statistics - year 1

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daily mean temperature

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Description and Tags

large data set, sampling, [] distributions and []

31 Terms

1

daily mean temperature

  • measured in C

  • average of the hourly temperature readings measured during a 24-hour period

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2

daily total rainfall

  • measured in mm (to 1 d.p.)

  • includes rain, snow and hail (melted)

  • amounts less than 0.05mm are recorded as ‘tr‘ (trace)

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3

daily total sunshine

  • measured in hours (to the nearest tenth of an hour)

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4

daily maximum relative humidity

  • the amount of water vapour in the air

  • measured as a percentage of maximum water vapour that could be in the air

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5

daily mean windspeed (& direction)

  • measured in knots (1 knot = 1.15 mph)

  • direction is measured in degrees (to the nearest 10)

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6

daily maximum gust (& direction)

  • measured in knots (1 knot = 1.15 mph)*

  • direction is measured in degrees (from the north)

*beaufort conversion

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7

daily mean visibility

  • the greatest horizontal distance at which an object can be seen in daylight

  • measured in dm (decameters/10m)

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8

daily mean pressure

  • measured in hectopascals (hPa)

  • small range (~980 to 1035)

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9

daily mean cloud cover

  • measured in oktas (how many eighths of the sky is covered in clouds)

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10

population

a whole set of items that are of interest

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11

census

observes or measures every member of a population

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12

benefits and drawbacks of a census

  • it should give a completely accurate result

  • time consuming and expensive

  • cannot be used when the testing process destroys the item

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13

sample

  • a selection of observations taken from a subset of the population

  • used to find out about the population as a whole

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14

benefits and drawbacks of a sample

  • less time consuming and expensive than a census

  • the data may not be as accurate

  • the sample may not be large enough to give accurate information about a small sub-groups of the population

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15

sampling unit

individual units of a population

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16

sampling frame

a list of sampling units that are individually named or numbered

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17

simple random sample

  • random sampling method

  • each unit is allocated a unique number and numbers are selected randomly

  • numbers can be generated randomly (using a computer) or ‘drawn from a hat’

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18

benefits and drawbacks of simple random sampling

  • free of bias

  • each sampling has a known and equal chance of selection

  • not suitable when the population/sample size is large, as it is potentially time consuming, disruptive and expensive

  • a sampling frame is needed

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19

systemic sampling

  • random sampling method

  • required elements are chosen at regular intervals from an ordered list

  • the first item is chosen randomly, the rest chosen at regular intervals from the first (e.g. every 5 items)

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20

benefits and drawbacks of systemic sampling

  • simple and quick to use

  • suitable for large populations/samples

  • a sampling frame is needed

  • can introduce bias if sampling frame is not random

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21

stratified sampling

  • random sampling method

  • the population is divided into mutually exclusive strata (e.g under 18s and over 18s) and a simple random sample is taken from each

  • the number of samples taken from each strata must be proportional to the population

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22

benefits and drawbacks of stratified sampling

  • sample accurately reflects the population structure

  • guarantees proportional representation of groups within a population

  • population must be clearly classified into distinct strata

  • selection within each stratum has the same disadvantages as simple random

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23

quota sampling

  • non-random sampling

  • the population is divided into groups (quotas) according to a given characteristic

  • the interviewer meets people, assesses their group and allocates them into the appropriate quota

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24

benefits and drawbacks of quota sampling

  • allows a small sample to still be representative of the population

  • no sampling frame required

  • quick, easy and inexpensive

  • non-random sampling can introduce bias

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25

opportunity sampling

  • non-random sampling method

  • consists of taking a sample from people who are available at the time, who fit the criteria

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26

benefits and drawbacks of opportunity sampling

  • inexpensive and easy to carry out

  • unlikely to provide a representative sample

  • highly dependent on individual researcher

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27

quantitative data

data associated with numerical observations

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28

qualitative data

data associated with non-numerical observations

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29

continuous variable

a variable that can take any value in a given range

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30

discrete variable

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

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31

frequency density

frequency ÷ class width

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