SOCR EduMaterials Activities PieChart

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==Background ==
==Background ==
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When comparing groups of data, Bar Charts are one of the best approaches for single category data analysis. Interpreting bar charts are not difficult as observers clearly look for the tallest bar, shortest bar, growth or shrinking of bars over time, comparison of bars, and change in bars representing the same category in different classes since bar charts are a type of visual data presentation.
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From the many different types of charts available, Pie Charts are most useful for illustrating percentages of a greater whole. Each section of the pie charts represents data from a specific category within the whole pie that creates the total data.
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Although Bar Charts are simple, it is easily abused as users use inconsistent scales, unequal classes, and varying intervals between classes. Still, Bar Charts offer useful statistical data such as mean, maximum, minimum, range,  sample size, and standard deviation.
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Since Pie Charts provide a clear visualization of the data set, it is easy to grasp the purpose and classification of the presented values.
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For more references, go to [http://en.wikipedia.org/wiki/Pie_chart Wikipedia], [http://www.mathleague.com/help/data/data.htm How to use Pie Charts], [http://nces.ed.gov/nceskids/createagraph/ How to Create Pie Charts].
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==Goals==
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* To show the important of Pie Charts
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* Display the daily application of SOCR Pie Charts
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* Ensure understanding of utilizing the SOCR Charts demonstrations
== Description ==
== Description ==
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Go to the SOCR Charts and select Bar Charts from the items located on the left. Then select Category Plot:
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Go to the [http://socr.ucla.edu/htmls/SOCR_Charts.html SOCR Charts] and select '''Pie Charts''' from the items located on the left. Then select one of the different types of Pie Charts according to your data format and the Chart look-and-feel you desire:
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507.jpg|400px]]</center>
<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507.jpg|400px]]</center>
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By selecting the first nine sets of demo under this category, these images simply demonstrate how bar charts may vary in sizes, classes, shapes, dimensions, and direction as Bar Charts may be presented vertically and horizontally:
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This image of a Pie Chart illustrates the proportions of the data set by a clear 3D visualization.
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By selecting the other demonstrations under [http://socr.ucla.edu/htmls/SOCR_Charts.html Pie Charts], notice that any set of data may be more eye appealing by allowing the data to rotate, applying different colors, or even display the images as a Ring Chart:
<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig2.jpg|400px]]</center>
<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig2.jpg|400px]]</center>
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig2.jpg|400px]]</center>
 
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The next three demonstrates how Bar Charts may be more eye appealing as they can be presented in 3-dimensions:
 
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig4.jpg|400px]]</center>
 
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The following two demonstrations show that Bar Charts may also have layering classes in which researchers may easily show that one of their main goals is to show how one set of data may be compared for every interval:
 
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig5.jpg|400px]]</center>
 
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The next four demonstrations show how Bar Charts may be stack upon one another also in comparison of data. Layering and stacking bar charts are similar but have some differences in which stacking is clearly for data that cannot be repeated so that all of the bars may be observed. As for layering, some data may be almost equal to another set of data so that when layering the bars, all data may still be seen on the independent variable axis:
 
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig6.jpg|400px]]</center>
 
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The Statistical Bar Chart adopts the characteristics of a typical Bar Chart except that it illustrates mean and standard deviation as well:
 
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig7.jpg|400px]]</center>
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==Data Type and Format==
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There are two different types of data spreadsheet formats/types that are allowed for plotting Pie-Charts. In both cases, one needs to provide two columns - one of a [http://mathworld.wolfram.com/CategoricalVariable.html categorical variable] (e.g., Name) and one of a [http://onlinestatbook.com/glossary/quantitative_variable.html quantitative variable] (numerical value associated with the name in first column). The different between these is the presence of an additional column in the second case (Pullout Flag), which indicates whether the (name, value) pair on this row will be plotted as a pulled out slice in the Pie Chart.
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Finally, the Waterfall Bar Chart is a unique way to present a Bar Chart that summarizes all data in one bar chart. Each bar chart builds from the previous bar chart to the last set of data, then one bar chart is created at the end to show the total or sum of the data:
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<center>[[Image:SOCR_Activitites_PieCharts_Dinov_090707_Fig4.jpg|300px]]
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[[Image:SOCR_Activitites_PieCharts_Dinov_090707_Fig3.jpg|300px]]</center>
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<center>[[Image:SOCR_Activitites_PieCharts_Chui_090507_Fig8.jpg|400px]]</center>
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==Example (Lake contamination and Mercury in Fish)==
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Create a Pie chart using the Alkalinity measurements in the first 10 Lakes listed in the [[NISER_081107_ID_Data#Data_Table | Lake contamination and Mercury in Bass Dataset]]. Copy the first 10 rows of this data table.
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<center>[[Image:SOCR_Activitites_PieCharts_Dinov_020807_Fig5.jpg|500px]]</center>
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Paste these 10 rows in the [http://socr.ucla.edu/htmls/SOCR_Charts.html SOCR Pie Chart] under the data tab.
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<center>[[Image:SOCR_Activitites_PieCharts_Dinov_020807_Fig6.jpg|500px]]</center>
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Them Map Lake to Name and Alkalinity to Value (in the Mapping Tab).
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<center>[[Image:SOCR_Activitites_PieCharts_Dinov_020807_Fig7.jpg|500px]]</center>
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Click UPDATE_CHART to see the Pie Chart illustrating the relative levels of Alkalinity in the 10 lakes. You can repeat this with more lakes or with any of the other variables (e.g., pH). Notice the large deviation in Alkalinity levels between lakes (e.g., compare lakes Apopka and Annie).
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<center>[[Image:SOCR_Activitites_PieCharts_Dinov_020807_Fig8.jpg|500px]]</center>
== Applications ==
== Applications ==
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One of the most persuasive elements when proposing data and literature to others is a well-designed chart presentation. For example, students have the ability to display their outcome of a Statistics project by utilizing the Pie Chart as a reference of proportions in the total data set.
One of the most persuasive elements when proposing data and literature to others is a well-designed chart presentation. For example, students have the ability to display their outcome of a Statistics project by utilizing the Pie Chart as a reference of proportions in the total data set.
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For industries, Pie Charts will give them the advantage of organizing their income of different types of products in a more appealing approach that is easy to project their research.
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For industries, Pie Charts will give them the advantage of organizing their income of different types of products sold to consumers.
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{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_EduMaterials_Activities_BallotExperiment}}
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{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_EduMaterials_Activities_PieCharts}}

Current revision as of 13:51, 3 May 2008

Contents

PIE CHARTS

Background

From the many different types of charts available, Pie Charts are most useful for illustrating percentages of a greater whole. Each section of the pie charts represents data from a specific category within the whole pie that creates the total data.

Since Pie Charts provide a clear visualization of the data set, it is easy to grasp the purpose and classification of the presented values.

For more references, go to Wikipedia, How to use Pie Charts, How to Create Pie Charts.

Goals

  • To show the important of Pie Charts
  • Display the daily application of SOCR Pie Charts
  • Ensure understanding of utilizing the SOCR Charts demonstrations

Description

Go to the SOCR Charts and select Pie Charts from the items located on the left. Then select one of the different types of Pie Charts according to your data format and the Chart look-and-feel you desire:

This image of a Pie Chart illustrates the proportions of the data set by a clear 3D visualization.

By selecting the other demonstrations under Pie Charts, notice that any set of data may be more eye appealing by allowing the data to rotate, applying different colors, or even display the images as a Ring Chart:

Data Type and Format

There are two different types of data spreadsheet formats/types that are allowed for plotting Pie-Charts. In both cases, one needs to provide two columns - one of a categorical variable (e.g., Name) and one of a quantitative variable (numerical value associated with the name in first column). The different between these is the presence of an additional column in the second case (Pullout Flag), which indicates whether the (name, value) pair on this row will be plotted as a pulled out slice in the Pie Chart.

Example (Lake contamination and Mercury in Fish)

Create a Pie chart using the Alkalinity measurements in the first 10 Lakes listed in the Lake contamination and Mercury in Bass Dataset. Copy the first 10 rows of this data table.

Paste these 10 rows in the SOCR Pie Chart under the data tab.

Them Map Lake to Name and Alkalinity to Value (in the Mapping Tab).

Click UPDATE_CHART to see the Pie Chart illustrating the relative levels of Alkalinity in the 10 lakes. You can repeat this with more lakes or with any of the other variables (e.g., pH). Notice the large deviation in Alkalinity levels between lakes (e.g., compare lakes Apopka and Annie).

Applications

One of the most persuasive elements when proposing data and literature to others is a well-designed chart presentation. For example, students have the ability to display their outcome of a Statistics project by utilizing the Pie Chart as a reference of proportions in the total data set.

For industries, Pie Charts will give them the advantage of organizing their income of different types of products sold to consumers.



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