SOCR EduMaterials Activities BarCharts CategoryPlot

From SOCR
Revision as of 16:50, 5 September 2007 by PriscillaChui (talk | contribs) (Description)
Jump to: navigation, search

BAR CHARTS

CATEGORY PLOT

Background

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.

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.

Description

Go to the SOCR Charts and select Bar Charts from the items located on the left. Then select Category Plot:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig1.jpg

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:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig2.jpg
SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig3.jpg

The next three demonstrates how Bar Charts may be more eye appealing as they can be presented in 3-dimensions:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig4.jpg

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:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig5.jpg

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:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig6.jpg

The Statistical Bar Chart adopts the characteristics of a typical Bar Chart except that it illustrates mean and standard deviation as well:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig7.jpg

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:

SOCR Activitites BarCharts CategoryPlot Chui 090507 Fig8.jpg

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 on automobile prices by utilizing the Bar Chart as a reference to compare the class of prices among the data set of different companies of vehicles.

For industries, Bar Charts may be to their advantage for analyzing data as the Statistical Bar Chart will present the mean and standard deviation of the data.



Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif