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Sampling and Sampling Designs

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Title: Sampling and Sampling Designs Author: ELPS Last modified by *** Created Date: 9/22/1998 12:30:42 PM Document presentation format: – PowerPoint PPT presentation

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Title: Sampling and Sampling Designs


1
???????
2
Population ??
Sample ??
Sampling ??
? s2
?2
Generalization ??
Parameter ??
Statistic ???
3
Why sample?
  • Lower cost
  • Greater accuracy of results
  • Greater speed of data collection
  • Availability of population elements
  • Sample vs. Census

4
What is a good sample
  • Accuracy
  • Systematic variance ????
  • The variation in measures due to some known or
    unknown influences that cause the scores
    (results) to lean in one direction more than
    another
  • Precision
  • Sampling error ????
  • the degree to which a given sample differs from
    the underlying population
  • sampling error tends to be high with small sample
    sizes and will decrease as sample size increases

5
??
  • Differences between parameters and
    statisticserror
  • sampling error ????
  • Systematic error ???? (also called measurement
    error)

6
Target Population
  • group to which you wish to generalize the results
    of the study
  • should be defined as specifically as possible

7
  • Sampling frame ????
  • the list of elements from which the sample is
    actually drawn

8
Steps in sampling design
  • What is the population?
  • What are the parameters of interest?
  • What is the sampling frame?
  • What is the type of sample?
  • What size sample is needed?
  • How much will it cost?

9
What is the population
  • Clearly define your population of interest
  • Population vs. research subjects

10
What are the parameters of Interest?
  • Summary of descriptors (mean, variance) of
    variables in the population
  • Issue of the scale of measurement

11
What is the sampling frame?
  • the list of elements from which the sample is
    actually drawn

12
What is the type of sample?
  • Probability sample vs. nonprobability sample

13
What size sample is needed?
  • The larger, the better

14
Sampling Techniques
  • Probability Sampling (random sampling) ????
  • Nonprobability Sampling (nonrandom sampling)
    ?????

15
Probability Sampling
  • sample should represent the population
  • using random selection methods
  • members of the population have a known and
    non-zero chance of being selected (EPSEM Equal
    Probability of SElection Method)

16
Types of Probability Sampling
  • Simple random sampling??????
  • Systematic sampling?????
  • Stratified sampling ??????
  • Cluster sampling ????
  • Double sampling ????

17
Simple Random Sampling
  • every unit in the population has an equal and
    known probability of being selected as part of
    the sample (??)

18
Random Numbers Table ???
  • a table of random digits arranged in rows and
    columns
  • after assigning an identification number to each
    member of the population, numbers in the random
    numbers table are used to select those who will
    be in the sample

19
???
1 2 3 4 5 6 7 8 9 10
1 49486 93775 88744 80091 92732 38532 41506 54131 44804 43637
2 94860 36746 04571 13150 65383 44616 97170 25057 02212 41930
3 10169 95685 47585 53247 60900 20097 97962 04267 29283 07550
4 12018 45351 15671 23026 55344 54654 73717 97666 00730 89083
5 45611 71585 61487 87434 07498 60596 36255 82880 84381 30433
6 89137 30984 18842 69619 53872 95200 76474 67528 14870 59628
7 94541 12057 30771 19598 96069 10399 50649 41909 09994 75322
8 89920 28843 87599 30181 26839 02162 56676 39342 95045 60146
9 32472 32796 15255 39636 90819 54150 24064 50514 15194 41450
10 63958 47944 82888 66709 66525 67616 75709 56879 29649 07325
20
Characteristics of simple random sampling
  • Unbiased ???????????????
  • Independence ?????????????????????????

21
Limitations of simple random samples
  • not practical for large populations
  • Simple random sampling becomes difficult when we
    dont have a list of the population

22
Systematic Sampling?????
  • a type of probability sampling in which every kth
    member of the population is selected
  • kN/n
  • N size of the population
  • n sample size

23
For example You want to obtain a sample of 100
from a population of 1,000. You would select
every 10th (or kth) person from the list. k
1000/10010
24
Advantages/disadvantages of systematic sampling
  • Assuming availability of a list of population
    members
  • Randomness of the sample depends on randomness of
    the list
  • periodicity bias ??????????????????, systematic
    sampling ???????(periodicity bias)

25
Stratified Random Sample??????
  • Prior to random sampling, the population is
    divided into subgroups, called strata, e.g.,
    gender, ethnic groups, professions,
    etc.??????????(Strata) ????????
  • Subjects are then randomly selected from each
    strata????????????(using simple random sampling)

26
???
???
???
. . . . .
?K?
Sample
27
  • Homogeneity is very high within the strata.
  • Heterogeneity is very high between the stratas

28
Why use stratified samples?
  • permits examination of subgroups by ensuring
    sufficient numbers of subjects within subgroups
    ??????????????????,????????
  • generally more convenient than a simple random
    sample

29
Potential disadvantages
  • Sometimes the exact composition of the population
    is often unknown
  • with multiple stratifying variables, sampling
    designs can become quite complex

30
Types of Stratified Sampling
  • Proportionate Stratified Random Sampling ????????
  • Disproportionate Stratified Random
    Sampling?????????

31
Proportionate Sampling
  • strata sample sizes are proportional to
    population subgroup sizes?????????
  • e.g., if a group represents 15 of the
    population, the stratum representing that group
    will comprise 15 of the sample

32
Disproportionate Sampling
  • strata sample sizes are not proportional to
    population subgroup sizes?????????????????????
  • may be used to achieve equal sample sizes across
    strata

33
For example Suppose a researcher plans to
conduct a survey regarding various attitudes of
Agricultural College Students at Tunghai U. He
wishes to compare perceptions across 4 major
groups but finds some of the groups are quite
small relative to the overall student population.
As a result, he decides to over-sample minority
students. For example, although Hospitality
students only represent 10 of the Agricultural
student population, he uses a disproportional
stratified sample so that Hospitality students
will comprise 25 of his sample.
34
Cluster Sampling????
  • used when subjects are randomly sampled from
    within a unit or group (e.g., classroom,
    school, country, etc)
  • ????????? (cluster),?????????????????????????????

35
??
??
??
??
??
??
??
k ?
Population
Sample
36
Example
  • ???????????????
  • ??????????????
  • ????3??????3????????????
  • Compare using cluster sampling technique and
    simple sampling technique

37
Why use cluster samples?
  • They're easier to obtain than a simple random or
    systematic sample of the same size

38
Disadvantages of Cluster Sampling
  • Less accurate than other sampling techniques
    (?selection stages, ?accuracy)
  • Generally leads to violation of an assumption
    that subjects are independent

39
Double sampling ?????
  • ???????????????
  • Systematic sample cluster/stratified sample

40
Nonprobability sampling
  • Convenience sampling ?????
  • getting people who are most conveniently
    available
  • fast low cost
  • Purposive sampling ?????
  • Judgment sampling
  • Quota sampling
  • Snowball sampling ??????

41
Characteristics of nonprobability samples
  • members of the population do not have a known
    chance of being selected
  • do not represent any known population
  • results cannot be generalized beyond the group
    being tested
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