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Sampling Error
Prof.Dr.Chinna Chadayan.N
RN.RM., B.Sc (N)., M.Sc (N)., Ph.D (N).,
Professor
Enam Nursing College
Unit 14b
Sampling Error
Sampling is a technique
• Sampling is a technique of selecting individual members or a subset of the
population to make statistical inferences from them and estimate characteristics of
the whole population.
• Different sampling methods are widely used by researchers in market research so
that they do not need to research the entire population to collect actionable insights.
• It is also a time-convenient and a cost-effective method and hence forms the basis
of any research design.
• Sampling techniques can be used in a research survey software for optimum
derivation.
SAMPLING ERRORS
SAMPLING ERROR: is incurred when the statistical
characteristics of a population are estimated from a subset,
or sample, of that population.
For example, if one measures the height of a thousand
individuals from a country of one million, the average height
of the thousand is typically not the same as the average
height of all one million people in the country.
Sampling errors
Non-sampling errors
NON-SAMPLE ERRORS
1.Non Response Error
2.Response Error Not Control by Sample Size
Non Response Error
A non-response error occurs when units selected as part of the
sampling procedure do not respond in whole or in part
Response Errors
A response or data error is any systematic bias that occurs during data
collection, analysis or interpretation
1. Respondent error (e.g., lying, forgetting, etc.)
2.Interviewer bias
3.Recording errors
4.Poorly designed questionnaires
5.Measurement error
1.Respondent error
 respondent gives an incorrect answer, e.g. due to prestige or competence
implications, or due to sensitivity or social undesirability of question
 respondent misunderstands the requirements
 lack of motivation to give an accurate answer
 “lazy” respondent gives an “average” answer
 question requires memory/recall
 proxy respondents are used, i.e. taking answers from someone other than the
respondent
2.Interviewer bias
 Different interviewers administer a survey in different ways
 Differences occur in reactions of respondents to different
interviewers, e.g. to interviewers of their own sex or own
ethnic group
 Inadequate training of interviewers
 Inadequate attention to the selection of interviewers
 There is too high a workload for the interviewer
5.Measurement Error
 The question is unclear, ambiguous or difficult to answer
 The list of possible answers suggested in the recording instrument is
incomplete
 Requested information assumes a framework unfamiliar to the
respondent
 The definitions used by the survey are different from those used by the
respondent (e.g. how many part-time employees do you have? See next
slide for an example)
10. M
INIMIZEOF SAMPLINGERRORS …..
 Prepare updated sampling frame
 Use appropriate probability sampling
Technique.
 Minimizes the stages sampling.
 Appropriate sample size
Small – Increase sampling error
Large – decrease sampling error
 Reduction Attrition rates
Critique: SAMPLE
Are the subjects and sampling methods described?
Is the sample of sufficient size for the study, given the
number of variables and design?
Is there adequate assurance that the rights of human
subjects were protected?
Unit 2a Critique 11
Thank you

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Nursing Research Sampling errors.pptx

  • 1. 1 Sampling Error Prof.Dr.Chinna Chadayan.N RN.RM., B.Sc (N)., M.Sc (N)., Ph.D (N)., Professor Enam Nursing College Unit 14b Sampling Error
  • 2. Sampling is a technique • Sampling is a technique of selecting individual members or a subset of the population to make statistical inferences from them and estimate characteristics of the whole population. • Different sampling methods are widely used by researchers in market research so that they do not need to research the entire population to collect actionable insights. • It is also a time-convenient and a cost-effective method and hence forms the basis of any research design. • Sampling techniques can be used in a research survey software for optimum derivation.
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  • 5. SAMPLING ERRORS SAMPLING ERROR: is incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. For example, if one measures the height of a thousand individuals from a country of one million, the average height of the thousand is typically not the same as the average height of all one million people in the country. Sampling errors Non-sampling errors
  • 6. NON-SAMPLE ERRORS 1.Non Response Error 2.Response Error Not Control by Sample Size Non Response Error A non-response error occurs when units selected as part of the sampling procedure do not respond in whole or in part Response Errors A response or data error is any systematic bias that occurs during data collection, analysis or interpretation 1. Respondent error (e.g., lying, forgetting, etc.) 2.Interviewer bias 3.Recording errors 4.Poorly designed questionnaires 5.Measurement error
  • 7. 1.Respondent error  respondent gives an incorrect answer, e.g. due to prestige or competence implications, or due to sensitivity or social undesirability of question  respondent misunderstands the requirements  lack of motivation to give an accurate answer  “lazy” respondent gives an “average” answer  question requires memory/recall  proxy respondents are used, i.e. taking answers from someone other than the respondent
  • 8. 2.Interviewer bias  Different interviewers administer a survey in different ways  Differences occur in reactions of respondents to different interviewers, e.g. to interviewers of their own sex or own ethnic group  Inadequate training of interviewers  Inadequate attention to the selection of interviewers  There is too high a workload for the interviewer
  • 9. 5.Measurement Error  The question is unclear, ambiguous or difficult to answer  The list of possible answers suggested in the recording instrument is incomplete  Requested information assumes a framework unfamiliar to the respondent  The definitions used by the survey are different from those used by the respondent (e.g. how many part-time employees do you have? See next slide for an example)
  • 10. 10. M INIMIZEOF SAMPLINGERRORS …..  Prepare updated sampling frame  Use appropriate probability sampling Technique.  Minimizes the stages sampling.  Appropriate sample size Small – Increase sampling error Large – decrease sampling error  Reduction Attrition rates
  • 11. Critique: SAMPLE Are the subjects and sampling methods described? Is the sample of sufficient size for the study, given the number of variables and design? Is there adequate assurance that the rights of human subjects were protected? Unit 2a Critique 11
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