# Unit 35 Laboratory Activity: Data Representation

## Goal: Learn now to represent data of different types so that patterns and trends are most visible.

#### Pre-Lab Preparation

Read through the examples and explanations at Visualizing Science Data. What are the advantages of data represented in

- Tables
- X-Y linear graphs
- bar charts
- maps
- pie charts
- surface maps

Are there some kinds of data that cannot be represented in each of these formats?

### Equipment and Materials:

- Paper and Pencil
- Spreadsheet program (if available)

### Procedure

- Choose
*one* of the hypotheses from the mastery exercise. You may use the experiment you chose for that assignment, or you may pick a different one. In your report, include the goals, equipment and materials, and procedures sections. For data, do the following:
- Generate some "dummy" data of the appropriate units and magnitudes, and use one of the above methods to represent it most effectively to show any trends, patterns, or periodicity. You may upload graphic files for this lab.
- Use one of the above methods to represent the dummy data most effectively to show any trends, patterns, or periodicity. You may upload graphic files for this lab.
- Write your formal conclusions based on your data. What data would you require to "prove" the opposite outcome to your hypothesis?

### Report

If you need some ideas about how to represent your data, see mycroft's example. Your fellow student used combinations of different string lengths (0.10m, 0.50m, 1.00m, 2.00m) and weights (0.25 lb, 0.50 lb, 1.0 lb, and 2.0 lb) and measured the time for a swing in seconds. He then plotted the time results as a function of weight vs. string length. His graph shows a slight curve, indicating that the appropriate formula describing pendulum periodicity involves an exponent (square, cube, square root) relationship.

© 2005 - 2021 This course is offered through Scholars Online, a non-profit organization supporting classical Christian education through online courses. Permission to copy course content (lessons and labs) for personal study is granted to students currently or formerly enrolled in the course through Scholars Online. Reproduction for any other purpose, without the express written consent of the author, is prohibited.