Hook | Questions | Procedures | Data Investigation | Analysis | Findings | New Questions

Student Page


The student page contains the hook only. It is intended to spark interest in the topic and lead students to ask questions or make predictions.

We all know that summers usually mean warmer temperatures and winters mean cooler temperatures, but have you ever hear somebody say on a hot summer day, "I would love to go up to the mountains to get away from this heat."

Or maybe you've heard somebody else say on a cold winter day, "I would love to take a vacation down south so I could bask in the warm sun."

When temperature is the issue, what's the big deal about...

  • going up to the mountains?
  • going south for the winter?
Look at the following cities on a map.
  • Beijing, China
  • Cairo, Egypt
  • Vancouver, Canada
  • Quito, Ecuador
  • Melbourne, Australia
  • St. Petersburg, Russia
  • Honolulu, Hawaii
  • Mexico City, Mexico

How would you expect the temperatures of the following cities to vary? Why? Go to weather.com's averages and records and find the average yearly temperature for each city. Then look up each cities elevation and latitude at the Global Gazetteer.

  • Do you notice anything about each city's average temperature and their elevation and latitude?


Students might ask similar but different questions than those listed here. The more students are guided to ask specific questions, the less inquiry-oriented the activity.

Two factors, elevation and latitude, have been briefly introduced as potentially affecting a given city's average temperature. Students might list other factors as well. The point to this activity is to help students see patterns in temperatures around the world, namely that temperature can be determined by a locations elevation and latitude. Questions that would be pertinent to this activity are:

  • How are elevation and latitude correlated with a location's average temperature?
  • If you were given the elevation and latitude of a location, could you predict what that location's average temperature would be?

To predict temperatures for different locations, developing a mathematical equation from these relationships would be helpful, so you might also want to lead your students to ask:

  • What is an equation(s) that would predict temperatures for different locations?


After students have asked questions related to the topic, they will need to decide a number of things, including:

  • Type(s) of data needed to answer the questions
  • Defining important terms
  • Choosing tools for data manipulation
  • Defining how data will be manipulated and presented

Type(s) of Data

Average temperature data, either yearly, monthly, or seasonal, for many locations will be needed for this activity. Also, the elevation and latitude for each location will be needed.

Defining "Correlation"

This activity might be a good opportunity to introduce the concept of correlationto your students. Meriam-Webster.com defines correlation as a "relation existing between phenomena or things or between mathematical or statistical variables which tend to vary, be associated, or occur together in a way not expected on the basis of chance alone."

It might be helpful to use the word in a sentence, such as, "There is a correlation between smoking and lung cancer."

Defining "Regression" and "Trend Line"

This activity might also present an opportunity to introduce or futher expose students to regression and trend lines. It is likely that students will complete a linear regression on collected data (temperature vs. elevation and temperature vs. latitude). Since these might be foreign concepts to students, they might require some explanation.

Investigation Tool(s)

Students will be using numerical data. Both graphing calculators and spreadsheets will scatter plot data and then calculate trend lines and their equations. The example shown uses a spreadsheet.

Manipulating Data

To caculate trend lines, students will need to invidually scatter plot temperature vs. elevation and temperature vs. latitude (see Data Investigation).

When selecting locations for the elevation scatter plot, best results will be found when all the locations are relatively near each other but at different elevations. Countries such as Ecuador, Peru, India, Nepal, and Switzerland have cities with varying elevations.

When selecting locations for the latitude scatter plot, best results will be found when all locations are at or near the same elevation but at different latitudes.

Data Investigation

There is often a giant leap from defining the type(s) of data desired and actually finding the data. Providing guidance to students in finding the necessary data may be necessary.

To find average temperatures, elevation, and latitude, students will need to use web sites such as WorldClimate.com or WeatherBase.com. Temperature data for thousands of separate places can be found at these sites. Latitude, longitude, and elevation of these places are usually provided as well.


For this example, Ecuador was chosen as a country to seek the relationship between elevation and temperature. The country borders the Pacific Ocean and quickly rises into the Andes mountains, and as a result, Ecuador has cities with widely varying elevations. The CIA World Factbook might be a good place to find a map of the country showing its major cities.

CIA World Factbook Map


For this example, several North, Central, and South American cities were chosen. In order to eliminate elevation as a possible cause for variation in temperature, all cities chosen are relatively near sea level. A world map or globe might be helpful for students as they choose cities for this part of the investigation.. A


Raw data/information usually has to be manipulated before it can answer any questions. Students might be unaware of how data can best be manipulated, so teacher guidance may be appropriate.


  • Using a site such as WorldClimate.com or WeatherBase.com, monthly average temperatures and elevations are entered into Microsoft Excel for several Ecuadoran cities. A good sample of cities with varying elevations is needed. After all the data has been placed in the spreadsheet it should be sorted by elevation.
  • The Elevation and Temp columns are highlighted and then charted into a scatter plot.

  • To determine the correlation and the regression line, right click (PC) or CTRL-click (Mac) on any of the points on the chart. Select Add Trendline... Choose Linear under "Type."

  • Click on "Options" and check the Display equation on chart and Display R-squared value on chart boxes.

    In this example, the equation for determining temperature based on elevation is Temperature = -0.0026 (Elevation) + 77.177°F.

    For those interested, R^2 = 0.9634 is the correlation.


  • Monthly average temperatures and latitudes are entered into Microsoft Excel for several locations in North, Central, and South America. After all the data has been placed in the spreadsheet it should be sorted by latitude.

  • As in the Elevation example, a scatter plot is created,

  • Before a trend line is added it is sometimes helfpul to take a closs look at the scatter plot:
    • It appears that locations between 0°N and 20°N all have average temperatures near 80°F.
    • It appears locations between 20°N and 60°N are related, but...
    • a different relationship occurs for locations above 60°N.

  • To find the trendlines for these subsets, two new charts need to be created:

  • So we now have three important equations for cities at or near sea level:
    • For locations below 20 degrees north: Temperature = 80°F.
    • For locations between 20 and 60 degrees north: Temperature = -0.988 (latitude) + 96.827°F.
    • For locations above 60 degrees north: Temperature = -2.5826 (latitude) + 193.33°F


No result is meaningful unless communicated appropriately. Discussion of findings should be supported. There may or may not be definitive answers to the questions students raised.

In this example we produced four separate equations, one for elevation and three for latitude.


Actual results will vary depending on cities selected, as well as a variety of other factors.

  • Temperature = -0.0026 (Elevation in feet) + 77.177°F


Actual results will vary depending on cities selected, as well as a variety of other factors.

  • For locations below 20°N: Temperature = 80°F.
  • For locations between 20°N and 60°N: Temperature = -0.988 (latitude) + 96.827°F.
  • For locations above 60°N: Temperature = -2.5826 (latitude) + 193.33°F

Combining Equations

We cannot quite combine two equations together. For example, it will not work to create an equation Temperature = -0.0026 (Elevation) + 77.177 -0.988 (Latitude) + 96.827. By putting 0 in for elevation and 30 in for latitude, we would get:

  • Temperature = -0.0025 (0) +77.177 - 0.988 (30) + 96.827 = 144.36 °F!
    That's way to high
    . The problem is the adding of both 77.177 and 96.827.

We should first use one of the latitude equations to establish what the temperature of a city would be if it were located at sea level. We could then adjust this temperature for the city's elevation.

Consider the following examples.


Mexico City, Mexico

Mexico City is located at 19.4°N and is 7,329 feet above sea level. We'd start with the equation for locations below 20°N (the contant 80°F) and then adjust for elevation:

WorldClimate.com shows an that the average temperature of Mexico City is 60.8°F, so 60.9°F is very close.

Tahoe City, CA

For example, consider Tahoe City, California. Tahoe City is located at 39.2°N and is 6,227 feet above sea level. We would start with the latitude equation for locations between 20°N and 60°N Temperature and then adjust for elevation:

WorldClimate.com shows an that the average temperature of Tahoe City is 43.3°F, so again we're not far off in our prediction of 41.9°F.

Possible New Questions

Answers often lead to new questions, starting the inquiry cycle over again.

This activity might cause students to ask additional questions, such as:

  • We focused on locations north of the equator. Do the same rules apply south of the equator?
  • Are there places that have average temperatures that deviate significantly from what the equations predict? If so, why?
  • What is the role of seasons for various geographic regions in determining average temperatures?
  • How is rainfall effected by latitude, elevation, and other factors?

The following web sites might be helpful in helping students explore further how elevation, latitude, and also seasons are related to temperature:


Activity created by Philip Molebash

Based on an activity created by Thomas Draganski, Marcia Halpern, Thuc Ho, and Jennifer DeLuna