This worksheet encourages users to apply their knowledge and understanding of sampling methods in a practical setting. It also shows how unwise it is usually to rely on our impressions of data, when a simple random sample can produce an unbiased statistical measurement. Users are asked to determine the (mean) average life expectancy of the data set of countries provided, using a variety of techniques.

What you need to do is as folllows:

1. Below is a pictogram showing the life expectancy rates for a selection of countries. This selection represents all the major global regions and includes countries which are rated by the UN as being at either high, medium or low levels of development.
2. Each of the 40 countries is represented by its national flag, which is accompanied by the life expectancy rate in that country in 1998.
3. Your task is, firstly, to estimate the mean average of the forty countries' life expectancy rates, by taking a representative sample of 10 countries. Select 10 countries and then submit your selection using the button provided. The mean of the 10 countries' life expectancy rates will be calculated.
4. At the same time ten countries will be chosen at random and the mean life expectancy of these 10 countries' calculated.
5. Make some notes on the differences between the two figures.
6. The true mean of the 40 countries' life expectancies will also be calculated and displayed.
7. Which of your two methods gave the best estimate?
8. How accurate was your sampling outcome and how much spread was there around the correct value?

1. Canada: 79.1	11. Costa Rica: 76.2	21. S. Africa: 53.2	31. Bhutan: 61.2
2. Australia: 78.3	12. Croatia: 72.8	22. El Salvador: 69.4	32. Laos: 53.7
3. UK: 77.3	13. Lithuania: 70.2	23. Indonesia: 65.6	33. Bangladesh: 58.6
4. Rep. Of Korea: 72.6	14. Mexico: 72.3	24. Namibia: 50.1	34. Haiti: 54.0
5. Barbados: 76.5	15. Cuba: 75.8	25. Egypt: 66.7	35. Congo: 51.2
6. Kuwait: 76.1	16. Russian Fed.: 66.7	26. Iraq: 63.8	36. Zambia: 40.5
7. Chile: 75.1	17. Colombia: 70.7	27. Ghana: 60.4	37. Malawi: 39.5
8. Slovakia: 73.1	18. Brazil: 67.0	28. Zimbabwe: 43.5	38. Mozambique: 43.8
9. Hungary: 71.1	19. Saudi Arabia: 71.7	29. Pakistan: 64.4	39. Ethiopia: 43.4
10. Estonia: 69.0	20. China: 70.1	30. Cambodia: 53.5	40. Sierra Leone: 37.9

Explaining the United Nations' Human Development Programme indices

Since its first publication in 1990, the United Nations' Human Development (UNDP) report has produced several indices to reflect and measure different aspects of human development.

The Human Development Index, (HDI), which has been produced ever since the inception of the report, measures average performance in basic human development and produces a ranking of countries. Built into the HDI are indicators of longevity, knowledge and standard of living.

In 1995 two new indices were introduced, the Gender-related Development Index (GDI) and Gender Empowerment Measure (GEM): the GDI adds to the HDI an indication of gender inequality in each country; the GEM measures gender inequality in economic and political opportunities.

In 1997, measuring human poverty was facilitated through the Human Poverty Index.

For the most recent (at time of writing) downloadable version of the UNDP report, go to http://www.undp.org/publications/annualreport2006/index.shtml

Some points are important to remember when you are reading the data included in the data set here. Firstly, most of these forty countries do not occupy the same HDI ranking as shown in the Excel country list. Some are in their HDI ranks, for instance Canada is in first position and Sierra Leone is in last place, but last position in the HDI is number 174 in the full HDI.

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