3.3 Processing and analysing data Flashcards

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1
Q

How quantitative data is processed and analysed

A
  • quantitative data from close-ended questionnaires surveys are processed and analysed using
    1. Measures of frequency
    2. Measures of central tendency
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2
Q

Measures of frequency

A
  • we can use counts and percentages to measure frequency

Count:
- total number of times something occurs

Percentage:
- proportion of smth expressed as a fraction out of 100
- Data/Total Data x 100%

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3
Q

Measures of central tendency

A
  • Mean
  • Median
  • Mode
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4
Q

Measures of central tendency

A
  • Mean
  • Median
  • Mode
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5
Q

Mean

A
  • average average
  • sum of all values in data set divided by number of values
  • advantages: includes every value & no data is left out to show its central location
  • disadvantages: subjected to influence of outliers, which can skew it, & thus not provide central location
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6
Q

Median

A
  • middle average
  • middles value of a set of data that has been arranged in ascending order
  • advantage: less affected by outliers
  • disadvantages: not as sensitive as mean in showing central location in data set
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7
Q

Mode

A
  • not very average average
  • most frequent value in data set
  • advantages: Useful for categorical data like the different modes of transport and is not affected by outliers
  • disadvantage: Not very useful for continuous data because there may be 2 or more values that share same highest frequency
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8
Q

How qualitative data from mental maps be processed and analysed

A

Qualitative data from mental maps are processed to:
- verify how well they represent real world
- examine a mapper’s sense of place

Can analyse and process qualitative data by:
- analysing how well maps represent reality and how features and labels are drawn or added
- examine how memories of experiences are represented on maps and described during semi-structured interviews

Aspects of mental maps:
- centering and borders
- scale of map elements
- labelling
- colours, legends and symbols
- perspective orientation

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9
Q

Centering and borders

A
  • Features drawn at the centre capture attention, and might signal greater importance to the mapper compared with those drawn at the borders.
  • However, this may not represent reality. The positions of the different features drawn may not match reality.
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10
Q

Scale of map elements

A
  • Comparing the scale of different map features within the map and with reality can provide insights into a mapper’s familiarity and activity within the space
  • Larger features could indicate greater familiarity and more frequent activity done there.
  • However these may not represent reality. Larger features drawn by the mapper may be smaller than other features in reality.
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11
Q

Labelling

A
  • Labelled and annotated places indicate mappers’ familiarity.
  • The content and choice of words, positive or negative, used in labelling provide information on the mappers’ knowledge and emotions of the places experienced.
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12
Q

Colours, legends and symbols

A
  • Colours used in maps can differentiate places and convey emotions, like red representing anger.
  • A legend may be included to explain the symbols that the mapper uses.
  • Symbols like hearts and stars convey personal experiences or information about places, such as a favourite or an important location to the mapper.
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13
Q

Perspective and orientation

A

Mental maps may present different perspectives:
- Aerial view captures a large area with less details.
- Street view captures a small area with greater details.
Places are positioned or oriented in relation to the surroundings reveals the mapper’s experiences.
- A place that is important to the mapper could be depicted on the map as closer to their home.

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14
Q

Other features

A
  • Paths, nodes, or intersections, may be added to mental maps to show the mapper’s personal history of the places such as a route that was often taken.
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15
Q

What else can we do with mental maps

A
  • can compare actual maps with peeps’ mental maps to analyse the differences or inaccuracies portrayed
  • Drawn map features can appear as distortions, mislabellings and miscations. They are key in understanding factors that infuence mapper’s perceived space.
  • further verification can be made with the mapper through open-ended questions asked during semi-structured interview.
  • Duing the interview, the mapper may also be asked why some spaces are prominent and others are absent or ignored.
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16
Q

How may relationships and patterns be examined?

A
  1. from scatter plots and best-fit lines
  2. from recognisable geometric shapes, clusters and repetitions from data sets
17
Q

Relationships and patterns from scatter plots and best-fit lines

A
  • to determine if there is a relationship between 2 variables
  • basically, if best-fit line has +ve gradient, there is a positive correlation between the 2 variables
  • if both variables has negative correlation, best-fit line has a -ve gradient
  • there may be outliers that do not fit the pattern of the scatter plot
  • it’s important to examine causes of outliers & determine if they should be included in data analysis
  • if there is no observable relationship between both variables, like if all points are really scattered, best-fit line cannot be drawn
18
Q

Recognisable geometric shapes, clusters and repetitions

A
  • patterns and relationships can emerge by identifying recognisable geometric shapes, clusters and repetitions, and analysing diff similarities between them
  • common approach is to find what is common/ popular among peeps
  • repetition or clusters of labelings, geometric shapes or drawn features in mental map indicate popularity and prominence of places
  • their absence indicates unfamiliarity and lack of interactions within the space