Data collection Flashcards

1
Q

Qualitative

A

Data that usually given in words not numbers to describe something

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2
Q

Quantitative

A

Data that is given using numbers which counts or measures something

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3
Q

Discrete

A

A variable that can take only specific values in a given range

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4
Q

Continuous

A

A variable that can take any value in a given range

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5
Q

class boundaries

A

They tell the maximum and minimum values that belong in each class

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6
Q

midpoint

A

the average of the class boundaries

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7
Q

class width

A

the difference between the upper and lower class boundaries

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8
Q

population

A

A whole set of the things that you are interested in

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9
Q

sample

A

A subset of the population which is used to collect the data from

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10
Q

sampling frame

A

a list of all members of the population
sample unit is one thing within sampling frame

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11
Q

population parameter

A

a numerical value which describes a characteristic of the population

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12
Q

sample statistic

A

a value computed using data from the sample

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13
Q

Census Definition

A

Collects data about all the members of a population

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14
Q

Census Adv

A

Gives fully accurate results

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15
Q

Census Disadv

A

Time consuming and expensive to carry out, can destroy or use up all the members of a population when they are consumable

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16
Q

Sampling Def

A

collects data from a subset of the population, the size of sample can affect the validity of any conclusion drawn

17
Q

Sampling Adv

A

quicker and cheaper, less data needed to be analysed

18
Q

Sampling DisAdv

A

might not represent the population accurately, could introduce bias

19
Q

Simple Random Def

A

A sample where every possible sample of size n has an equal chance of being selected

20
Q

Simple Random Adv

A

Easy for small samples
Random Sample
Free of bias

21
Q

Simple Random DisAdv

A

Difficult for large samples
Sampling frame

22
Q

Systematic Sampling Def

A

Where every nth person is picked from an ordered sampling frame

23
Q

Systematic Sampling Adv

A

Random Sample
Quick / Easy for small samples

24
Q

Systematic Sampling DisAdv

A

Sampling frame needed
If list is not random, the sample may not b random

25
Stratified Sampling Def
The population is divided into disjoint groups(called strata) and then a random sample is taken form each group(stratum) - The proportion of a stratum that is sampled is equal to the proportion of the population that belong to that stratum
26
Stratified sampling Adv
Sample accurately reflects the population structure, Guarantee proportional representation of groups within a population
27
Stratified Sampling DisAdv
Population must be clearly classified into distinct strata, selection within each stratum suffers from the same disadvantages as simple sampling
28
Quota Sample Def
Where the population is split into strata (groups) and a sample size is chosen for each group that is proportional to the group size. These people are then selected on a first come first served basis. Once you reach your quota, you stop.
29
Opportunity sampling
consists of taking the sample from people who are available at the time the study is carried out and who fit the criteria you are looking for
29
Opportunity Sampling Adv
Easy to carry put, Inexpensive
30
Quota Sample Adv
Do not need sampling frame Quick easy + cheap Reflects population Structure
31
Opportunity sampling Disadv
32
Quota Sample DisAdv
Not random sample People may refuse Interviewer bias Not always possible to split population into distinct groups