1. Stage 4:
Description,
Analysis and
Interpretation

2. Primary Data
Environmental Quality Assessment
Describe and justify how you used measurements of Central Tendency
(averages) to analyse your data.
 Using Excel measurements of mean and median Environmental Quality
Scores were calculated (see next slide)
These measurement provide a typical Environmental Quality Score value
for each location and can be used as an initial comparison point

3. Outer Suburbs - Quinton Inner Suburbs - Ladywood
Measurement Value Measurement Value
Mean 9 Mean -18
Median 7 Median -18
What did the results of these measurements show?
The average Environmental Quality Scores for Quinton are positive, between 7
(median) and 9 (mean) indicating that perceptions of this area are above
average, whilst the average score for Ladywood is negative, -18 (both mean and
median) indicating that this area is perceived to have an environmental quality
much lower than average.

4. Describe and Justify the use of Inter-Quartile Range (IQR) data
Qunton LQ 4
Ladywoood UQ -12
 By comparing the level of overlap between the Inter-Quartile Range (IQR)
for the Quinton and Ladywood data it is possible to determine if a
significant difference exists. (see next slide)

5. • As the upper quartile for Ladywood’s Environmental Quality Score is below the
lower quartile for Quinton, it can be said that a significant difference exists between
the perceived environmental quality of the two areas. Quinton has a significantly
higher environmental quality than Ladywood
What did the overlap of the IQR for different data sets show?

6. Describe and Justify the use of the Mann Whitney U Test.
 A Mann Whitney U Test will determine to a level of confidence
(95%,99% or 99.9%) whether there is a significant difference between
the Environmental Quality Scores for Quinton and Ladywood.
What did the results of this show?
• Using Minitab the results for this test are displayed below:
Mann-Whitney Test and CI: Quinton EQA, Ladywood EQA
N Median
Quinton EQA 48 7.000
Ladywood EQA 48 -17.500
Point estimate for ETA1-ETA2 is 26.000
95.0 Percent CI for ETA1-ETA2 is (23.000,30.000)
W = 3475.5
Test of ETA1 = ETA2 vs ETA1 > ETA2 is significant at 0.0000
The test is significant at 0.0000 This is the ‘p’ value.
See next slide for interpretation of ‘p’
values

7. p value Interpretation
>0.05 The result of the test is not significant
<0.05 With greater than 95% confidence the result is significant
<0.01 With greater than 99% confidence the result is significant
<0.001 With greater than 99.9% confidence the result is significant
• Therefore it can be said that with greater than 99.9% confidence, the
Environmental Quality Scores for Quinton are significantly higher than
those for Ladywood.

8. Census Data
Summarise what the bar charts showed in terms of socio-economic indicators?
• For all of the indicators of wealth
- Owner Occupied
- 2 or more cars
- Employed
- Mngmnt/ Prof occupations
Quinton has a higher % than
Ladywood and in most cases the
average for Birmingham
• For all of the indicators of deprivation
- Social rented
- 0 cars
- Unemployed
- No Qualifications
Ladywood has a higher % than Quinton
and in most cases the average for
Birmingham

9. Police Crime Data
Describe and justify how you used measurements of Central Tendency ( averages) to analyse your data.
What did the results of these measurements show?
Describe and Justify the use of Inter-Quartile Range (IQR) data.
What did the overlap of the IQR for different data sets show?
Describe and Justify the use of the Mann Whitney U Test.
What did the results of this show?
YOU need to do this bit on your own!!
Use Minitab to complete the Mann Whitney U Test –
see next slides for help
Great!
I love doing statistics

13. Step 4.
Phew !
Another section
complete