1. + Mortality

2. + Starter for 10…. In pairs write on a post it note: One statistic that we use to measure mortality On another post it note write down: A country in the world that you would expect life expectancy to be increasing and why? A country in the world that you would expect life expectancy to be falling and why? Stick your post it notes on the board at the front

3. + Key Questions & Skills Key Questions What is the global picture of life expectancy? What factors influence longevity? What are the implications of an ageing population? Skills Graphical – Line graphs, scatter graphs Statistical – Spearman Rank Correlation Coefficient Choropleth maps

4. Draw a graph to display the figures on Table 1 Comment upon the trends evident in the table and the graph you have drawn.

5. Map 1: Global patterns of crude death rates Describe the patterns of Global Mortality in your own words, as revealed by maps 1 & 2

6. Map 2: Global patterns of Infant Mortality Rates

7. + Look at the following slides and clips. Write down the 5 things that most significantly impact on death rates.

11. ‘DAILY BREAD” – FORTIFICATION OF BREAD IN EGYPT http://www.gatesfoundation.org/livingpr oofproject/Pages/their-daily-bread.aspx

13. REINVENTING THE TOILET http://www.gatesfoundation.org/infograp hics/Pages/reinvent-the-toilet-info.aspx

15. VACCINES WORK http://www.gatesfoundation.org/infograp hics/Pages/infographics.aspx

16. + Factors that influence mortality D rinking water E ating well A ccess to immunisations T reatment of sewage H ealthcare Is there anything else?

17. + Increasing Life Expectancies Describe the patterns of global life expectancy shown on Map 3 Where would you expect life expectancy to be increasing, and why? In which regions of the world do you think that life expectancy is falling? Explain why.

19. + Longevity in the UK Expected further number of years of life at ages 50 and 65, United Kingdom

20. + Spearman Rank 1 The Spearman's Rank Correlation Coefficient is used to discover the strength of a link between two sets of data. Not only does this test highlight a relationship but it also indicates the strength and statistical significance of the relationship, if any You should always get a value between 1 and -1, if not then you have gone wrong somewhere! The closer to 1 the stronger the positive relationship, the closer to -1 the stronger the negative relationship. Remember you have to compare you result to the critical values to see whether or not the relationship is statistically significant enough to accept and use to formulate conclusions regarding variables investigated.

21. + Spearman Rank 2 Null Hypothesis: There will not be a relationship between the two variables (sets of data). Again, the easiest way to do this calculation is within a table. You need to rank each variable independently, giving 1 to the highest and so on. When you have two values that are the same you add together the places they would rank, then divide it by how many would rank there (e.g. if three values would rank 13, you add together 13, 14 and 15 and find the middle value which is 14 and assign each one 14), then skip the same number of ranks to ensure that the lowest ranking number is given the same number as n (number of values) Use the table to calculate the value of R²

23. + Spearman Rank Calculation

24. + Understanding the result This value doesn't mean much on its own. It must be looked up on a Spearman Rank significance Table. In our example, the value -0.9757 gives a significance level of better than 0.01. That means that the probability of the relationship you have found being a chance event is less than 1 in a 100. You are over 99% certain that your hypothesis is wrong. REMEMBER !!! The hypothesis states that the relationship you have been studying DOES NOT exist. If the hypothesis is wrong, then the relationship DOES EXIST.

25. + Interpreting Spearman’s Rank What does this R value of -0.97 mean? The closer R is to +1 or -1, the stronger the likely correlation. A perfect positive correlation is +1 and a perfect negative correlation is -1. The R value of -0.73 suggests a fairly strong negative relationship. A further technique is now required to test the significance of the relationship.

26. + The R value of -0.97 must be looked up on the Spearman Rank significance table below as follows: Work out the 'degrees of freedom' you need to use. This is the number of pairs in your sample minus 2 (n-2). In the example it is 12 (14 - 2). Now plot your result on the table. If it is below the line marked 5%, then it is possible your result was the product of chance and you must reject the hypothesis. If it is above the 0.1% significance level, then we can be 99.9% confident the correlation has not occurred by chance. If it is above 1%, but below 0.1%, you can say you are 99% confident. If it is above 5%, but below 1%, you can say you are 95% confident (i.e. statistically there is a 5% likelihood the result occurred by chance).

27. + The value -0.97 gives a significance level of slightly less than 0.1%. That means that the probability of the relationship you have found being a chance event is about 0.1 in a 100. You are 99.9% certain that your hypothesis is correct. The reliability of your sample can be stated in terms of how many researchers completing the same study as yours would obtain the same results: 99.9 out of 100. This means the relationship IS statistically significant.

28. + Finally… The fact two variables correlate cannot prove anything - only further research can actually prove that one thing affects the other, but it does suggest that the relationship is statistically significant. Data reliability is related to the size of the sample. The more data you collect, the more reliable your result.

29. + Give me 5! 5 measures of mortality 5 influences on the death rate 5 other facts from todays lesson? No cheating! Don't look at your books!

30. + Further Study Finish any outstanding work from todays lesson Complete the past paper questions from January 2010 Read the Geofile on Ageing populations – be ready to discuss this next time