1. Essential Questions:  Which development indicators are most geographically informative?  What are different ways to display indicators of development?  What are the relationships between different development indicators?

2. What are Scatter Graphs?  Scatter graphs are an important type of graph used in geography to find or show a relationship between two sets of data or variables  They can be analyzed to show the extent to which two variables are correlated.  Eg: Is there a relationship between adult literacy levels and GDP?

3. What do you think we call this type of trend?

4.  Three possible outcomes exist when the data are plotted: 1. There may be a positive correlation: when higher magnitudes of one thing occur along with higher magnitudes of the other 2. There may be a negative, or inverse correlation when higher magnitudes of one thing lead to lower magnitudes of another 3. There may be not relationship at all

5. Activity: What type of correlation are these? We also use ‘high, low’ or ‘strong, moderate & weak’ to describe correlations

6. What can we say about a correlation?  To calculate and determine how strong a correlation is between two sets of variables we need to use a statistical test known as Spearman's Rank Correlation Coefficient.  When we do that we can see that it is easy to overstate the degree of correlation.

7. How do we interpret the correlation coefficient?  +1.00 shows a perfect positive correlation  -1.00 shows a perfect negative correlation  0.00 shows no correlation whatsoever, or complete statistical independence  Correlation is rarely perfect

8. Interpreting correlation coefficients: +0.81 and above = Very High Positive Correlation +0.71 to +0.80 = High Positive Correlation +0.51 to +0.70 = Moderate Positive Correlation +0.31 to +0.50 = Weak Positive Correlation +0.21 to +0.30 Very Weak Positive Correlation -0.20 to +0.20 = No Correlation -0.21 to -0.30 = Very Weak Negative Correlation -0.31 to -0.50 = Weak Negative Correlation -0.51 to -0.70 = Moderate Negative Correlation -0.71 to -0.80 = High Negative Correlation -0.81 and above = Very High Negative Correlation  USE THIS TO SHEET REPORT THE CORRELATION WHEN YOU DO THE ASSIGNMENT

9. Make sure the GNI is always on the x axis Make sure the GNI is always on the x axis GNP per capita (PPP) (USD) 2007%of labor Force employed in primary economic activity Plotting and labeling scatter graphs Y axis X axis Its also really important to have a well detailed title A scatter graph to show the correlation Between % of labor Force employed in primary economic activity and GNP per capita (PPP) (USD) 2007 The points represent the countries There should also Be a line of best fit

10. If we find a strong correlation does it mean the variables are influencing each other?  Many development indicators are not isolated, but inter-related parts of larger complexes of variables  We may therefore find a negative correlation between adult literacy and infant mortality, but find that they are in reality both jointly influenced by the level of economic development and are not actually influencing each other much at all  We can determine this by looking at the correlation of the variables in only the low-income countries, for example. We may find little or no correlation if the economic development of the countries is the same  That’s why it’s a good idea to have an economic indicator (in this case GNI (PPP) per capita as one of your indicators

11. Evidence of a correlation does not imply causation: (note the intentionally misleading X axis scale) Source: Church of the Flying Spaghetti Monster. http://www.venganza.org/about/open-letter/

12. Definition: Gross National Income (GNI)  Gross National Income (GNI) comprises the total value produced within a country (i.e. its Gross Domestic Product), together with its income received from other countries (notably interest and dividends), less similar payments made to other countries. Gross Domestic Product interestdividendsGross Domestic Product interestdividends  This is the main economic indicator on the from the prb.org site

13. Variables from the PRB website: