1. Avoiding Bias Chapter 2.5 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U

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 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 polled equally  ex: At CPHS 150 males and 50 females are surveyed to determine whether students would prefer to write exams in the gym 4. Response Bias  factors of sampling method bias the results  ex: poorly written questions, openly biased interviewer

5. Secondary Sources Chapter 2.6 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U

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 Do 2.5 p. 113 # 1-7, 11 Do 2.6 p. 123 # 5, 7, 9

8. Preparing Data Chapter 2.7 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U

9. So you have some data… Data A set of facts, concepts or statistics that can be analyzed to produce information. Information Data that has been organized within a context and translated into a form that has structure and meaning. Knowledge Derived 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. 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

12. 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

13. 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

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

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