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Statistics GCSE Edexcel > 1 Collecting Data > Flashcards

1 Collecting Data Flashcards

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1
Q

raw

A

data before it is sorted
eg data from a survey

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2
Q

quantitative

A

numerical
eg height

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3
Q

qualitative

A

non numerical
eg colour

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4
Q

continuous

A

can take any value on a scale
eg weight, length

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5
Q

discrete

A

can only take particular values on a scale
eg shoe size, no. siblings

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6
Q

categorical

A

can be sorted into non overlapping/ranked categories
eg gender

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7
Q

ordinal

A

can be written in order / be given a numerical ranking scale
eg test scores

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8
Q

bivariate

A

involves pairs of related date
eg working hours and pay

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9
Q

multivariate

A

3+ sets of data
eg plants: colour, leaf size and height

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10
Q

do intervals (usually) need to be equal widths

A

no

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11
Q

primary

A

collected by/for the user

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12
Q

secondary

A

collected by/for someone other than the current user
eg websites, newspapers, research articles, databases, census returns

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13
Q

primary vs secondary (adv and disadv)

A
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14
Q

census

A

survey/investagation with data from EVERY MEMBER of a population

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15
Q

sampling units

A

people or items that are to be sampled

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16
Q

sampling frame

A

a list of all the sampling units

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17
Q

eg of population, SU and SF
(number of hours spent on hw is more in Y7 and Y9

A

P: all Y7 and Y9 students
SU: students in Y7&9
SF: list of Y7&9 students

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18
Q

petersen capture recapture formula

A

m/n = M/N
no. marked in recapture/number in recapture = original number marked/total population

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19
Q

assumptions made in capture recapture method

A
  • P(caught) is same for all individuals
  • marks are not lost and always recognisable
  • sample size is large enough to be representative of population
  • population has not changed (no members have entered or left, no births or deaths between release and recapture)
  • marked individuals have mixed with rest of population between release and recapture
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20
Q

random sample

A

every sampling unit (member of population) has an equal chance of being included

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21
Q

pros and cons of random sample

A

P: more likely to be representative of population if sample size is large
- choice of members of sample is unbiased

D: need a full list of population
- need a large sample size

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22
Q

problems of random sample

A

random numbers may be out of range
random numbers may be repeated

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23
Q

how to generate random sample

A

1) RNG (eg calc) / names from a hat / random number table
2) ignore numbers out of range and duplicates
3) do this X times

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24
Q

judgement sampling

A

using your judgement to choose a sample which is representative of the population

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25
Q

opportunity sampling

A

using the people or items available at the time

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26
Q

cluster sampling

A

use natural groups which occur in data
list of clusters = sampling frame
and some clusters are randomly selected to make up the sample (eg geographical areas)

27
Q

systematic sampling

A

choose a start point in the sampling frame at random and choose items at regular intervals

28
Q

quota sampling

A

group the population by chosen characteristics and take a quota from each group (eg age/gender)

29
Q

how to decide if a sampling method is suitable

A
  • will it be biased
  • will SS be sensible
  • how quick and easy is method
  • how expensive
30
Q

stratified sample

A

contains members of each stratum in proportion to the size of that stratum.
sample from each stratum is selected randomly

31
Q

describe how to do a stratified sample

A

1) calculations
THEN -order each group into order
- assign each a random no.
- choose the relevant no. of people to survey

32
Q

data collection sheet

A

table/tally chart for recording your results

33
Q

direct observation

A

recording behaviour patterns systematically as you observe them

34
Q

independent variable

A

explanatory variable
what you control (but change)

35
Q

dependent variable

A

response variable
affected based on your changes to the explanatory variable

36
Q

extraneous variable

A

variable that you are not interested in but that could affect your results

37
Q

laboratory experiment

A
38
Q

field experiment

A
39
Q

natural experiment

A
40
Q

LabE pros and cons

A
41
Q

FieldE pros and cons

A
42
Q

NatE pros and cons

A
43
Q

simulation

A

can be used to model random real life evens to predict what could actually happen.
easier and cheaper than collecting and analysing real data

44
Q

an experiment is valid/reliable if…

A

when replicating an experiment gives very similar data

45
Q

questionnaire

A

set of questions designed to obtain data

46
Q

open vs closed question

A

open: no suggested answers
closed: answers to choose from

47
Q

con of open questions

A

every respondent gives a different answer so is hard to summarise and analyse the answers

48
Q

problem with opinion scales

A

most will answer somewhere near the middle
unlikely to indicate a strong opinion - do not want to seem extreme

49
Q

what to do in questionnaires

A
  • short questions, simple language
  • no biased/leading questions
  • intervals that don’t overlap
  • options cover all possibilities (0/never/don’t know)
  • include time frame
  • avoid questions respondents are unlikely to answer honestly
50
Q

interview pros and cons

A
51
Q

anonymous questionnaire pros and cons

A
52
Q

pilot survey

A

conducted on a small sample to test the design and methods of the survey

checks:
- respondents understand questions
- closed questions include all likely answer options
- questionnaire collects the information needed

53
Q

random response method

A
54
Q

how to answer estimate question about RRM

A
55
Q

outliers/anomalous data

A

values that do not fit the pattern of the data
can be ignored if it is due to a measuring/recording error

56
Q

cleaning data

A
  • identifying and correcting/removing inaccurate/extreme values
  • removing units or other symbols form data
  • deciding what do to with missing values
57
Q

control groups? and where are they often used

A
58
Q

matched pair test

A

where two group of people are used to test theffects of a particular factor
each individual in a group is paired with an individual in the second group with similar characteristics barring the factors which is to be studied

59
Q

pros and cons of matched pairs

A

P: can control for different factors
C: may have to test a large group at first to find enough matched pairs for a good test

60
Q

who is often used in MPTs

A

identical twins- easier to see different results
disadvantage: limited supply of willing twins

61
Q

hypothesis

A

an idea that can be tested by collecting and analysing data

62
Q

designing investigations- what do you need to consider?

A
63
Q

difference between field and natural experiments

A

a field experiment the researcher manipulates the independent variable (IV), while in a natural experiment the researcher does not

Statistics GCSE Edexcel (2 decks)

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