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Avoiding Bias

Avoiding Bias. Chapter 2.5 – In Search of Good Data Learning goal: Identify different ways that bias can occur in data. Bias. occurs when a sample is not representative of the population due to an unintended (or intended) influence in the data gathering

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Avoiding Bias

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  1. Avoiding Bias Chapter 2.5 – In Search of Good Data Learning goal: Identify different ways that bias can occur in data

  2. 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 our MDM 4U class are surveyed to determine attitudes of students in the school

  3. Types of Bias • 1. Sampling Bias • chosen sample does not accurately represent population • ex: students in the halls during period 1 are surveyed on academic destinations • 2. Non-Response Bias • data is not collected from potential respondents • ex: people do not return mail-in surveys

  4. Types of Bias • 3. Household Bias • types of respondent are over- or under-represented because groups of different sizes are not polled proportionately • ex: At CPHS, 30 grade 9s, 20 grade 10s, 10 grade 11s and 5 grade 12s are given an MSIP survey (no random selection) • 4. Response Bias • aspects of the survey itself bias the results • ex: poorly written questions, openly biased interviewer

  5. Secondary Sources Chapter 2.6 – In Search of Good Data Identify key considerations of secondary data

  6. 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 • It is important to try and find out: • what methods were used to collect the data? • If the source is credible?

  7. Exercises • Read p. 111 Ex 1 and 2 • Complete 2.5 p. 113 # 1-7, 11 • Complete 2.6 p. 123 # 5, 7, 9

  8. Preparing Data Chapter 2.7 – In Search of Good Data Manage and analyze data using various tools

  9. 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)

  10. 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

  11. 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

  12. Using software tools • see examples in the text starting on p.128 • see Appendix D (p.415) for Fathom procedures • see Appendix E (p.425) for spreadsheet procedures

  13. Exercises • work for this section will be addressed through projects we do during the course • you will be assessed on your ability to use software to draw conclusions, but not on procedures for using the software

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

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