PSY 313 Week 5 Notes
PSY 313 Week 5 Notes PSY 313
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This 3 page Class Notes was uploaded by Bria Harris on Friday October 2, 2015. The Class Notes belongs to PSY 313 at Syracuse University taught by Amy Criss in Summer 2015. Since its upload, it has received 68 views. For similar materials see Intro. to Research Methodology in Psychlogy at Syracuse University.
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Date Created: 10/02/15
PSY 313 Introduction to Research Methods Week 5 Lecture Notes September 28th amp 3Oth Sampling Picking people from a population of interest and sampling these people How we select people from the population Assignment How we place the sample into conditions of the experiment How do we know our sample is a Good Example 9representative of the Population We can never be sure But developing a sampling plan can help establish representativeness Sampling Goes Wrong In 1936 the Literary Digest polled 24 million people to figure out who would be elected president Roosevelt or Landon Predicted Landon from poll Roosevelt actually won 62 to 38 What went wrong Got respondents from phone directories club memberships amp auto registrations only people that ad access to telephones not representative of the entire population Representative How similar the sample is to the population of interest Very similar highly representative Measured by bias and stability Important Traits of a Sample Bias sample differs from population on important dimensions Stability how much quotnoisequot in our data Unstable Means Our Sample is NOT reliable Stability spread or variance of the sample High stability low spread a good thing Margin of error in a poll is based on stability 0 Eg We can say with 95 confidence that the maximum margin of error is 4 points How to avoid unstable sample sufficiently large sample size N Sample Size Increase sample size more certainty our sample represents the population How large is large Bias Means We Have Inaccurately Sample Our Data Bias systematic difference between samples amp population Unbiased good representative sample How to avoid bias develop a sampling plan Sampling Plan Nonprobability not drawing form the entire population Probability sampling each member of the population has a known amp non zero chance of being selected Eg Census NonProbability Sampling Convenience take what you can get Quota selectively take what is available according to a plan Eg Take the 1St eligible 10 men and 10 women sample every 10th person from each gender Probability Sampling Each member of the population has a known amp nonzero chance of being selected Known must be able to identify and have access to each member of the population Nonzero everyone has a chance of being sampled Types of Probability Sampling Simple Random Sample everyone in the population has an equal chance of being selected Without replacement each person can only be sampled once With replacement people can be selected multiple times Stratified break population into sub samples amp choose randomly from the sub sample Eg Age 2570 income range Stratified random sample an equal number form each strata eg 20 of your sample from each of the 5 income brackets Proportionate stratified sample Sample each stratum in proportion to its size in the population 0 Eg 3 13 27 20 37 from the 5 brackets Stratification must be a dimension relevant for your research question Eg Do Big 10 schools adequately train their Biology students Population Students majoring in Biology at Big 10 schools Probability Sampling Sampling Plans 1 Simple Random Sample randomly select Biology students at Big 10 schools without replacement use random number generator to select NN100 participants from that list 2 Stratified random sample First select strata that are relevant Freshman Sophomore Junior Senior take 25 from each strata sample may not re ect the distribution of the population 3 Proportionate Stratified Freshman 5 Sophomore 20 Junior 50 Senior 25 the proportion in the population percentage or the number of Big 10 Biology students that are Freshman Sophomore Junior Senior sample re ects the distribution of the population Describing the Results of a Study Estimating a Population Using a Sample Population group you are studying We are estimating the value of the population based on the values we measured with our sample which is why having a robust sampling plan is important Descriptive Statistics techniques that help describe a set of data Organize summarize amp simplify data Terminology N of observations X individual score 2 sum of sigma square root M mean S SD Standard deviation V variance
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