginferences; (b) the data reflectgood homogeneity; and that (c)properanalysis has beendonethroughstatistical methods. (ii) Theresearchermustremaincautiousaboutthe errors that can possibly arise in the process of interpreting results.
Errors can arise due to false generalization Errors can arise due to false generalization and/or due to wrong interpretation of statistical measures, suchas the application of findings beyond the range of observations, identification of correlation with causation . and thelike. Anothermajorpitfall isthetendencytoaffirm that definite relationships exist on the basis of confirmation of particularhypotheses.
Researcher must remain vigilant Infact, thepositivetestresultsacceptingthe hypothesis must be interpreted as being in accord with the hypothesis, rather than as confirming the validity of thehypothesis . The researcher must remain vigilant about all suchthingssothatfalsegeneralization maynot takeplace. He/she should be well equipped with and must know the correct use of statistical measures for drawing inferencesconcerning hisstudy.
Researcher must always keep in view that the task of interpretation is very much intertwined withanalysisandcannotbedistinctlyseparated. Assuch hemusttakethetaskof interpretationas a special aspect of analysis and accordingly must take all those precautions that one usually observes while going through the process of analysis viz., precautions concerning the reliability of data, computational checks, validation and comparison ofresults.
Data Interpretation Methods Datainterpretation maybethemostimportantkeyin proving or disproving yourhypothesis. Itisimportanttoselecttheproperstatisticaltool to make useful interpretation of yourdata. If youpickan improperdataanalysismethod,your resultsmaybesuspectand lackcredibility.
Visually scanning the data Before doing any statistical analyses of thedatayouhavecollected, lookclosely at the data to determine the best method of organizing it. By visually scanning the data and reorganizing it, you may be able to spot trendsorotheranomaliesthatmayhelp youinyouranalysisof thedata.
STATISTICS Statisticsisascienceassistingyouto make decisionsunder uncertainties (based on somenumerical and measurablescales). Decision making process must be based on dataneitheronpersonalopinion noronany belief.
What is Statistical Data Analysis? Data are not information! To determine what statistical data analysis is, one must firstdefine statistics. Statistics is a set of methods that are used to collect, analyze,present, and interpretdata.
Statistical methods Statistical methods are used in a wide variety of occupations and help people identify, study, and solve manycomplex problems. In the business and economic world, these methods enable decisionmakers and managers to make informed and better decisions about uncertain situations.
Usingstatisticstodeterminerelationshipsis paramount to thesuccess of good research. Using tools such as ANOVA, correlations, Fisher ExactTests,regression,etc.canpredictwhetheror notyour research hypothesis is satisfied. But, REMEMBERtoselectyourp-valuebeforeyou begin your researchproject. Doing thiswilladdcredibilitytoyourresearch.
One other important point to remember when doingdataanalysisistouseparametricstatistics instead of nonparametric statistics whenever possible. Rememberthatparametricstatisticsreliesonthe assumptions of normality, which gives greater power than nonparametrictesting. Both parametric and nonparametricstatistical tests are used forinterpretation.
Statistics consists of Statisticsconsistsof theprinciplesand methodsfor Designingstudies Collectingdata Presenting and analysingdata Interpreting theresults Statistics has been describedas Turning data intoinformation Data-based decisionmaking.
Scientistsinterpret data based on their background Scientists interpret data based on their background knowledge and experience; thus, differentscientistscan interpretthesamedata in differentways. By publishing their data and the techniques they used to analyze and interpret those data,scientists give the community the opportunity to both reviewthedataand usethem infutureresearch.
