This document discusses common errors in research and their implications. It begins by outlining the differences between quantitative and qualitative research approaches. Common errors for various research methods like questionnaires, interviews, experiments and observational studies are then described. These errors can lead to wrong business decisions, loss of capital, and market failures if research conclusions are flawed. Finally, steps like conducting a literature review, using statistical tools, double entry of data, pilot testing, and training of researchers are suggested to minimize errors.

1. Errors In Research
Presented By:
Team 18
Abinesh Raja M
Raghu Priya
Rajeshwaran
Sriram Kumar
Vijayalakshmi S

2. Agenda
1 Introduction To Research Errors
2 Common Errors In Research
3 Implications of Research Errors
Research Errors Leading to Marketing
4 Failure
5 Steps to Reduce Research Errors

3. Qualitative and Quantitative research
Quantitative Qualitative
Deductive Inductive
Tests hypotheses Produces theories
Positivism Phenomenology
Objectivism Constructionism
Employs measurement Does not employ measurement
Measures objective facts Constructs social meaning
Focuses on variables Focus on interactive processes
Reliability is key Authenticity is key
Independent of context Context constrained
Statistical analysis Thematic analysis

4. Quantitative Errors
Population Specification Error
Sampling Error
Selection Error
Non Response Error
Surrogate Information Error
Measurement Error
Experimental Error

5. Qualitative Errors
 Selective observation
 Inaccurate observation
 Overgeneralization
 Made-up information
 Ex post facto hypothesizing
 Illogical reasoning
 Ego involvement in understanding
 Premature closure of inquiry
 Mystification

6. Common Errors In Research
Questionnaire Studies
 Using a questionnaire to work with problems that lend
themselves better to other research techniques.
 Not giving enough care to the development of the questionnaire
and not pretesting it.
 Asking too many questions, thus making unreasonable
demands on the respondents time.
 Overlooking details of format, grammar, printing, and so on that
can influence respondents. first impression.
Interview Studies
 Not adequately planning the interview or developing the
interview guide.
 Not conducting sufficient practice interviews to acquire needed
skills.
 Failing to establish safeguards against interviewer bias.

7. Experimental Studies
 Inadvertently or otherwise treating the experimental and control groups
differently, thus leading to biased findings.
 Using too few cases, leading to large sampling errors and insignificant
results.
 Failing to divide the main groups into subgroups in situations where
subgroup analysis may produce worthwhile knowledge.
Observational Studies
 Not sufficiently training observers and thus obtaining unreliable data.
 Using an observation procedure that demands too much of the observer.
 Failing to safeguard against the observer’s disturbing or changing the
situation being observed
Relationship (Correlation) Studies
 Assuming that a correlation between pieces of data is proof of a cause-and
effect relationship.
 Using a sample in correlational research that differs on so many variables
that comparisons of groups are not interpretable.
 Selecting variables for correlation that have been found unproductive in
previous studies.

8. Implications of Research errors
Purpose: Support or Contradict a proposed business
decision….
Market Academic
Research Research
Highly important to
1.Wrong decision be error free as it
2.Loss of capitol acts as a guide for
3.Shut down future references
by many
Example:
New product Must be a good fit
development or in the view of a
market introduction single drop inside
may fail due to error an ocean.
in research

9. Exceptions
HAWTHORNE STUDIES…..
Group
PURPOSE: Status
To study the effects of
lighting and other factors Group
on employee efficiency and Internal
work efficiency….. Organizati
on

11. Research Errors -> Marketing Failures

12. Steps to Minimize Errors
A proper
literature review
Statistical tools
for adjusting Increase in
measurement sample size
error
Double entry of
Pilot testing
data
Training for
Interviewers
and observers