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Lecture

# SOC202.JAN 31 2012.SP.docx

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School
University of Toronto St. George
Department
Sociology
Course
SOC202H1
Professor
Scott Schieman
Semester
Winter

Description
SOC202H1S Qualitative Analysis in Social Sciences January 30 2012 – Week 4 TG. SP. Today’s lecture will be a bit more abstract and a lot of materials will be from the slides. - There is 1% of population that is very extreme. Most people are centered because that is what average is about. For example, some people are really rich but not all. Essentially what we will do is we will take that idea – take sample statistics and see if it is representing a population by various tests. Sleep: in a typical 24-hour period, approx. how many hours of sleep do you usually get? - There are very few people that have depression. If depressed people were common, our result will be very different. - In the test he will get you to think about distribution and examples. So he will have an example of huge Canadian survey. So what would happen to the mean if we added 1 more case to 1 hour? Then the data wont change so much, because sample size is so huge - Larger the sample, it absorbs amount of potential of outlier - The more deviant from the norm you have, it is very easy and political to label it. - One case of deviance is not a big deal. But if there is a lot, it becomes the problem o You are trying to get average income, but person that makes 50,000 dollars a day can pull it up. - Standard deviation – seeing how far each score is from the mean. Sampling distribution - The relationship between hours of sleep and conflict - We will establish the relationship of X and Y here. - People are not truly representative. People who are here and not here hold different chance to be selected in the sample. - How likely is it that we can grab 2 samples and obtain different result? - Say we scoop another sample on top of a sample, we might be get different result. But if it was done correctly and appropriately, the both results should be fairly close to each other. If they are significantly different, there is something wrong - Figure 7-1 o One sample is off by 4.0, 5.5, 4.3, etc. it is the estimate of the idea o This is the idea behind the notion of sampling - We basically want to quantify an error. Use as template as a sample of population. - The bigger samples are better because there
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