This section focuses on interpreting statistics that show how places differ in their human and physical characteristics. The material presented is designed to help you meet the following objectives. 

It is easy to underestimate how often statistics crop up in our everyday lives. Most of us have been polled either online or over the phone about certain issues or political candidates. Business decisions often rely on statistical data, and marketers use statistics to push products. Statistical reasoning is, therefore, a skill students need in order to lead informed adult lives (Probability, 2004, p.6).

Much of geography involves perceiving relationships between systems, whether human or physical, and statistics are used in graphs and other visual representations to show spatial patterns and relationships. It follows that geography is a good place to start introducing statistical concepts in the elementary grades.

Geographers use both quantitative and qualitative data. Statistics would be an example of quantitative data—in other words, statistical data is measurable. For example, if a geographer is interested in the geographic influence on a social trend such as immigration, he or she can gather data on location (coordinates, zip codes, longitude and latitude) and data on migrations and international trade (Spence and Owens, 2011, p. 29).

"Data used in geographical research—human or physical—can be either from primary or secondary resources" (Spence and Owens, p. 34-5). Primary data is collected by the researcher, while secondary data is collected by someone else or a group such as a government agency. An example of this would be census data.

There is even a branch of geography called statistical geography, which "provides the extra dimension of location to statistics" (Statistical, 2012, par. 1). This type of geography uses a category called statistical areas that shows where data vary. Statistical geography also allows users to perceive relationships over time (Statistical, par. 2).

In studying statistical data, researchers look at variables: things that we can control, measure, and manipulate for study. Most statistical research that uses existing data is of the correlational variety. In this kind of research, there is no attempt to influence the variables, only to measure them and look for relationships. Finding a relationship between two or more variables gives meaning to some quantity or quality of those variables. The two most formal properties of any variables are the "size" or magnitude of the relationship and the reliability or truthfulness of the relationship. The latter refers to whether the relationship is representative of other such relationships.

Examples of things that might be measured statistically for differences would be population trends and migration patterns, food supply and hunger, and health and disease data.

Required Reading

For a review of the national geography standards related to the statistical study of geography, read "The Characteristics, Distribution, and Migration of Human Population on Earth's Surface" at the link below.

http://www.nationalgeographic.org/standards/national-geography-standards/9/

The Food and Agricultural Organization of the United Nations provides a frequently updated statistical database for approximately 210 countries. Areas of focus include agriculture, nutrition, forestry, food aid, land use, and population. To review some statistics on factors that account for differences in human and physical characteristics in places, click on the following link.

http://www.fao.org/faostat/en/#home

The World Health Organization provides a report on the status of world health each year, comprising annual statistical data about the health of people throughout the world.The 2020 report can be viewed at https://www.who.int/gho/publications/world_health_statistics/2020/en/. The type of data contained in this report gives statistical support for the measurement of quantitative differences in health and disease data in countries around the globe.