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MGMT2003 > Sampling > Flashcards

Sampling Flashcards

1
Q

What is a population or universe?

A

Any complete group with common characteristics

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2
Q

What is a population element?

A

Single member of a population

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3
Q

What is a census?

A

Investigation of all individual elements that make up a population

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4
Q

What is a sample?

A
  • Subset of the larger population of interest

- This is the subset of group that the researcher will actually study or investigate

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5
Q

What is a population frame?

A

A list of all the elements in the population

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6
Q

What is a sample frame?

A

A list of all the elements in the population from which the sample may be drawn

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7
Q

What is sampling frame error?

A

An error which occurs when certain sample elements are not listed or are not accurately represented in a sampling frame

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8
Q

What is a sampling unit?

A

An element or group of elements subject to selection in the sample

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9
Q

What is inclusion/exclusion criteria?

A

The criteria potential participants must meet in order to be included in the study

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10
Q

What are the core statistical concepts?

A
  • Descriptive statistics
  • Inferential statistics
  • Population parameters
  • Sample statistics
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11
Q

What are descriptive statistics?

A
  • Describe the data
  • Measure of central tendency, frequencies, dispersion
  • Trends
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12
Q

What are inferential statistics?

A
  • Project characteristics of a sample to an entire population
  • Make an inference about a population from a sample
  • Used in hypothesis testing
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13
Q

What are population parameters?

A
  • Characteristics of the population
  • Variable in a population or measure characteristics of the populaiton
  • Greek letters as notation
  • μ = ∑X/N
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14
Q

What are sample statistics?

A
  • Estimates of population parameters
  • Variables in a sample or measures computed from sample data
  • English letters for notation
  • X̅ = ∑X/N
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15
Q

What is the cost associated with sampling and the solution to this?

A
  • A loss of information

- To make up for this loss we have to ensure that the sample is representative of the population

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16
Q

What does representativeness determine?

A

The representativeness of the sample determines the extent to which generalisable inferences can be made

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17
Q

What does the CLT imply?

A
  • Suggests that the sampling distribution of the sample mean produces a normal curve
  • As the sample size increases, the means of random samples taken form the population approach a normal distribution
  • This means we have a representative sample - and our sample mean will be within close range of the true population mean
18
Q

What is probability sampling?

A

Chance of selecting any particular member is known and is equal for all units (probability is non-zero)

19
Q

What methods of probability sampling are there?

A
  • Simple random
  • Systematic
  • Stratified
  • Cluster
20
Q

What is simple random sampling?

A

A sampling procedure that ensures that each elements in the population will have an equal chance of being included in the sample

21
Q

What is systematic sampling?

A

Every nth name from a list (sampling frame) will be drawn

22
Q

What is stratified sampling?

A
  • Subsamples are drawn within different strata
  • Strata are subgroups of elements that may be expected to have different parameters on a variable of interest
  • Each stratum is more or less equal on some characteristic
23
Q

What different types of stratified sampling are there?

A
  • Subjects drawn from each stratum can be either dispropriationate or proportionate to the number of elements in the stratum
    • Proportionate stratified sampling (20% of members from each stratum)
    • Disproportionate stratified sampling (% of members disproportionate across stratum)
24
Q

What is cluster sampling and what is the important aspect of it?

A
  • Purpose is to sample economically while retaining the characteristics of a probability sample
  • Primary sampling unit
    • No longer the individual elements in the population
    • Instead, a larger cluster of elements located in proximity to on another
25
Q

What is non-probability sampling and when is it useful?

A
  • Chance of selecting any particular member is unknown

- Useful when sampling frame cannot be created

26
Q

What kinds of non-probabilty sampling are there?

A
  • Convenience methods

* Purposive Methods

27
Q

What types of convenience methods of sampling are there?

A
  • Convenience

* Snowball

28
Q

What is convenience sampling?

A
  • The sampling procedure of obtaining the people or units that are most consistently available
  • Least reliable of all sampling designs in terms of generalisability, but may be the only viable alternative when quick and timely information is needed
29
Q

What is snowball sampling?

A
  • Initial respondents are selected by probability methods

- Additional respondents are obtained form information provided by the initial respondents

30
Q

What types of purposive sampling methods are there?

A
  • Judgement

* Quota

31
Q

What is judgement sampling?

A
  • An experienced individual selects the sample based on his or her judgement about some appropriate characteristics required of the sample member
  • May curtail generaliablity, but it is the only viable sampling method for obtaining the type of information from specific sub-groups
32
Q

What is quota sampling?

A
  • Ensures that the various subgroups in a population are represented on the pertinent sample characteristics
  • Are basically stratified samples from which subjects are selected non-randomly and on the basis of convenience
  • Needed to adequately represent minority groups
33
Q

What are confidence and precision in regard to sampling errors?

A
  • Confidence and precision refer to the extent and degree to which legitimate inferences can be made about a target population from a sample
  • Confidence and precision will be influenced by sampling errors
34
Q

What do sampling errors do?

A
  • Sampling errors limit the extent of generalisability because they diminish representativeness
  • Sampling errors can cause differences in the sample statistic and population parameters
35
Q

What types of sampling errors are there?

A
  • Random sampling error

* Non-random or systematic sampling error

36
Q

What are random sampling errors?

A
  • Difference between the sample result and the result of a census conducted using identical procedures
  • Statistical fluctuation due to chance variations
    • Large number of untypical subjects
    • Outliers and extreme values
  • Inversely related to sample size, thus only way to manage is through large sample
37
Q

In sampling, what are non-random or systematic sampling errors?

A
  • Sampling error not due to chance i.e. biased selection
  • Non-response error
  • Pattern of responses are atypical of target population: self-selection bias; social desirability
  • Study design errors or imperfections in execution
  • Managed through sampling design
38
Q

In sampling, what kinds of non-random or systematic sampling errors are there?

A
  • Self-selection bias

* Social desirability bias

39
Q

What is self-selection bias?

A
  • The bias that creeps into results when the participants of a study are people who choose to participate
  • The key component is that research subjects (or organisations) volunteer to take part in the research on their own accord. They are non approached by the researched directly
  • It’s a bias because a group of people who choose to participate is not the same as a random sample of the population
  • They may also differ in important ways from those who do not choose to partipcate
    • They motivations and decision to participate in the study may reflect some inherent bias
  • This can either lead to the sample not being representative of the population being studies, or exaggerating some particular finding from the study
40
Q

What is social desirability bias?

A
  • The tendency of subjects to attribute to themselves statements which are desirable and reject those which are undesirable
  • In other words, some people like to portray themselves positively - tending to exaggerate or inflate their strengths and achievements, and often deny or trivialise their deficiencies and failures
  • Particularly problematic with self-reports of performance
  • To manage this it is important to collect data from multiple sources of use a scale to measure social desirability

MGMT2003 (13 decks)

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