Sampling

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Sampling

• Chapter 5

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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

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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

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Introduction

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

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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.

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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

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Introduction

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

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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?

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Introduction

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

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Quiz Question 2

• In the case of presidential elections in the
  United States the population is ________ and the
  elements of this population are _________.

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Introduction

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

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Introduction

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

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Introduction

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

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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?

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Introduction

• Sampling Frames, Probability versus
  Nonprobability Samples
• Nonprobability Samples
• A sample that has been drawn in a way that
  doesnt give every member of the population a
  known chance of being selected

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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

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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

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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.

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Introduction

• STOP AND THINK
• Can you think why researchers havent used cell
  phone numbers in polling until recently?
• What problem may result from only using landline
  numbers?

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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.

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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.

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Sources of Error Associated with Sampling

• Types of Survey Error due to sampling
• Coverage Error
• Nonresponse Error
• Sampling Error

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Sources of Error Associated with Sampling

• Coverage Errors
• Errors that results from differences between the
  sampling frame and the target population

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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?

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Sources of Error Associated with Sampling

• Coverage Errors
• Parameter- A summary of a variable characteristic
  in a population

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Sources of Error Associated with Sampling

• Coverage Errors
• Statistic-A summary of a variable in a sample

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Sources of Error Associated with Sampling

• Nonresponse Error
• Errors that result from differences between
  nonreponders and responders to a survey

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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?

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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

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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

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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

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Types of Probability Sampling

• Simple Random Sampling
• Systematic Sampling
• Stratified Sampling
• Cluster Sampling
• Multistage Sampling

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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)

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Types of Probability Sampling

• Simple Random Sampling
• Sampling distribution
• The distribution of a sample statistic
• A visual display of the samples

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Types of Probability Sampling
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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

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Types of Probability Sampling

• Systematic Sampling
• Selection interval
• The distance between the elements selected in a
  sample
• Selection Interval (k) population size
• sample size

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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

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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

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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

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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

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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

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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

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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?

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Types of Nonprobabilty Sampling

• Purposive Sampling
• Quota Sampling
• Snowball Sampling
• Convenience Sampling

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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

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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

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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

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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

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Choosing a Sampling Technique

• Is it desirable to sample at all or can the whole
  population be used?
• Is it important to generalize to a larger
  population?
• Political preference polls
• Do you have the access and ability to perform
  probability sampling?
• Major considerations
• Methods
• Theory
• Practicality
• Ethics

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Summary

• Sampling is a means to an end.
• We sample because studying every element in our
  population is frequently beyond our means or
  would jeopardize the quality of our.
• On the other hand, we dont need to sample when
  studying every member of our population is
  feasible.