Statistics gcse (copy)

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Things to consider when collecting data

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1

Things to consider when collecting data

  • The sample size

  • whether it’s representative

  • Whether it’s biased

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2

How to avoid bias

Sampling method or by increasing the sample size

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3

How to collect data

Questionnaires

Interviews

Observations

Surveys

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4

Mean

Total number of all values divided by the number of values

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5

Median

The middle value

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6

Mode

The most common value

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7

Range

The difference between the highest and lowest value

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8

Interquartile range

Upper quartile - lower quartile

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9

Ways to represent quantitive data

Table, bar chart, scatter graph etc

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10

Representing qualitative data

Use a pie chart etc

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11

Examples of bias in surveys

Voluntary response sampling- People have chosen to take the survey

Response bias - The wording makes people not want to answer truthfully

Convenience sampling - the first people to show up

Non response - people don’t reply so their pov is missed

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12

Non random sampling

Voluntary: asking people to do a survey

Convince: Sampling the first people to show up

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13

Pros of grouped data

  • Makes the data easier to read and understand

  • Easier to spot patterns and compare data

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14

Cons of grouped data

  • Lose accuracy of the data as you no longer know the exact values

  • Calculations made from these will only be an estimate

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15

Laboratory experiments

  • Researcher has full control of the variables

  • Easy to replicate

  • People may react differently to normal under test conditions

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16

Field experiments

  • Carried out in an everyday environment

  • Researcher has some control of the variables

  • Not easy to replicate and it’s hard to control extraneous variables

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17

Natural experiments

  • Carried out in the everyday environment

  • Researcher has no/little control of the variable

  • Reflects real life behaviour

  • Low validity due to little control of the variables and it’s difficult to replicate

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18

Frequency density equation

Frequency density = Frequency/ class width

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19

Types of misleading diagrams

  • Pictograms - same symbol and size need to be used for all the diagrams and a key is needed

  • 3d charts - Distort part of the diagram making it difficult to read the values

  • Colours - Some colours make part of the diagram stand out more, making it seem more important

  • Lines drawn too thick make it difficult to read information

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20

Axes and scales that can be misleading

  • A scale that does not start at zero

  • Missing values on the scales

  • Axes that are unevenly scales

  • Axes that are not labelled

  • Not using a key

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21

Bivariate

Involves measuring two variables

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22

Multivariate

Made up of two or more variables

eg: comparing height, weight, age and shoe size together

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23

cluster sampling

The population is put into random groups, one group is randomly selected and everyone in the group is asked

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24

Census

Collects information from all members of a population

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25

Lower class boundary

The smallest number in the class

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26

Pilot study

A pilot study is a small scale study that is conducted to inform, predict and direct an intended future scale study

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27

Opinion scale

An opinion scale lets people express their feelings on a numbered scale

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28

How to calculate an index number

Current price divided by base year price then x100

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