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maths > Statistical sampling > Flashcards

Statistical sampling Flashcards

1
Q

What is random (simple) sampling

A

A sample where each individual has a equal chance of being chosen

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2
Q

How would you form a random sample from a population of n individuals

A
  • Give all individuals a unique integer from 1 to n
  • Generate a random number (with a calculator)
  • Continue until the sample size is reached (discard duplicates)
  • Chose the people assigned the generated numbers
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3
Q

What are the benefits of random sampling

A
  • Equal chance of selection, so reduces bias
  • Requires less population knowledge to be completed
  • Simplest form of sampling
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4
Q

What are the potential problems with random sampling

A
  • Data is not necessarily representative of the population
  • Time consuming to allocated numbers and then choose
  • Ineffective with smaller populations
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5
Q

What is systematic sampling

A

A sample that selects individuals at fixed periodic intervals

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6
Q

How would you form a systematic sample from a population

A

Choose every nth individual, depending on the size of the population and of the desired sample size.

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7
Q

What are the benefits of systematic sampling

A
  • Simple and convenient to use
  • Creates a sample of members evenly distributed in the sample, so reduces bias
  • Works effectively for large populations
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8
Q

What are the potential problems with systematic sampling

A
  • Requires the knowledge of an approximate population total
  • Interacts with periodic traits (ie. systematic errors are either ignored or exaggerated)
  • It creates a fractional chance of selection, which means that most individuals are systematically missed, with no chance of selection
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9
Q

What is stratified sampling

A

A sample with subgroups (strata) in the same proportion as the whole population

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10
Q

How would you form a stratified sample from a population

A
  • Calculate the proportion of the population made up by the subgroups (number in subgroup / total population)
  • Multiply this proportion by the desired sample size
  • Use random sampling to select this number of individuals from each group.
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11
Q

What are the benefits of stratified sampling

A
  • Representative of the whole population
  • Reduces bias
  • Using random sampling to fill each category if simple to do
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12
Q

What are the potential problems with stratified sampling

A
  • Requires detailed knowledge about individuals in the population to calculate the proportions
  • The random sampling evolved is time consuming
  • Individuals overlapping categories may cause issues
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13
Q

What is cluster sampling

A

A sample made up of a pre-existing sub group (cluster) that is representative of the whole population.

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14
Q

How would you form a cluster sample

A

Choose a cluster of individuals that are representative of the whole population to use as a sample.
(eg. people on the same flight at an airport - as long as the sample doesn’t need to be representative of destinations)

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15
Q

What are the benefits of cluster sampling

A
  • Requires minimal knowledge about the total population size
  • Requires minimal effort to construct a sample
  • Can be used on very large populations to save time
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16
Q

What are the potential problems with cluster sampling

A
  • Can result in unconscious bias if the cluster isn’t representative of the population
  • Results can only apply to the specific demographic of the cluster
  • Only available in populations with unbiased clusters dependent on the reason for the sample (eg. if location specific, can’t use postcode clusters)
17
Q

What is opportunity sampling

A

A sample made up of individuals chosen as the opportunity arises

18
Q

How would you form a sample with opportunity sampling

A

Select individuals that are available and willing to take part, not considering if the sample is exactly representative of the population.

19
Q

What are the benefits of opportunity sampling

A
  • Convenient and easy to carry out
  • Data is immediately available
  • Can be used for very large populations
20
Q

What are the potential problems with opportunity sampling

A
  • Sample is not representative of the whole population
  • Prone to unconscious bias
  • Researcher bias can occur, where only certain people are targeted
21
Q

What is quota sampling

A

A sample made up of individuals that fit into predetermined sub groups (strata), selected until the groups are filled.

22
Q

How would you form a sample with quota sampling

A
  • Calculate the number of individuals required from each group to be part of the sample (ie. by calculating the proportion if the total population is known)
  • Use another sampling method (eg. opportunity, random) until each quota is filled, then ignore individuals in the filled groups
23
Q

What are the benefits of quota sampling

A
  • Convenient way of creating a sample
  • Sample is representative of the population
  • Saves time as pre-counting the categories isn’t needed
24
Q

What are the potential problems with quota sampling

A
  • May lead to researchers bias as individuals are targeted to fill the quotas
  • cross over between groups may make the sample less representative
  • If quotas filled by opportunity sampling, bias may arise
25
Q

What is self-selected sampling

A

A sample of individuals that have elected themselves to take part

26
Q

How would you form a self-selected sample

A

Advertise the need for a sample and allow individuals to volunteer themselves to take part (eg. optional online survey)

27
Q

What are the benefits of self-selected sampling

A
  • Allows all view points the opportunity to be heard
  • Easier method for large population
  • Requires minimal effort from the researchers
28
Q

What are the potential problems with self-selected sampling

A
  • May be time consuming as individuals have to elect themselves to take part
  • Only individuals with passionate views will usually volunteer, so bias may arise
  • Not representative of the population

maths (19 decks)

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