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?

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

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

Complete 2.5 p. 113 # 1-7, 11

2.6 p. 123 # 5, 7, 9

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

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

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

Secondary Sources

Chapter 2.6 – In Search of Good DataIdentify key considerations of secondary data

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?

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

Preparing Data

Chapter 2.7 – In Search of Good DataManage and analyze data using various tools

So you have some data… Data

A 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)

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

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

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

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

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