3. RESEARCH -
• Re+ search
• An attempt to elicit facts
• An attitude of enquiry
• Journey known to unknown
• “Research is creative and systematic work undertaken
to increase the stock of knowledge. It involves the
collection, organization and analysis of information to
increase understanding of a topic or issue. A research
project may be an expansion on past work in the field”
4. PROCESS OF RESEARCH
1. Define Research topic
2. Review of literature
3. Define your objective
4. Formulate the hypothesis
5. Prepare your research design
6. Data collection
7. Data Analysis
8. Data Interpretation
9. Report Writing
5.
6. OBJECTIVE OF RESEARCH-
• Research introduce you to new ideas.
• Research gives us latest information.
• Research impact is real change in the real
world.
• Research build a better understanding
decision making and analytical ideas to
facilitate better result in every field.
• It brings public awareness.
• It result in many predictions theories and
principles.
7. OBJECTIVE OF RESEARCH-
• It leads to great observation.
• It helps in decision making and motivate
others.
• It helps in understanding the society.
• It is most valuable tool to understand and
disapprove lies uphold the truth and build on
to create authentic and reliable information.
• Different kinds of impact including attitudinal,
awareness, economic, social, policy cultural
and health.
8. TYPES OF RESEARCH-
QUALITATIVE RESEARCH
• Interpretive research
• Case study research
• Ethnography research
• Grounded theory research
• Historical research
• Narrative research
• Phenomenological research
9. QUANTITATIVE RESEARCH-
• Descriptive research
• Correlation research
• Comparative research
• Experimental research
• Quasi-experimental research
• Predictive exploratory research
• Survey research
10. CONSTRAINTS IN RESEARCH-
• Time constraints
• Financial constraints
• Technical constraints
• Cultural constraints
• Knowledge constraints
• Ethical constraints
11. OTHER LIMITATIONS-
• Limited access to information.
• Conflicts on biased views and personal issues.
• Research design limitations.
• Impact limitation.
• Data or statistical limitation.
• Formulation of your objective and aims.
• Implementation of your data collection method.
• What are sample size.
• How to structure your research limitation.
• Lacking previous studies in same field.
12. CONCEPTS OF DATA-
• Data refers to raw input that when processed
or arranged makes meaningful output.
Information is usually the processes outcome of
data. When data is processed into information ,
it becomes interpretable and gains significance.
• Data is not the same as information.
• Data is independent of a relationship(just
numbers or words)until it is linked then it
becomes knowledge.
13. TYPES OF DATA-
Qualitative data-
Qualitative data can’t be expressed as a number
and can’t be measured. Qualitative data
consists of words, pictures and symbols not
numbers. It also called categorical data because
the information can be sorted by category not by
number. It can answer questions such as “how
this has happened or and “why this has
happened”.
Examples- Haircolour , your favorite holiday
destination , names, nationality
Types -
Nominal data
Ordinal data
14. TYPES OF DATA-
Quantitative data-
Quantitative data seems to be the easiest to
explain. It answers key questions such as “how
many” “how much” and “how often”.
Quantitative data can be expressed as a number
or can be quantified . It can be measured by
numerical variables.
Quantitative data are easily amendable to
statistical manipulation and can be represented
by wide variety of statistical types of graphs and
charts.
Examples- scores on test and exams, the weight
of a person , the shoe size, temperature in a
room.
15. NOMINAL SCALE-
• Most elementary form of measurement.
• Name and categories.
• Each category is assign a number.
• No order, no distance, no arithmetic
relationship, no origin.
• EXAMPLE- GENDER - male female
• HAIR COLOR - black brown
• Mode is only measure of central tendency.
• Chi-square test, fisher test, can use for this
data.
16. ORDINAL SCALE
• Places events in order or ranks.
• No distance and no origin.
• Implies greater than / less than relationship.
• EXAMPLE- Ranks- 1,2,3.
• letter grades – A,B,C
• Economic status – low ,medium
• Median is the popular measure of central
tendency.
• Percentile , decentile is used.
• Non-parametric test can use for this data.
17. INTERVAL SCALE-
• Order and distance.
• Interval between two points are adjusted in
terms of some rules that has been
established for purpose of making units
equal.
• No unique origin and no absolute zero.
• EXAMPLE- Time of each day, temperature,
• dress size
• Mean, standard deviation
• T-test, f-test can use .
18. RATIO SCALE-
• Order, distance, and unique origin.
• Absolute zero.
• All mathematical operation can apply .
• Geometric mean , harmonic mean
• All parametric test.
• EXAMPLE- Height, weight, age , salary
• NOMINAL – She is young, marry is old.
• ORDINAL- She is younger than marry.
• INTERVAL- She is 20 yr younger than marry.
• RATIO- She is twice as young as marry.
19. DISCRETE DATA -
Discrete data is a count that involves only
integers. The discrete values cannot be sub-
divided into parts.
EXAMPLES- The number of students in a
class.
The number of test questions you
answered.
You can count whole individuals or students.
You can’t count 1.5 students.
20. CONTINUOUS DATA-
Continuous data is information that could be
meaningfully divided into finer levels. It can be
measured on a scale or continuum and can
have almost any numeric value.
EXAMPLES- The amount of time required to
complete a project .
The height of children.
The speed of cars.
You can measure your height at very precise
scales- meters, centimeters, millimeters etc.
21. INFORMATION AND INTELLIGENCE-
Information- Information is data that contain a
message or knowledge of something and also it
can be shortened as info as well. Everything a
person knows can be regarded as knowledge
and this knowledge is usually in the form of
information. Information can give answers to
problems that arise in humans, since they carry
knowledge. It can be seen that somebody
requires his her intelligence to acquire
information. Information may not come to a
person, but the person may have to search for
it. Thus, it needs to have intelligence. In one’s
process of education, he/she collects
information and expands their existing
knowledge.
22. INTELLIGENCE-
Intelligence can be defined as the intellectual
capacity of a human being or any other
species. As mentioned above intelligence is
one of the main requirements to have access
to different information. Intelligence is usually
characterized by the ability to perceive
something, understanding, logical thinking
and self awareness, etc. Due to intelligence,
human beings gain the cognitive ability to
learn and to analyze various things.
Moreover, intelligence is the driving force of
humans to solve their problems with
23. WHAT IS THE DIFFERENCE BETWEEN
INFORMATION AND INTELLIGENCE-
• Information is available to any person,
anywhere in the world equally.
• In contrast, intelligence is something innate to
humans and the level of intelligence varies from
one person to another.
• Information collection of a person depends on
the level of that person’s intelligence. In that
sense, there is an interrelationship between the
two terms.
• However, both information and intelligence are
important to humans because they survive their
lives based on these two factors.
24. CHARACTERISTICS OF VALUABLE INFORMATION
• Accessible- Information should be easily
accessible by authorized users so they can
obtain it in the right format and at the right time
to meet their needs.
• Accurate- Accurate information is error free. In
some cases, inaccurate information generated
because inaccurate data is fed into the
transformation process. This is commonly called
garbage in, garbage out (GIGO).
• Complete – Complete information contains all
the important facts. For example, an investment
report that does not include all important costs
is not complete.
25. TO BE CONTINUED-
Economical – information should also be
relatively economical to produce. Decision
makers must always balance the value of
information with the cost of producing it.
Flexible- flexible information can be used for a
variety of purposes, for example, information on
how much inventory is on hand for a particular
part can be used by a sales representative in
closing a sale, by a production manager to
determine whether more inventory is needed,
and by a financial executive to determine the
total value the company has invested in
26. TO BE CONTINUED-
Relevant- Relevant information is important to the
decision maker. Information showing that
lumber prices might not be relevant to a
computer chip manufacturer.
Reliable- Reliable information can be depend on.
In many cases, the reliability of the information
depends on the reliability of the data collection
method. In other instances, reliability depends
on the source of the information.
Secure – information should be secure from
access by unauthorized users.
27. TO BE CONTINUED-
Simple – Information should be simple, not
overly complex. Sophisticated and detailed
information might not be needed . Infact , too
much information can cause information
overload, whereby a decision maker has too
much information and is unable to determine
what is really important.
Timely –Timely information is delivered when it
is needed. Having a mobile application
show’s last week’s weather conditions will
not help when trying to decide what coat to
28. TO BE CONTINUED
Verifiable –Information should be verfiable.
This mean that you can check it to make
sure it is correct , perhaps by checking many
sources for the same information , such as
code resources and in providing any
information should contain link to a
reference.
29. VARIABLES-
Any characteristics which is subject to change
and can have more than one value such as
age,intelligence.
TYPES OF VARIABLES-
Dependent variables – variables affected by
the independent variables.
It responds to the independent variable.
We always test the dependent variables
outcomes because independent variables
don’t changes.
30. INDEPENDENT VARIABLES-
An independent variable is the variable you
manipulate, control, or vary in an
experimental study to explore its effects on
dependent variable. It’s called “independent”
because it’s not influenced by any other
variables in the study. Independent variables
are also called explanatory variables.
EX- “Promotion affects employees motivation”
Independent variable- Promotion
Dependent variable- employees motivation
31. INTERVENING/ MEDIATING VARIABLE
• It is a variable whose existence is inferred
but it can’t be measured.
• Established link between DV and IV.
• It is caused by independent variable and
itself a cause of dependent variable.
EX- “Higher education typically leads to higher
income”.
Higher education- independent variable
Higher income- dependent variable
Better occupation- intervening variable
32. EXTRANEOUS VARIABLE-
• In real life situation there can be many factors
that may affect the outcome.
• If these variables affects our outcome then it is
called “confounding variable”.
• If extraneous variable > independent variable.
• CONSTANT VARIABLE-
• It is variable that is not allowed to be changed
unpredictably during an experiment.
• Ex- if you are examining “how electricity affects
experimental subjects you should keep voltage
constant, otherwise the energy supplied will
change as the voltage will be changed.
33. BINARY/ DICHOTOMOUS VARIABLE-
Bi or Di means two , observation (dependent
variable) that occurs in one of two possible
states . Example- improved/ not improved
success/ failure
POLYCHOTOMOUS VARIABLE-
More than 2.Variables that can have more than
two possible values. The usual inference is to
categorical variables with more than two
categories.
ENDOGENOUS VARIBLE- COME FROM INSIDE
THE STUDY
EXOGENOUS VARIABLE – COME FROM
OUTSIDE THE STUDY
34. HYPOTHESIS -
• It’s a prediction
• An assumption
• Logical relationship between two variables.
• Capable of being tested by scientific methods.
• CHARACTERISTICS-
• Clear and precise.
• Simple terms.
• Must be specific.
• Able to relate to a variable.
• Must be testable with in a reasonable time.
• Must explain the facts which most need explaining.
• Facilitate the formulation of theory.
35. TYPES OF HYPOTHESIS-
Null hypothesis-
• Denoted by H0.
• This says that there is no significant
difference between A and B or sample and
population.
• No observed effect
• No change in opinion or actions.
• ALTERNATIVE HYPOTHESIS-
• Denoted by H1 OR Ha.
• It says that there is significant difference
36. DIRECTIONAL HYPOTHESIS-
• also known “one tail test”.
• Use the sign <, >.
• It states the direction of the predicted
difference.
NON- DIRECTIONAL HYPOTHESIS-
• Also known as “two tail test”.
• States that there will be a difference but we
don’t know the direction that difference will
be.
• Use the sign not equal .
37. TYPE 1 ERROR-
• False positive.
• It is incorrect rejection of true null hypothesis.
• Denoted by Greek letter alpha.
• Short cut to learn = R-R ( right – reject).
TYPE 2 ERROR-
• False negative.
• It is incorrect acceptance of false null
hypothesis.
• Denoted by Greek letter beta
• Short cut to learn= W-A(wrong – accept).
38. PROCESS OF TESTING HYPOTHESIS-
• Specify the null hypothesis.
• Specify the alternative hypothesis.
• Set the level of significance.
• Collect data.
• Calculate a test statistic.
• Construct acceptance /rejection regions.
• Based on 5 and 6 step , Draw a conclusion .
“Hypothesis testing is an act in statistics whereby
an analyst test an assumption regarding a
population parameter. It is used to assess the
plausibility of a hypothesis by using sample
data.”
39. RESEARCH DESIGN-
• Research design is the framework of research
methods and techniques chosen by a researcher.
• It is a plan of what data to gather, from whom, how
and when to collect the data and how to analyze
the data obtained.
• It can be say that research design is the blueprint
of whole research.
• CHARACTERISTICS OF RESEARCH DESIGN-
• Reliability
• Validity
• Generalization
• Neutrality
40. ELEMENTS OF RESEARCH DESIGN-
• Purpose statement
• Technique
• Methodology
• Objections
• Settings
• Timeline
• Measurement
• Analysis method
• TYPES OF RESEARCH DESIGN –
1 Exploratory 2. Descriptive 3. Diagnostic 4.
41. EXPLORATORY RESEARCH
• Fundamental research to know the problem
which is not clearly defined yet.
• Helps to have better understanding of the
problem.
• It is initial research which forms the basis of
more conclusive research.
• Tends to new problem on which little or no
previous research has been done.
• This type of research does not intend to offer
final and conclusive solution to existing
problem.
• EXAMPLE – Why our sales is declining?
42. DESCRIPTIVE RESEARCH-
• Also known as “statistical research”.
• Tell us what is/what was.
• They are at present with the researcher having
no control over variables.
• It is used to describe various aspects of
phenomena.
• Ascertain and describe the characteristics of
issue.
• Describe of the state of affairs as it exist.
• EXAMPLE – survey and facts findings,
observation, case study.
43. DIAGNOSTIC RESEARCH-
• In diagnostic research firstly we determine the
cause of the problem.
• Discovering what is happening and why it is
happening and what can be done about.
• Determine frequency with something occurs or
its association with something else.
• EXAMPLE- A type of test used to help
diagnose a diseases or condition.
Mammograms and colonoscopies are example
of diagnostic procedure.
44. CAUSAL RESEARCH
• Also known as co-relational
research/experimental research/explanatory
research.
• Answer what will be?
• Research have control over the experiment
variables.
• To identify the extent and nature of cause and
effect relationship.
• Explain the pattern of relationship between
variables.
• EXAMPLE- Price and demand (price is cause
45. SOME OTHER TYPES OF RESEARCH-
LONGITUDINAL RESEARCH-
• Researchers repeatedly examine the same
individuals to detect any changes that might occur
over a period of time.
• In it there is only one variable studying on a same
sample over a long period of time.
CROSS- SECTIONAL RESEARCH-
A cross sectional study is a type of research design
in which you collect data from many different
individual or different sample at a single point of
time. In it you observe variables without
46. QUASI- EXPERIMENTAL RESEARCH-
• Sort of half experiment.
• Researcher does not have control over the
experiment and variables.
• Mainly done in natural setting and in economics,
sociology, public administration, political sciences
etc.
• EXAMPLE- Increase in population, on it we can
research but can’t control.
HISTORICAL RESEARCH-
• When we study about the old concepts and
trends.
EXAMPLE- Evolution of human resource
47. EX-POST FACTO RESEARCH-
• When any event happened in past in which
there is dependent and independent variables.
• In it we experiment not only study the facts.
• Also known as causal comparative research.
• Independent variables not manipulated and
groups are already formed.
• EXAMPLE- Impact of any diseases on death
rate of population.
48.
49. ERRORS-
• The total error is the variation between the true
mean value in the population of the variable of
interest and the observed mean value obtained
in the marketing research project.
• Random sampling error is the variation
between the true mean value for the population
and the true mean value for the original sample.
• Non-sampling errors can be attributed to
sources other than the sampling including error
in problem definition, interviewing methods, and
data preparation and analysis.
50. ERRORS-
• Non- response errors arises when some of the
respondents included in the sample do not
respond.
• Response errors arises when respondents give
inaccurate answers or their answers are mis-
recorded or misanalyzed.
