Teaching Idea: Graphing Regional Statistics (6-8)


Students will learn statistical and graphical methods for comparing data between population groups.

Time requirements:
Preparation: 20 minutes
In-class: 50 minutes

Materials:
CultureGrams World Edition—Data Tables

Sierra Leone’s real GDP per capita is $806, while Luxembourg’s is $60,228. Five per 1,000 infants die yearly in New Zealand compared to 79 in Pakistan. Statistics, though they don’t tell the whole story about a country, offer helpful tools for tracking demographic and economic trends while comparing countries and regions.

1.    Discuss which statistics are used to measure a nation’s demographics and economy and why. You might talk about infant mortality, literacy, and life expectancy rates along with Real GDP per capita. Explain the types of deductions that can be made from these statistics; for example, high infant mortality rates indicate that pregnant women receive poor health care. Also mention that statistics can be misleading. For instance, some oil-rich nations have high Real GDPs per capita, but most of their population is poor due to grossly unequal wealth distribution. For the most part, however, these types of statistics provide a valuable way of comparing countries.

2.    Choose a pair of statistics to focus on (for example, literacy and life expectancy). Have the students use the sortable data tables to look up these statistics for some of the sub-regions (i.e. Central Africa, South America, etc.) of the world.

3.    Then, have students create averages from the statistics found in these regional data tables .From these averages, assign students to draw three histograms. The first should be a comparison of, for example, regional literacy rates; the second, regional life expectancy; and the third, a combination of both statistical averages.

4.    Have the students compare and contrast the first two histograms they made. Do they share a similar pattern? Discuss the third histogram. Does there seem to by any correlation between the two statistics they analyzed? If so, what might be the cause of such a relationship? Might it be coincidental, and if so, what other factors might affect literacy, life expectation, or the stats you chose?

5.    For a more in-depth comparison, have the students create a scatterplot of all the country statistics, identify and eliminate countries that are extreme outliers, and recalculate the regional averages. They would turn in these averages with an explanation of how much the outliers affected the overall statistical picture.

Questions for further discussion:

1.    How can different graphical representations of statistics influence people’s perception of data? Which type of representation would most emphasize the differences between the regional averages found? Which one would minimize that difference? (You can discuss histograms, scatterplots, graphs, pie charts, etc.)

Discuss regional trends noted in the activity. What types of factors might cause them? Talk about whether they are geographic, historic, political, etc.

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