1 / 52

Sampling

Sampling. Chapter 5. Introduction. Sampling The process of drawing a number of individual cases from a larger population A way to learn about a larger population by obtaining information from a subset of a larger population Example

sshirley
Télécharger la présentation

Sampling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Sampling Chapter 5

  2. Introduction • Sampling • The process of drawing a number of individual cases from a larger population • A way to learn about a larger population by obtaining information from a subset of a larger population • Example • Presidential polls are based upon samples of the population that might vote in an election

  3. Introduction • Why Sample? • To learn something about a large group without having to study every member of that group • Time and cost • Studying every single instance of a thing is impractical or too expensive • Example • Census

  4. Introduction • Why Sample? • Improve data quality • Obtain in-depth information about each subject rather than superficial data on all

  5. Introduction • Why Sample? • We want to minimize the number of things we examine or maximize the quality of our examination of those things we do examine.

  6. Introduction • Why Sample? • When is sampling unnecessary? • The number of things we want to sample is small • Data is easily accessible • Data quality is unaffected by the number of things we look at • Example • You are interested in the relationship between team batting average and winning percentage of major league baseball teams • There are only 30 major league teams • Data on team batting averages and winning percentages are readily available

  7. Introduction • Why Sample? • Elements • A kind of thing the researcher wants to look at

  8. Quiz – Question 1 Suppose you are interested in describing the nationality of Nobel prize-winning scientists. What would an element in your study be? What would the population be?

  9. Introduction • Why Sample? • Population • The group of elements from which a researcher samples and to which she or he might like to generalize

  10. Quiz – Question 2 • In the case of presidential elections in the United States the population is ________ and the elements of this population are _________.

  11. Introduction • Why Sample? • Sample • A number of individual cases drawn from a larger population

  12. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Target population • A population of theoretical interest

  13. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Sampling frame or study population • The group of elements from which a sample is actually selected

  14. Quiz – Question 3 The local television station conducted a study of TV viewers in the local viewing region. A list of all residential customers who subscribed to cable TV was obtained from the cable company. The list had 200,000 households as subscribers. The TV station samples every 40th household on the subscriber list. An interviewer visited each household and conducted the survey on viewing habits of household members. What is the sampling frame of the study?

  15. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Nonprobability Samples • A sample that has been drawn in a way that doesn’t give every member of the population a known chance of being selected

  16. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Probability • A sample drawn in a way to give every member of the population a known (nonzero) chance of inclusion • Probability samples are usually more representative than nonprobability samples of the populations from which they are drawn

  17. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Biased Samples • A sample that is not representative from the population which it is drawn • Probability samples are LESS likely to be biased samples

  18. Introduction • Sampling Frames, Probability versus Nonprobability Samples • Generalizability • The ability to apply the results of a study to groups or situations beyond those actually studied • A probability sample tends to be more generalizable because it increases the chances that samples are representative of the populations from which they are drawn.

  19. Introduction STOP AND THINK • Can you think why researchers haven’t used cell phone numbers in polling until recently? • What problem may result from only using landline numbers?

  20. Focal Research • “Calling Cell Phones in ’08 Pre-Election Polls” • Examines the hypothesis than Barack Obama fared better in probability samples including landline- and cell phone-users than in samples including landline users alone.

  21. Focal Research • Thinking about ethics • Because of the sampling technique employed, the Pew pollsters never knew the identity of their respondents, so respondent anonymity was never in danger. • Moreover, participation in the survey was voluntary.

  22. Sources of Error Associated with Sampling • Types of Survey Error – due to sampling • Coverage Error • Nonresponse Error • Sampling Error

  23. Sources of Error Associated with Sampling • Coverage Errors • Errors that results from differences between the sampling frame and the target population

  24. Sources of Error Associated with Sampling • Coverage Errors • People are typically left out, if samples are drawn from phone books, car registrations, etc… • Unlisted Phone Numbers – one of the greatest potentials for coverage error • Pollsters use random digit dial to avoid unlisted numbers • Random-digit dialing • A method for selecting participants in a telephone survey that involves randomly generating telephone numbers • What are potential future problems, with using telephone listings to draw a sample?

  25. Sources of Error Associated with Sampling • Coverage Errors • Parameter- A summary of a variable characteristic in a population

  26. Sources of Error Associated with Sampling • Coverage Errors • Statistic-A summary of a variable in a sample

  27. Sources of Error Associated with Sampling • Nonresponse Error • Errors that result from differences between nonreponders and responders to a survey

  28. Stop and Think • What kinds of people might not be home to pick up the phone in the early evening when most survey organizations make their calls? • What kinds of people might refuse to respond to telephone polls, even if they were contacted?

  29. Sources of Error Associated with Sampling • Sampling Error • Any difference between the characteristics of a sample and the characteristics of the population from which the sample is drawn

  30. Sources of Error Associated with Sampling • Sampling Error • Sampling Variability • The variability in sample statistics that occurs when different samples are drawn from the same population

  31. Sources of Error Associated with Sampling • Margin of error • Suggestion of how far away the actual population parameter is likely to be from the statistic

  32. Types of Probability Sampling • Simple Random Sampling • Systematic Sampling • Stratified Sampling • Cluster Sampling • Multistage Sampling

  33. Types of Probability Sampling • Simple Random Sampling • A probability sample in which every member of a study population has been given an equal chance of selection • One way to draw a simple random sample, is to put all possibilities on paper, cut them up, and then draw a sample from a hat • Research Randomizer (http://randomizer.org)

  34. Types of Probability Sampling • Simple Random Sampling • Sampling distribution • The distribution of a sample statistic • A visual display of the samples

  35. Types of Probability Sampling

  36. Types of Probability Sampling • Systematic Sampling • A probability sampling procedure that involves selecting every kth element from a list of population elements, after the first element has been randomly selected • Example • Divide the total number of elements by the number you want in your sample 24/6 = 4 • Randomly select a number between 1 and 4 and then select every 4th element from that number

  37. Types of Probability Sampling • Systematic Sampling • Selection interval • The distance between the elements selected in a sample Selection Interval (k) = population size sample size

  38. Types of Probability Sampling • Stratified Sampling • A probability sampling procedure that involves dividing the population in groups or strata defined by the presence of certain characteristics and then random sampling from each stratum • Example • If you had a population that was 10% women and you want a sample that is also 10% women

  39. Types of Probability Sampling • Stratified Sampling • Steps to draw a stratified random sample • Group the study population into strata or into groups that share a given characteristic • Enumerate each group separately • Randomly sample within each strata

  40. Types of Probability Sampling • Cluster Sampling • A probability sampling procedure that involves randomly selecting clusters of elements from a population and subsequently selecting every element in each selected cluster for inclusion in the sample • Cluster sampling is an option if data collection involves visits to sites that are far apart

  41. Types of Probability Sampling • Cluster Sampling • Example • You are conducting a study of Kentucky high school students • You could obtain a list of all high school students in the state and complete random sampling • A cluster sample would be more practical • Obtain a list of all high schools in Kentucky • Random sample the high schools from the list • Obtain a list of students for each high school selected and then contact each of those students

  42. Types of Probability Sampling • Multistage Sampling • A probability sampling procedure that involves several stages, such as randomly selecting clusters from a population, then randomly selecting elements from each of the clusters

  43. Types of Probability Sampling • Multistage Sampling • Example • Random Digit Dial • Stage 1: Areas Codes randomly sampled • Stage 2: Three digit local exchanges randomly sampled • Stage 3: Last four digits randomly sampled • Stage 4: Asking the person who answer the phone for the appropriate person you want to interview

  44. Quiz – Question 4 You want to draw a sample of the employees at a large university ensuring that in your sample you have people represented from all personnel categories including administrators, faculty, secretarial staff, cleaning staff, mail room staff, technicians, and students. What type of probability sample would be best?

  45. Types of Nonprobabilty Sampling • Purposive Sampling • Quota Sampling • Snowball Sampling • Convenience Sampling

  46. Types of Nonprobability Sampling • Purposive Sampling • A nonprobability sampling procedure that involves selecting elements based on a researcher's judgment about which elements will facilitate his or her investigation

  47. Types of Nonprobability Sampling • Quota Sampling • A nonprobability sampling procedure that involves describing the target population in terms of what are thought to be relevant criteria and then selecting sample elements to represent the “relevant” subgroups in proportion to their presence in the target population

  48. Types of Nonprobability Sampling • Snowball Sampling • A nonprobability sampling procedure that involves using members of the group of interest to identify other members of the group

  49. Types of Nonprobability Sampling • Convenience Sampling • A nonprobability sampling procedure that involves selecting elements that are readily accessible to the researcher • Sometimes called an available-subjects sample

More Related