# SOCR EduMaterials Activities AreaCharts

### From Socr

## Contents |

## SOCR Area Charts Activity

## Summary

This activity describes the construction of the area chart in SOCR. The applets can be accessed at SOCR Charts. For more references: Wikipedia, Percent Area Charts, Area Charts.

## Goals

The aims of this activity are to:

- show the importance of the area chart
- illustrate how to use SOCR to construct an area chart

## Background & Motivation

Area Charts show related data groups. Each group adopts a different value of area in which the sum of all the groups equal to the total area of the data set or 100% of the data. Area charts is similar to a combination of Pie Charts and Bar Charts in which it implies the proportion of each group with two variables of a chart.

## Examples

Go to the SOCR Charts and select *Area Charts* from the items located on the left. A demonstration of an area chart will be displayed with four tabs above. Select **DATA** and enter in data of a desired experiment such as student's individual test scores during a semester. By selecting the **MAPPING** button, it allows the user to set any variable as independent or dependent. Once all entries have been inputted, the area chart referring to the data set will appear under **GRAPH**.

**Example 1**: Suppose the temperature has been recorded every hour during the week. Create an area chart and display each day as a different area in the graph.

**Example 2**: Consider an insurance company that wants to illustrate the number of accidents for every situation such as drinking and driving, talking on the cellphone while driving, changing the radio station, etc. You are given the data. Create an area chart pertaining this information.

## Data Type and Format

By clicking **Data** inbetween the *Graph* and *Mapping* button, it allows users to input or vary the values of the data set. There are two different types of data that is allowed for plotting data points which are one categorical variable (e.g., Series) and the remaining values as quantitative variables (numerical values). Below these values list the statistical values for each categorical value as demonstrated in the following image:

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