Unit 1- Statistical Sampling Flashcards

1
Q

Population

A

The whole set of items that are of interest

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2
Q

Census

A

Observes or measures every member of a population

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3
Q

Sample

A

Selection of observations taken from a subset of the population which is used to find out information about the population as a whole

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4
Q

Sampling units

A

Individual units of a population (often individually named/numbered)

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5
Q

Sampling frame

A

A list of sampling units

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6
Q

Advantage(s) of a census

A

Should give a completely accurate result

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7
Q

Disadvantage(s) of a census

A
  • Time-consuming and expensive
  • Can’t be used when testing destroys the item
  • Hard to process if a large quantity
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8
Q

Advantages(s) of a sample

A
  • Less time-consuming and expensive
  • Fewer people are needed
  • Less data to process
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9
Q

Disadvantage(s) of a sample

A
  • Data may not be as accurate
  • Not enough sample to inform about small sub-groups of the population
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10
Q

Random sampling

A

Every member of the population has an equal chance of being selected, so the sample would be representative of the population

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11
Q

Three methods of random sampling

A

Simple random sampling, systematic sampling and stratified sampling

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12
Q

Simple random sampling

A

Allocate each person or thing a unique number and then randomly generate using a random number table or lottery sampling

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13
Q

Lottery sampling

A

The members of the sampling frame could be written on tickets and placed into a ‘hat’

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14
Q

Systematic sampling

A

The required elements are chosen at random intervals from an ordered list

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15
Q

Stratified sampling

A

The population is divided into mutually exclusive strata and a random sample is taken from each

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16
Q

The number sampled in a stratum =

A

(number of stratum / number in population) * overall sample size

17
Q

Advantage(s) of random sampling

A
  • Free of bias
  • Easy and cheap for small populations/samples
  • Each sampling unit has a known equal chance
18
Q

Disadvantage(s) of random sampling

A
  • Not suitable when the population or sample size is large
  • A sampling frame is needed
19
Q

Advantage(s) of systematic sampling

A
  • Simple and quick to use
  • Suitable for large samples/populations
20
Q

Disadvantage(s) of systematic sampling

A
  • A sampling frame is needed
  • Can introduce bias if the sampling frame is random
21
Q

Advantage(s) of stratified sampling

A
  • Sample accurately reflects the population structure
  • Guarantees proportional presentation of groups in a population
22
Q

Disadvantage(s) of stratified sampling

A
  • Population must be clearly classified into distinct strata
  • A sampling frame is needed
  • Not suitable when the population/sample size is to large
23
Q

Two methods of non-random sampling

A

Quota sampling and opportunity sampling

24
Q

Quota sampling

A

An interview selects a sample that reflects the characteristics of a wide population and allocates them into an appropriate quota

25
Opportunity sampling
Taking the sample from people who are available at the time the study is carried out and who fit the required criteria
26
Advantage(s) of quota sampling
- Allows a small sample to still be representative - No sampling frame needed - Quick, easy and cheap - Easy to compare between different groups
27
Disadvantage(s) of quota sampling
- Can introduce bias - Population must be divided into groups which can be costly or inaccurate - Increasing scope of study increases number of groups, increasing time and expense - Non-responses aren't recorded as such
28
Advantage(s) of opportunity sampling
- Easy to carry out - Inexpensive
29
Disadvantage(s) of opportunity sampling
- Unlikely to be representative - Dependant on each researcher
30
Quantitative data/variables
Associated with numerical observations
31
Qualitative data/variables
Associated with non-numerical observations
32
Continuous variable
Can take any value in a given range
33
Discrete variable
Can only take specific values in a given range
34
Class boundaries in a group frequency table
The maximum and minimum values in each class
35
Midpoint in a group frequency table
The average of the class boundaries
36
Class width in a group frequency table
The range of the class boundaries
37