1. Minds On! Suppose you have selected a sample of 60 students at CPHS You are armed with 60 surveys and you set out to have them completed What could possibly go wrong?  i.e., what could happen that would result in the data not representing the population?

2. AGENDA Summary of surveys (2 slides) 2.5 – Types of Bias 2.6 – Secondary Sources (not tested) 2.7 – Tools (not tested) Test Fri:  ~20 MC (Ch1 & 2)  ~6 problem

3. Avoiding Bias Chapter 2.5 – In Search of Good Data Learning goal: Identify different ways that bias can occur in data Read p. 111 Ex 1 and 2 Complete2.5 p. 113 # 1-7, 11 2.6 p. 123 # 5, 7, 9

4. Bias When a sample is not representative of the population  The data “is biased” or “contains bias” Due to an unintended or intended influence in the data gathering Biased data is useless as it does not represent the population

5. Types of Bias 1. Sampling Bias  the chosen sample does not accurately represent the population  ex: students in the caf at lunch are surveyed 2. Non-Response Bias  data is not collected from potential respondents  ex: people do not return mail-in surveys  ex: people do not respond to email surveys

6. 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, 15 grade 9s, 15 grade 10s, 15 grade 11s and 15 grade 12s are surveyed 4. Response Bias  aspects of the survey itself bias the results  ex: poorly written questions  ex: openly biased interviewer

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

8. Why Secondary Sources? Although it is ideal 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?

9. MSIP / Home Learning Read p. 111 Ex 1 and 2 Complete 2.5 p. 113 # 1-7, 11 Complete 2.6 p. 123 # 5, 7, 9

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

11. 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)

12. Working with data Spreadsheets (Excel, OpenOffice, LibreOffice, Google Sheets)  text and numbers may be used  organized in rows and columns  very powerful for mathematical operations  graphing capabilities available

13. Fathom Dynamic statistics analysis tool Organizes data in collections of rows and columns Easy to graph data (drag-and-drop) Offers analysis tools (all MDM4U calculations) Speed is the largest advantage Can import data from other sources easily

14. 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

15. 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

16. 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