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Published byJan Stoodley Modified about 1 year ago

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Suppose the Office of Institutional Research and Planning (IRP) calls 50 recent alumni and ask about their current income. The average reported monthly income of these 50 alumni was $3,100.

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Question: The 50 surveyed students are a_____. A.Parameter B.Population C.Sample D.Statistic

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Question: “average income of $3,100” is a _______? A.Parameter B.Population C.Sample D.Statistic

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What would need to change with regards to the sample size, n, to make the “reported average income” a parameter? A.n=1 B.n=1,000 C.n=Number of recent alumni=N D.You can’t find the parameter value because the population is infinite in size.

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A parameter describes a characteristic of the population. We typically can’t sample the entire population (do a census), so we collect a sample. We design our sample so it is likely representative of the population. A statistic is calculated from a sample. We use the statistic to estimate the parameter.

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Very first steps Define your population Determine what parameter of the population is of interest to you. (What’s the study’s question?)

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A prospective cohort study of over 1,300 children found that children who are breast- fed for a year, on average, test 4 IQ points higher than non breast-fed children. (JAMA 7/29/2013)

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Question: Not knowing more details about this study, this study could most likely be classified as an____________. A.observational study. B.experiment.

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Question: To use simple random sampling to sample 10 people from this class of 80, I should: A.Use every 8 th name from my roll sheet. B.Have people write their names on a piece of paper, put them in a hat, and pull 10 pieces of paper from the hat. C.Ask for 10 volunteers. D.Assign each person a number (1-80) and then use a computer or random number table to get 10 names.

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Why use randomness when sampling? Avoid bias!

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