Working with Data

The Data Analysis lesson is designed to introduce learners to how archaeologists (and other researchers) use data to answer their research question(s) and how they present their data in research papers and presentations. Youth will use real data that they have collected from their own research/experiments to make charts and graphs and begin to interpret data for their final project.

Grade Level: 6-8

Objective: The goal of this lesson is to have learners explore how to work with data (e.g., counts and weights of artifacts) by using archaeological data to create charts and graphs as well as basic descriptive statistics (means, medians, modes) that they will then interpret in relation to their hypotheses or research questions.

Learning Outcomes: Learners will be able to state why presenting data in graphic form is important and the various types of graphs/charts available, particularly ones appropriate to their data. Learners will be able to use a computer program to create their charts and graphs.

STEM: Math

Materials: pencils, artifacts, rulers, calipers, Excel computer program or Google Sheets

Time: 60 minutes

Overview: Archaeologists use large amounts of data to analyze the artifacts and features they find at archaeological sites. These include counts, weights, and linear measurements on stone tools and pottery, numbers of features and their volumes, and types of sites across a landscape. It is important to be able to understand how to use the data that is collected to help answer research questions. Finding measures of central tendency including means (averages), medians (middle number), modes (most frequent), and ranges is useful information for comparing samples and testing hypotheses. This can be done in Excel or Google Sheets. The data can be presented in many ways: tables, charts, graphs.

Vocabulary: data, mean, median, mode, calipers

Procedure: Have learners work with archaeological data (or pictures, replicas, or 3D printed images; please do not purchase artifacts). Give learners a bag of artifacts or objects to classify and identify. Have learners sort artifacts into types and make graphs/charts of the number of items in each type.. Discuss which graph/chart is best for representing different types of data. Explain how to enter data into Excel or Google Sheets and how to make charts and graphs from the data in the program. Make sure all figures have a title and that each axis is labeled. Have learners present their graphs to the group. Note differences in how data was presented between learners. Work with learners to determine what types of data they will need to answer the research questions they defined in previous weeks.

Extensions: Find the volume of soil removed from a unit (Volume=length x width x height). For example, the volume of soil from a 1 x 1 m unit that is 1 m deep is 1 cubic meter.

Assessment activities: Determine if each group was successful in creating appropriate graphs and charts in Excel or Google Sheets and how well they could explain their results to all learners. They will also begin to plan how they will analyze and present data for their research project.

Wrap up: Ask learners why presenting data in graphic form is important; what types of data are best represented with a bar or line graph vs a pie chart. Ask groups to describe how they will present their research data for their final project.

Crosscutting Concepts: Patterns, graphs, charts, and images can be used to identify patterns in data.

NYS Standards: -NY-6.SP Statistics and Probability.

Develop understanding of statistical variability.

  1. Understand that a set of quantitative data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape.
  2. Recognize that a measure of center for a quantitative data set summarizes all of its values with a single number while a measure of variation describes how its values vary with a single number.

Summarize and describe distributions.

4. Display quantitative data in plots on a number line, including dot plots, and histograms.