1. Stage 3:
Data
Refinement
and Display

2. Environmental Quality Assessment Data:
Tables of results
Describe and justify how the data collated/processed into tables?
 Data for 48 environmental quality assessment in both Quinton and
Ladywood were tabulated in order from highest to lowest scores (see
next slide)
Positives Negatives
Individual scores can be easily
identified
Difficult to see clear differences in
the data

3. Outer Suburbs - Quinton Inner Suburbs - Ladywood
Environmental Quality Score Data Sorted Environmental Quality Score Data Sorted
highest highest
25 7 -3 -19
23 7 -4 -19
20 7 -5 -19
20 7 -6 -19
19 6 -6 -20
19 6 -6 -20
18 6 -7 -21
16 5 -8 -21
16 4 -9 -22
16 4 -10 -23
15 4 -10 -24
14 4 -12 -25
13 4 -12 -25
13 3 -13 -25
12 3 -14 -25
12 2 -15 -26
10 2 -15 -26
10 1 -15 -28
10 0 -15 -28
10 0 -16 -29
10 -1 -16 -30
8 -1 -16 -31
8 -2 -16 -31
7 -6 -16 -36
lowest lowest

4. Environmental Quality Assessment Data:
Box Plots
Describe and justify how the data was represented graphically into Box
Plots.
48 EQA scores for Quinton and Ladywood used to create box plots:
Positives Negatives
Box plots can be use to determine if a
significant difference exists between
the two data sets by comparing the
level of overlap of the inter-quartile
ranges
Apart from the highest, lowest and
median value it is difficult to determine
precise data values from each data set

5. Photographs and Fieldwork Notes
Describe and justify how this data has been used and displayed
Photographs were annotated with field notes recorded at each location:
Litter on street
Many properties
are for student
rental
accommodation
Low level of property
maintenance
Properties lack
privacy
Positives Negatives
Annotated photos help to
justify the Environmental
Quality Assessment scores
Choice of annotations can be
subjective

6. Census Data
Describe and justify how the data was collated/processed into
tables?
 Data for 12 socio-economic Census indicators of wealth/deprivation for
2 LLSOA in both Quinton and Ladywood were tabulated (see next slide)
Positives Negatives
Individual scores can be easily
identified
Difficult to see clear differences in
the data

8. Data for 12 socio-economic Census indicators of wealth/deprivation for 2 LLSOA in both
Quinton and Ladywood were plotted in the form of bar charts. The average value for each
indicator in Birmingham was also plotted to provide a point of comparison. (see next slide)
Census Data
Describe and justify how the data was collated/processed into a bar chart?
Positives Negatives
• Enables a clear visual comparison
between the inner and outer areas of
Birmingham for each socio-economic
Census indicator
•Allows for a visual comparison with
the average value for Birmingham
Does not prove that there is a
significant difference between the
values for the inner and outer area

10. Police Crime Data
Describe and justify how the data collated/processed into tables?
Describe and justify how the data was represented graphically into Box Plots.
YOU need to do this bit on your own!!
Use Minitab to plot your box plots – see next
slides for help
I love Geography.
It’s just one fun activity
followed by another!!
Month of 2014 Quinton B32 1LB Ladywood B16 8RB
January
February
March
April
May
June
July
August
September
October
November
December