basic research tips and techniques

1. Advance Research one
Survey Research
Lecture-9
Muhammad Shafiq,
University of Balochistan, Quetta

2. 1. Basic Definitions for surveys
Survey: a research technique in which information
(primary data) is gathered from a sample of
people to make generalizations.
Primary data: data gathered and assembled
specifically for the project at hand.
Sample of the survey: respondents who are asked to
provide information, assuming that they can
represent (possess same features with) a target
population.

3. POPULATION
SAMPLESample:
Subset of a larger population
Selecting a Sample
Sampling:
• Who is to be sampled?
• How large a sample?
• How will sample units be selected?

4. Basic Definitions for sampling
(http://www.stats.gla.ac.uk/steps/glossary/sampling.html)
Target population: the group about which the
researcher wishes to draw conclusions and make
generalizations
Random sampling: selecting a sample from a
larger target population where each respondent is
chosen entirely by chance and each member of
the population has a known, but possibly non-
equal, chance of being included in the sample.

5. Basic Definitions for data collection
Surveys ask respondents (who are the subjects of the
research) questions by use of a questionnaire.
Respondent: The person who provides information
(primary data) by answering a questionnaire or an
interviewer’s questions.
Questionnaire: a list of structured questions
designed by the researchers for the purpose of
codifying and analyzing the respondents’ answers
scientifically.
Advantages of Surveys: Quick, Inexpensive, Efficient,
Accurate, Flexible way of gathering information.

6. 2. Errors in Surveys
2.1. Random Sampling Error
2.2. Systematic Error (sample bias)
2.2.1. Respondent error
* Nonresponse bias
* Response bias
2.2.2. Administrative error
* Data processing error
* Sample selection error
* Interviewer error
* Interviewer cheating

7. 2.1. Random Sampling Error
• Even if randomly selected, samples may possess
different characteristics than the target population
(the likelihood of bias is reduced but still exists)
• This is a statistical fluctuation due to chance
variation.
• Then, an important difference occurs between the
findings obtained from this sample and the
findings obtained from a possible census of the
whole target population.

8. Continue…
• Consider the hypothetic case in which a study
sample could be increased until it was infinitely
large; chance variation of the mean, or random
error, would be reduced toward zero. These are
random errors.
• Systematic errors would not be diminished by
increasing sample size.
(Bias in Research Studies,
http://radiology.rsna.org/content/238/3/780.full)

9. 2.2. Systematic Error
• Systematic error results from some mistake(s)
done in the design and/or execution of the
research.
• All types of error -except random sampling error,
are included in this definition,
• Sample bias: a persistent tendency for the results
of a sample to deviate in one direction from the
true value of the population parameter.
• Sample bias can arise when the intended sample
does not adequately reflect the spectrum of
characteristics in the target population.

10. 2.2.1. Respondent Bias
• A classification of sample bias resulting
from some respondent action or inaction
• Nonresponse bias
• Response bias

11. Nonresponse Error
• Nonrespondents: in almost every survey information
from a small or large portion of the sample cannot be
collected. These are those people who refuse to
respond, or who can not be contacted (not-at-homes)
• Self-selection bias: only those people who are
interested strongly with topic of the survey may
respond while those who are still within the same
sample but indeferent or afraid avoid participating.
• This leads to the over-representation of some extreme
positions, but under-representation of others.

12. Response Bias
• A bias that occurs when respondents tend to
answer questions with a certain inclination
or viewpoint that consciously (deliberate
falsification) or unconsciously
(unconscious misinterpretation)
misrepresents the truth.

13. Reasons of response bias
• Knowingly or unknowingly people who answer questions of
the interviewer may feel unconfortable about the truth that
they share with others, and change it in their responses.
• They may desire to show themselves as more intelligent,
wealthy, sensitive, etc. than they really are.

14. Acquiescence bias (positive answers)
Extremity bias (exaggerated answers)
Interviewer bias (answers acceptable by the interviewer)
Auspices bias (answers acceptable by the organization)
Social desirability bias (answers creating a favorable impression)
Types of Response Bias
Deliberate falsification (consciously false answers)

15. 2.2.2. Administrative Error
• Unadvertently or carelessly improper
administration and execution of the research
task
• Blunders are:
• Confusion
• Neglect
• Omission

16. Types of Administrative Errors
Data processing error: incorrect data entry, computer
programming, or other procedural errors during the
analysis stage.
Sample selection error: improper sample design (e.g.
based on incomplete databases) or sampling
procedure execution (e.g. executed in daytime while
most of the target population are working)
Interviewer error: mistakes done by the interviewer
(e.g. taking wrong or incomplete notes about the
answers of the respondents.
Interviewer cheating: filling in fake or false answers
indeed not given by the respondents.

17. 3. Classification of Survey Methods
3.1. Structure of the questionnaire:
* whether standardized questions with a limited
number of allowable answer -multiple choices
* or unstandardized open ended questions with the
possibility of being answered in numerious ways.
3.2. Level of Directness of the questions:
* whether direct/undisguised questions
* or indirect/disguised questions to hide the real
purpose of the survey

18. Classification of Survey Methods
3.3. Time basis of the Survey:
Cross-Sectional Study: data on various segments of a
target population are collected at a single moment in
time to make comparisons among segments.
Longitudinal Study: data are collected at different times
from the similar respondents to compare trends and
identify changes.
Panel Study: A longitudinal survey of exactly the same
respondents to record (in a diary) their attitudes,
behaviors, or purchasing habits over time.