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Published byTrevor Golden Modified over 9 years ago
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Population size * Population size doesn’t matter as long as… * Population > 10*n (10*sample size) * As long as your sample is random, and your population is big enough, its size doesn’t matter to the variability of the statistic (the results).
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Example There are two local high schools, Central High and North High. Central has 1,000 students and North has 3,500 students A researcher wants to determine the average income for the families that send their students to the different high schools. He has 2 different sampling methods: Sample 5% from each school Sample 100 students from each school
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Try these: p #45 & 46
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Margin of Error and Confidence Statements
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Example: A newspaper article states that they took a poll of Americans and found that 65% of them think the President is doing a good job. They say that they are 95% confident about their results, but they have a margin of error of plus or minus3%. What can you infer about the % of ALL Americans that think he’s doing a good job? Do you trust their results?
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The same newspaper prints an article the next day saying that they were wrong, that they have a margin of error of 30%, not 3%. They are still 95% confident in their results though! What can you infer about the % of ALL Americans that think the President is doing a good job?
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The same newspaper prints another article
The same newspaper prints another article. They took a new sample because their realized their margin of error was too high before. So now they have a margin of error of 5%. But they are only 60% confident in their results now. What can you infer about the % of ALL Americans that think the President is doing a good job?
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Margin of Error: Want it to be a low % Its always a plus or minus % Usually paired with a level of confidence Use both the level of confidence and the margin of error to decide whether you trust the results Larger samples mean lower margin of error.
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Confidence Statement:
Use both level of confidence, and margin of error, conclude about population Example: 90% confident that 45% vote for Democrat, having a margin of error of 3%. I am 90% confident that the true percent of the population that will vote for the Democrat is between 42% and 48%.
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Try p. 232 #42 a &b, 43 42 (a) I am 95% confident that the true percent of the population that think Women had to give up too much to get better jobs is between 45% and 51%. 42 (b) Because 48% is just from the one sample (the one poll). Samples are not always representative of the population. This is why we need the margin of error
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43) Men = 472 margin of error = 5%
Women = 1025 margin of error = 3% The margin of error for the men was larger because they had a smaller sample size. So their sample is more variable (wider histogram, less accurate).
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