Week 5 (Sampling Techniques) Flashcards

1
Q

Reliability vs Validity:

And methods for testing them

A

R=The consistency in measurement - the same data would be collected each time in repeated observations of the same phenomenon
R1-Test-Retest Method (Make the same measurement more than once)
R2-Split-Half Method(Assign a set of measurements to half of the sample and another set to the other half)
R3-Use Established Measures(Measures that have proven their reliability in previous research)

V=A term describing a measure that accurately reflects the concept it is intended to measure
V1- Face validity(quality of an indicator that makes it seem a reasonable measure of some variable)
V2-Criterion-related validity(degree to which a measure relates with some external criterion {predictive validity}
V3-Construct validity(degree to which a measure relates to other variables as expected within a system of theoretical relationships)
V4-Content validity(The degree to which a measure covers the range of meanings included within a concept)

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2
Q

Sampling in Qualitative vs Quantitative research:

A

Qualitative research An in-depth understanding is the main goal. Qualitative researchers tend to use non-probability sampling.

Quantitative research: the goal may be to generalize findings. If this is the case, then probability sampling techniques are used.

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3
Q

Element
Sample
Population
Sampling
Sampling Frame:
Random sampling:

A

Element:The unit of which a population is composed, and which is selected in a sample

Sample: A subset of cases selected from a population

Population : The theoretically specified aggregation (collection) of the elements in a study

Sampling : The technique used to acquire a sample from a population of interest

Sampling frame:A list or quasi-list of elements from which a probability sample is selected

Random Sampling:the sampling method in which each element has an equal chance of selection independent of any other event in the selection process

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4
Q

5 reasons it is important to sample:

A

1.Studying a subset of a population is cheaper than studying the entire population, saves time, labor, resources
2.We collect more information
3.Guard against conscious or unconscious bias
4.In probability sampling, there is a higher level of precision
5.In probability sampling, we can achieve representativeness, so our results can be generalized

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5
Q

What are the two major sampling techniques and general info about them:

A

Probability Sampling :
Sampling frame is generally known
Certain characteristics of the population are known
Probability of selection is known
Sample size is known and is calculated for representativeness
Sampling ends when the sample size is met
Sample may be representative of the population

Non-probability Sampling :
Sampling frame is not known
Certain characteristics of the population may be anticipated
Probability of selection is not known
Sample size is defined based on convenience
Sampling ends when a sufficient sample size is located
Not representative

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6
Q

Types of probability sampling:

A

1.Simple Random Sampling
Elements composing a population are assigned numbers, a set of random numbers is then generated, and elements having those number are included in the sample

  1. Systematic sampling: Using a fixed interval, every kth element in the sampling frame is chosen for inclusion in the sample. To avoid bias, choose the first element from the list at random (usually between 1 and the sampling interval).

sampling interval = p/s

Extra: Stratified Sampling
Is not an alternative to random or systematic sampling but is a refinement of both. Use this type of sampling when we want to ensure certain characteristics in the population are reflected in our sample

The grouping of the units composing a population into homogeneous/similar subsets (strata) with heterogeneity/differences between subsets, and to select the appropriate number of elements from each

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7
Q

Types of non probability sampling:

A
  1. Reliance on Available Subject/Convenience Sampling
  2. Snowball Sampling (Rely on referrals, a network to develop a sample )
  3. Purpose Sampling (Select the units to be observed based on your own judgment about which ones will be most useful or representative)
  4. Quota Sampling(Units are selected into the sample on the basis of pre-specified characteristics so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied)
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