2.5 Examination Question Answers -
Examination Assignment 2.1
(Skills: graphical skills, scatter graphs, best fit lines, handling data)
1)What is the meaning of the term infant mortality rate?
The number of deaths of children under one year of age [1 mark] per 1000 live births in a year [1 mark]
(2 marks)
2)Using the data in Figure 2.28 construct a scatter graph (below) to show the relationship between per capita GDP (gross domestic product) and infant mortality rate.
(5 marks)
Exam hint
Make sure you label the axes and place the independent and dependent variables on the correct axes!
3)Draw in a best-fit line to show the trend of the data. Circle any anomalies.
(2 marks)
A scatter graph to show the relationship between per capita GDP and infant mortality rate
4)Explain how you drew the best-fit line.
Equal number of points on either side of the line [1 mark]
Mean points taken for per capita GDP and IMR [1 mark] and intersection plotted [1 mark]
Line should be drawn through that point [1 mark]
(3 marks)
5)What conclusions can you draw from the completed scatter graph?
Generally as GDP increases then infant mortality decreases [2 marks]
There are some exceptions/anomalies to this trend – India has a very high infant mortality rate of nearly 35 despite a high per capita GDP, Belarus has a low IMR but a low per capita GDP [2 marks]
(4 marks)
6)Describe the advantages of using the scatter graph as a means of analysing data.
Scatter graphs provide a good visual impression of the distribution/trends of the data [1 mark]
It is easy to identify anomalies/variations from the data [1 mark]
Relatively easy to construct in order to be able to see a pattern [1 mark]
Prediction is possible from the graph [1 mark]
(4 marks)
7)Describe the factors that influence infant mortality rates in countries at different stages of development.
Level 1(1–3 marks) / One or two factors described but description is weak and lacking in detail – health, medicine, no/little mention of different stages of development (e.g. Africa given)
Level 2
(4–5 marks) / Several factors described and good detail given, as well as reference to different stages of development, different country names – UK acceptable for an MEDC (low IMR), Nigeria for an LEDC (high IMR)
Appreciation of the importance of sanitation – how poor sanitation can lead to digestive disorders such as dysentery and gastro-enteritis and poor diet can lead to poor nutrition, description of how improvements in sanitation and diet can reduce the infant mortality rate, the importance of access to clean water, as well as access to doctors and medicine, better answers might even include AIDS (in Zimbabwe) causing high IMR
(5 marks)
`(Total marks = 25)
Examination Assignment 2.2
1)Complete the Spearman Rank correlation table (Figure 2.28).
Figure 2.28 Infant Mortality/Per Capita GDP *(2007)
Country / per capitaGDP (US$) / Rank / Infant mortality rate / Rank / d / D
Canada / 38200 / 1 / 4.6 / 11 / -10 / 100
Belarus / 10000 / 10.5 / 6.6 / 8 / 2.5 / 6.25
Sweden / 36900 / 2 / 2.8 / 14 / -12 / 144
N. Zealand / 27300 / 6 / 5.7 / 9 / -3 / 9
France / 33800 / 4 / 3.4 / 13 / -9 / 81
U.K. / 35300 / 3 / 5.0 / 10 / -7 / 49
India / 27000 / 7 / 34.6 / 1 / 6 / 36
Spain / 33700 / 5 / 4.3 / 12 / -7 / 49
Poland / 16200 / 8 / 7.1 / 7 / 1 / 1
Philippines / 3300 / 14 / 22.1 / 5 / 9 / 81
Egypt / 5400 / 13 / 29.5 / 2 / 11 / 121
Romania / 10000 / 10.5 / 24.6 / 4 / 6.5 / 42.25
Brazil / 9700 / 12 / 27.6 / 3 / 9 / 81
Russia / 14600 / 9 / 11.1 / 6 / 3 / 9
d2 / = 809.5
*per capita GDP (or Gross Domestic Product) means the average income per person
(6 marks)
2)Use the following formula to calculate the Spearman Rank Correlation coefficient (rs) between per capita GDP and infant mortality.
Spearman Rank (rs) = 1 - 6d2
n3-n
1 - 4857
2730
1 – 1.779 = -0.78 (2 decimal places)
(2 marks)
3)State the Null Hypothesis (Ho).
There is no relationship between per capita GDP and infant mortality rate
(1 mark)
4)Using the correlation graph (Figure 50) give the level of significance of your results. Can you accept or reject the Null Hypothesis (Ho)?
1% significance level [1 mark]
Only one chance in 100 that there is no correlation between the two data sets [1 mark]
Can reject the Null Hypothesis [1 mark]
5)What conclusions can be drawn from your results and what are the reasons for them?
Level 1(1–4 marks) / Conclusions are weak and there are no reasons given or reasons for the correlation are unclear, there may be no reference made to the actual data.
Level 2
(5–7 marks) / Good conclusions are given based on the data, clear reasons are given for the correlation, there is an appreciation of anomalies in the data.
Conclusions include a clear statement that the higher the per capita GDP – the lower the IMR, there is a 99% certainty of this correlation (highest level of correlation), and only 1 chance in 100 that this is not true, all of the MEDCs have low IMRs and a high GNP. However, there are some anomalies, in particular India has a relatively high GNP but has the highest IMR.
Reasons could include access to good health and sanitation in MEDCs, as well as a diet with plenty of nutrition.
(7 marks)
Exam hint
Remember that correlation can be either positive or negative. Both are equally valid as long as the trend is obvious or the coefficient is significant. The coefficient can only vary between +1 and -1 (if your coefficient is larger that this then go back and check your calculations!)
6)Assess the strengths and weaknesses of the Spearman rank correlation test for analysing data.
Strengths (1 mark for each)
Accurate statistical technique
Can be used to compare different pairs of items
Uses different significance levels to see the degree of association
Weaknesses (1 mark for each)
One or two anomalies could affect the result as they are included in the coefficient
Can’t see any anomalies in the data
Very small scale/little range in the coefficient (-1 to +1)
(6 marks)
(Total marks = 25)