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VCU STAT 210 - Producing Data

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STAT210 1st EditionLecture 3Outline of Last LectureI. Descriptive statistics, qualitative/quantitativeII. Constants/variablesOutline of Current LectureIII. Producing DataIV. BiasV. Sampling ProceduresCurrent LectureVI. Selection Bias – systematically excluding some membersa. Undercoverage = some part of the population is not representedb. Example: representing 20/50 statesVII. Nonresponse Bias – person who’s supposed to be counted does not respondVIII. Response Bias – inaccurate information or question itself influenced answerIX. Haphazard Samples – selection of a sample that does not involve randomizationa. Example: asking students as they walk by/ handing out surveys at the mallX. Volunteer Response Bias – people who choose to be polled (they often have strong, negative opinions that are an inaccurate representation of the population) XI. Random Sample – subjects are chosen randomly; this better represents the population; mostly bias freeXII. Probability Sampling Design – when each subject of the population has a positive and equal probability of being selectedXIII. With SIMPLE RANDOM SAMPLING you choose N of the subjects in such a way that everyset of N subjects has an equal chance of being selectedXIV. To use a table of random digits:a. Randomly choose a starting pointb. Read across rows or down columns, reading off 1-digit, 2-digit, 3-digit etc. numbers (depending on how many digits are in N)These 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.XV. Duplicate numbers are omitteda. Ex. If N = 636, we read 3-digit numbers; if we get 761 it is omitted because it doesn’t correspond with N; if we get 122 twice, we omit it the second timeXVI. Stratified Random Sampling XVII. Population is divided into 2 or more groups of similar subjects called STRATAa. For example, strata 1 = males; strata 2 = femalesXVIII. Simple random samples are selected from each strata then combinedXIX. ****Number chosen from each strata should match % of the total population in each stratum****a. Example: Population is 20,000 undergraduate studentsb. Sample = 200 undergraduate studentsc. If 6000 are freshman, that means they make up 30% of the population so 60 freshman would be chosend. If 5000 are sophomores, it means 50 sophomores would be chosene. If 4000 are juniors, it means 40 juniors would be chosenf. If 5000 are seniors, it means 50 seniors would be chosenXX. Multi Stage Random Sampling – easier to obtain a. Example: Population = All American college studentsb. Parameter = some characteristic of the study habits of all American college studentsc. Sample = 225 studentsd. It’s hard to get samples from 225 different colleges, so we select some groups to sample (not all like simple random sampling); each chosen group is further divided and then simple random sampling is usede. There must be at least 2 randomization


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VCU STAT 210 - Producing Data

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