Example Excel Activities

Initial Publication Date: December 21, 2006

Level I Activities

The Level I activities assume no prior knowledge of the spreadsheet environment and focus on fairly basic skills of labels and numbers, equation entry, formatting, and graphing using Microsoft Excel. Different formulas related to science content are used as a central theme for each tutorial. If you have students work through several of these activities for the science content they can easily skip through the introductory parts.

Level II Activities

Level II activities assume a moderate familiarity with the spreadsheet environment and assume that students have worked through one of the Level I activities. They emphasize science content more than the Level I activities below but also help students learn how to use Excel to import and graph data from text files, and then to compare data to model predictions. Some of these activities are designed as sequels to the level I activities of similar name (as in Sea Floor Spreading I & II).

  • US Historical Climate: Excel Statistical
    Students import US Historical Climate Network mean temperature data into Excel. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates.
  • Planck Radiation Laws: Excel; Mac or PC
    Students use an existing Excel workbook to investigate how spectral irradiance from a blackbody radiator depends on temperature, Excel Mac or PC
  • Sea Floor Spreading II
    Students import ocean bathymetry data from text files, they then use Excel to graph these observations along with model prediction to assess the model's ability to simulated the observed.
  • Vostok Ice Core: Excel (Mac or PC)
    Students use Excel to graph and analyze Vostok ice core data (160,000 years of Ice core data from Vostok Station). Data includes ice age, ice depth, carbon dioxide, methane, dust, and deuterium.
  • World Population Activity II:Excel
    Students import UNEP World population data/projections, graph this data, and then compare it to the mathematical model of logistic growth.