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Questions for thought

Questions for thought. If you think your school is the best school in the world, raise your hand. What’s the problem with this survey? To see what percentage of Canadians like curry, a survey is conducted in Toronto. What’s wrong with this survey? How could you make these surveys better?

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Questions for thought

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  1. Questions for thought • If you think your school is the best school in the world, raise your hand. • What’s the problem with this survey? • To see what percentage of Canadians like curry, a survey is conducted in Toronto. • What’s wrong with this survey? • How could you make these surveys better? • In groups of your choosing, brainstorm four ways to survey student’s favourite tv shows within the school.

  2. SAMPLING TECHNIQUES Unit 3 – One Variable Statistics

  3. Statistics • The study of the collection, organization, analysis, interpretation, and presentation of data.

  4. Key terms • Population – all individuals or items that belong to a group being studied. • Sample – The group of people chosen for a survey. • Census – A survey where the sample is the whole population. • Bias Results – Misleading or not representative of the whole population.

  5. Sampling Techniques • Simple Random • Stratified Random • Systematic • Cluster • Convenience • Voluntary response

  6. 1. Simple Random Sample Each member of the population has an equal chance of being selected. Example: Drawing 5 names from a hat of a total of 30 names. Pros Cons • Easy to do • Fair to all involved • Could get poor representation (i.e. all people chosen have same opinion)

  7. 2.Stratified Random Sample Population is divided into subgroups (i.e. gender, age, nationality) and then a random sample is taken from each subgroup.Example: Dividing a school by grades and randomly selecting from each grade. Pros Cons • Fair representation of the population • Increased setup time • Could still be biased • Survey may not be relevant to certain subgroups

  8. 3.Systematic Sample Choosing every nth member of the population Example: A light bulb manufacture r tests every 100th light bulb Pros Cons • Easy to do • Spreads sample evenly over population • Could be hidden pattern in the system

  9. http://www.youtube.com/watch?v=rASK8PpqakM • Clip on Simple, Systematic, and Stratified Sampling

  10. 4.Cluster Sample Population is divided into clusters and a random number of clusters (or cluster) is chosen as a sample Example – Clusters could be the set of students sitting at a table. Not necessarily a specific grouping. Pros Cons • Easy to do • Often over-represents some opinions as clusters have a higher chance of sharing opinions

  11. 4.Convenience Sample Sample composed of those that it is easiest to get data from. Example: Sampling friends, conducting internet or telephone survey. Pros Cons • Easiest to do • Good way to start research and get ideas • Not randomized • High chance that sample doesn’t represent population

  12. 4.Voluntary-Response Sample Sample contains population members who volunteer to do the survey Example: Those with pet allergies may volunteer to do a study on their allergies Pros Cons • Often useful for psychological and/or pharmaceutical trials • Participants sometimes vote more than once and skew change) the results

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