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U-M STATS 250 - Margin of Error, Confidence, and Bias in Surveying
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STATS 250 1st Edition Lecture 3 Outline of Last Lecture I. Numerical Summaries of Quantitative VariablesII. How to Handle OutliersIII. Features of Bell-Shaped DistributionsIV. Population vs. SampleOutline of Current Lecture I. Collecting and Using Sample Data WiselyII. Margin of Error, Confidence Intervals, and Sample SizeIII. How to Ask Survey QuestionsCurrent LectureI. Collecting and Using Sample Data Wiselya. Descriptive Statistics: describing data using numerical summaries (mean, IQR, etc.) and graphical summaries (histograms, bar charts, etc.)b. Inferential Statistics: Using sample information to make conclusions about a larger group of items/individuals than just those in the samplec. Population (N): the entire group of items/individuals that we want information about, about which inferences are to be maded. Sample (n): the smaller group, the part of the population we actually examine in order to gather informatione. Variable: the characteristic of the items or individuals that we want to learn aboutf. Sample data can be used to make inferences about population data if the data can be considered to be representative of the whole populationi. One way to guarantee this is to use a completely random sampleg. Sample vs. Censusi. Census: measures every item in the population1. Takes too long, costs too much, measuring destroys the itemii. Sample survey: subgroup of a large population is questioned1. More efficienth. Bias: occurs when survey methods consistently produce values that are either too high or too lowThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.i. Selection bias: occurs if the method for selecting the participants produces a sample that does not represent the population of interestii. Nonparticipation/Nonresponse bias: occurs when a representative sample is chosen for a survey, but a subset cannot be contacted or does not respondiii. Response bias: occurs when participant respond differently from how they truly feelII. Margin of Error, Confidence Intervals, and Sample Sizea. Margin of Error: measure of accuracy in sample surveys showing how close a proportion comes to the truth for the entire populationi. Proportion ( )ppii. Conservative (approximate 95%) Margin of Error: 1/(√n)b. Confidence Intervalsi. Approximate 95% Confidence Interval for p: +/- 1/(√n)ppIII. How to Ask Survey Questionsa. There are several sources of bias in questioning:i. Deliberate bias in questionsii. Unintentional bias in questionsiii. Desire of respondents to pleaseiv. Asking the uninformedv. Unnecessary Complexityvi. Ordered questioningvii. Confidentiality/anonymity


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U-M STATS 250 - Margin of Error, Confidence, and Bias in Surveying

Type: Lecture Note
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