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Avoiding Bias

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bias occurs when a sample is not representative of the population due to an ... over or under represented because groups of different size are polled equally ... – PowerPoint PPT presentation

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Title: Avoiding Bias


1
Avoiding Bias
  • Chapter 2.5 In Search of Good Data
  • Mathematics of Data Management (Nelson)
  • MDM 4U
  • Author G. Greer and K. Myers

2
Bias
  • bias occurs when a sample is not representative
    of the population due to an unintended (or
    intended) influence in the data gathering
  • data collected with bias is useless as it
    distorts the truth
  • ex students in MDM 4U are surveyed to determine
    attitudes of students in the school

3
Types of Bias
  • Sampling Bias
  • chosen sample does not accurately represent
    population
  • ex students in halls during period one are
    surveyed on academic destinations
  • Non-Response Bias
  • data is not collected from potential respondents
  • ex people do not return mail-in surveys

4
Types of Bias
  • Household Bias
  • types of respondent are over or under represented
    because groups of different size are polled
    equally
  • ex 5 students are sampled in each homeroom
    despite the fact that the homerooms are of
    different sizes
  • Response Bias
  • sampling method factors bias the results
  • ex poorly written questions, openly biased
    interviewer,

5
Exercises
  • read through examples 1 and 2 starting on page
    111
  • try page 113 1-7, 11

6
Secondary Sources
  • Chapter 2.6 In Search of Good Data
  • Mathematics of Data Management (Nelson)
  • MDM 4U
  • Author G. Greer and K. Myers

7
Why Secondary Sources?
  • although it is informative to collect your own
    data (primary source) it is often impossible to
    do so (cost, time, expertise)
  • the reliability of the source becomes a key issue
  • what methods were used to collect the data?
  • is the source credible?

8
Exercises
  • in the computer room complete the sheets titled
    Secondary Sources (also located on
    http//napaneedss.limestone.on.ca/greer/mdm4u/chap
    ter2/secondary.pdf)
  • try page 123 1, 3, 5, 7

9
Preparing Data
  • Chapter 2.7 In Search of Good Data
  • Mathematics of Data Management (Nelson)
  • MDM 4U
  • Author G. Greer and K. Myers

10
So you have some data
  • DataA set of facts, concepts or statistics that
    can be analyzed to produce information.
  • InformationData that has been organized within a
    context and translated into a form that has
    structure and meaning.
  • KnowledgeDerived from information but richer and
    more meaningful than information. It includes
    familiarity, awareness and understanding gained
    through experience or study, and results from
    making comparisons, identifying consequences,
    making connections, 'know how', 'applied
    information', 'information with judgment' or 'the
    capacity for effective action'.
  • (National electronic Library for Health, 2001)

11
Working with data
  • spreadsheets
  • text and numbers may be used
  • organized in rows and columns
  • very powerful for mathematical operations
  • can be treated like simple databases
  • if you have numerical data, consider this as an
    option
  • graphing capabilities available

12
Working with data
  • database
  • software for storing, organizing and retrieving
    data
  • powerful for storage and retrieval
  • organized in terms of records, containing data
  • can be VERY large
  • can search for data in very complex ways using
    search languages
  • complex math can sometimes be programmed in
  • may offer graphing utilities

13
Fathom
  • designed as a dynamic statistics analysis tool
  • organizes data in collections of rows and columns
  • easy to graph data
  • offers some analysis tools
  • speed is the largest advantage
  • can import data from sources easily

14
Using software tools
  • see examples in the text starting on page128
  • see Appendix D page 415 for Fathom procedures
  • see Appendix E page 425 for spreadsheet
    procedures

15
Exercises
  • work for this section will be addressed through
    projects we do during the course
  • it is likely that we will not work with database
    software
  • students will be assessed on their abilities to
    use software to draw conclusions, but not on
    procedures for using the software

16
References
  • National electronic Library for Health (2001).
    Knowledge Management Glossary. Retrieved
    September 27, 2004 from http//www.nelh.nhs.uk/kno
    wledge_management/glossary/glossary.asp
  • Wikipedia (2004). Online Encyclopedia. Retrieved
    September 1, 2004 from http//en.wikipedia.org/wik
    i/Main_Page
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