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Stats data collection Flashcards

(65 cards)

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1
Q

What is a population in statistics?

A

The whole set of items that are of interest

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2
Q

What is raw data?

A

Unprocessed information obtained from a population

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3
Q

What is a census?

A

Observes or measures every member of a population

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4
Q

What is a sample?

A

A selection of observations taken from a subset of the population

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5
Q

Advantages of a census include:

A
  • Completely accurate result
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6
Q

Advantages of a sample include:

A
  • Less time consuming than a census
  • Less expensive than a census
  • Fewer people have to respond
  • Less data to process than in a census
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7
Q

Disadvantages of a census include:

A
  • Time consuming
  • Expensive
  • Cannot be used when testing process destroys the item
  • Hard to process large quantities of data
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8
Q

Disadvantages of a sample include:

A
  • Data may not be as accurate
  • Sample may not be large enough for small sub-groups
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9
Q

What factors affect the size of a sample?

A
  • Required accuracy
  • Available resources
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10
Q

How does the size of the sample affect accuracy?

A

Generally, the larger the sample, the more accurate it is

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11
Q

What happens if the population is very varied?

A

You need a larger sample than if the population were uniform

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12
Q

What are individual units of a population called?

A

Sampling units

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13
Q

What is a sampling frame?

A

A list of individually named or numbered sampling units of a population

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14
Q

True or False: A sample can lead to different conclusions due to natural variation in a population.

A

True

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15
Q

Fill in the blank: Information obtained from a population is known as _______.

A

raw data

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16
Q

Fill in the blank: A census measures every member of a _______.

A

population

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17
Q

Fill in the blank: A sample is used to find out information about the _______ as a whole.

A

population

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18
Q

What is random sampling?

A

Every member of the population has an equal chance of being selected

Random sampling helps ensure that the sample is representative of the population and reduces bias.

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19
Q

What are the three methods of random sampling?

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

Define simple random sampling.

A

Every sample of size n has an equal chance of being selected.

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21
Q

What is required to carry out a simple random sample?

A

A sampling frame, usually a list of people or things.

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22
Q

What is the purpose of allocating a unique number to each member in a sampling frame?

A

To randomly select members for the sample.

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23
Q

Name two methods of choosing numbers for random sampling.

A
  • Generating random numbers
  • Lottery sampling
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24
Q

Describe lottery sampling.

A

Members of the sampling frame are written on tickets and drawn from a ‘hat’.

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25
True or False: In random sampling, bias can still affect the results.
False
26
Fill in the blank: A simple random sample of size n requires a _______.
[sampling frame]
27
What is the first step in random sampling?
Choose the first person at random.
28
In stratified sampling, how is the population divided?
Into mutually exclusive strata.
29
What is an example of strata in stratified sampling?
Males and females.
30
What should be the proportion of each stratum sampled in stratified sampling?
The same.
31
Fill in the blank: The number sampled in a stratum = number in stratum _______ number in population * overall sample size.
[divided by]
32
What is the formula to calculate the number of people to sample from each stratum?
number in stratum / number in population * overall sample size.
33
What is an advantage of simple random sampling?
Free of bias ## Footnote Simple random sampling ensures that every member of the population has an equal chance of being selected, minimizing biases.
34
What is another advantage of simple random sampling?
Easy and cheap to implement for small populations and small samples ## Footnote Simple random sampling is particularly effective when dealing with smaller datasets.
35
What does each sampling unit in simple random sampling have?
A known and equal chance of selection ## Footnote This characteristic is crucial for reducing bias in the sampling process.
36
What is a disadvantage of simple random sampling related to large populations?
Not suitable when the population size or the sample size is large as it is potentially time consuming, disruptive and expensive ## Footnote Larger populations require more resources and time to ensure random selection.
37
What is required for simple random sampling?
A sampling frame ## Footnote A sampling frame is a complete list of the population from which samples are drawn.
38
What is a key advantage of systematic sampling?
Simple and quick to use
39
What is another advantage of systematic sampling?
Suitable for large samples and large populations
40
What is a major advantage of stratified sampling?
Sample accurately reflects the population structure
41
What does stratified sampling guarantee?
Proportional representation of groups within a population
42
What is a disadvantage of stratified sampling?
A sampling frame is needed
43
What can introduce bias in stratified sampling?
If the sampling frame is not random
44
What must the population be classified into for stratified sampling?
Distinct strata
45
Selection within each stratum suffers from the same disadvantages as _______.
simple random sampling
46
What are the two types of non-random sampling?
Quota sampling and Opportunity sampling ## Footnote Non-random sampling is utilized when random sampling is not feasible.
47
Define quota sampling.
An interviewer selects a sample that reflects the characteristics of the whole population by dividing the population into groups based on specific characteristics ## Footnote The sample size for each group is determined by the proportion of that group in the population.
48
What is the process of quota sampling?
Meet people, assess their group, allocate them into the appropriate quota until all quotas are filled ## Footnote If a person refuses or the quota is full, the interviewer moves on to the next person.
49
What is opportunity sampling?
Taking a sample from people who are available at the time of the study and fit the criteria being researched ## Footnote It is also known as convenience sampling.
50
Provide an example of opportunity sampling.
The first 20 people you meet outside a supermarket on a Monday morning who are carrying shopping bags ## Footnote This method relies on the availability of subjects at a specific time.
51
List advantages of quota sampling.
* Allows a small sample to still be representative of the population * No sampling frame required * Quick, easy and inexpensive * Allows for easy comparison between different groups within a population ## Footnote These advantages make quota sampling a practical choice in many research scenarios.
52
List disadvantages of quota sampling.
* Non-random sampling can introduce bias * Population must be divided into groups, which can be costly or inaccurate * Increasing scope of study increases number of groups, adding time and expense * Non-responses are not recorded as such ## Footnote These disadvantages can affect the validity of the research findings.
53
What is opportunity sampling?
A sampling method where participants are selected based on their availability and willingness to participate. ## Footnote This method is often used in research settings for its convenience.
54
What are the advantages of opportunity sampling?
* Easy to carry out * Inexpensive ## Footnote Opportunity sampling is favored for its simplicity and cost-effectiveness.
55
What is a major disadvantage of opportunity sampling?
Unlikely to provide a representative sample. ## Footnote The sample may not reflect the broader population due to its reliance on availability.
56
How does opportunity sampling depend on the researcher?
It is highly dependent on individual researcher. ## Footnote The choices made by the researcher can significantly influence the sample's characteristics.
57
What are quantitative variables or quantitative data?
Variables or data associated with numerical observations ## Footnote Example: Shoe size is a quantitative variable.
58
What are qualitative variables or qualitative data?
Variables or data associated with non-numerical observations ## Footnote Example: Hair colour (blonde, red, brunette) is a qualitative variable.
59
What is a continuous variable?
A variable that can take any value in a given range ## Footnote Example: Time can take values like 2 seconds, 2.1 seconds, etc.
60
What is a discrete variable?
A variable that can take only specific values in a given range ## Footnote Example: The number of girls in a family is a discrete variable.
61
How can large amounts of data be displayed?
In a frequency table or as grouped data.
62
What is a grouped frequency table?
A table where specific data values are not shown; groups are known as classes.
63
What are class boundaries?
They tell you the maximum and minimum values that belong in each class.
64
What is the midpoint in a class?
The average of the class boundaries.
65
What is class width?
The difference between the upper and lower class boundaries.

Maths General (6 decks)

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