1-4.1. Summarizing Data: Pie Charts

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From the course by University of Illinois at Urbana-Champaign

Exploring and Producing Data for Business Decision Making

230 ratings

University of Illinois at Urbana-Champaign

Exploring and Producing Data for Business Decision Making

230 ratings

Course 5 of 7 in the Specialization Managerial Economics and Business Analysis

This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. Specifically, you will be introduced to statistics and how to summarize data and learn concepts of frequency, normal distribution, statistical studies, sampling, and confidence intervals. While you will be introduced to some of the science of what is being taught, the focus will be on applying the methodologies. This will be accomplished through the use of Excel and data sets from many different disciplines, allowing you to see the use of statistics in very diverse settings. The course will focus not only on explaining these concepts, but also understanding the meaning of the results obtained. Upon successful completion of this course, you will be able to: • Summarize large data sets in graphical, tabular, and numerical forms. • Understand the significance of proper sampling and why you can rely on sample information. • Understand why normal distribution can be used in so many settings. • Use sample information to infer about the population with a certain level of confidence about the accuracy of the estimations. • Use Excel for statistical analysis. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.

From the lesson

Module 1: Introduction and Summarizing Data

Data is all around you, but what is the data telling you? The first step in making better decisions and taking action is to get a good understanding of information you have gathered. In this module we will learn about some of the tools in statistics that help us achieve this.

1-4.1. Summarizing Data: Pie Charts4:54

1-4.2. Pie Charts in Excel5:11

Meet the Instructors

Fataneh Taghaboni-Dutta
Clinical Professor of Business Administration
University of Illinois, Urbana-Champaign College of Business Department of Business Administration

In the last two lessons, you learned about frequency tables and

then we moved on to histograms.

In this lecture, we will learn about pie charts.

Pie charts are another excellent graphical summary tool for categorical data

where we can compare proportions for various categories very effectively.

So here is a fun fact about the Americans.

When asked what desserts Americans would prefer a friend or a family member

bring to their house for holiday dinner, pie was the winner with 29%,

cake had 17%, cookies 15%, which rounded out the top three spots.

And nearly one out of five, about 19% of Americans prefer apple pie,

followed by pumpkin pie at 13%, pecan at 12%, banana cream, 10% and cherry, 9%.

So now let's display this information with a pie chart.

This pie chart quickly communicates American desert preferences,

often that is the power of the picture versus spoken or written words.

Pie charts are very useful in comparing the relative sizes

of the categories to one another.

Also, the categories collectively represent all the possibilities.

Likewise, we can take the second finding, which is about one of the slices of

this graph, and create a second pie chart to illustrate this information.

Once again, you see the relative proportion of the different categories

to one another and together, they comprise all possible categories.

Now let's look at some graphs that I have developed using data from U.S. government.

I have looked at the exports from USA to China in 2015 and

have decided to display the results first using a column graph.

This graph shows the top ten exports based on their dollar values.

Looking at this one, one can see that high value dollar is in the aerospace sector,

followed by electric, machinery and so on.

Now let me display the same thing in a pie chart.

Here, the same data is displayed differently.

What do you see as pros and cons of each when I display them side by side?

Looking at the bar chart, you see the order of the top ten categories, and

you can see what is the value of each particular category.

For example, aerospace related exports for number one, for

the total value of approximately $14 billion.

On the other hand, looking at the pie chart, one can see that the five

export categories comprise three fourths of the total values.

These are broadly in the aerospace,

electric, nuclear, vehicle, seeds and seed oil industries.

The dollar values are not displayed, but

it is a quicker way of communicating the relationship of the top ten categories.

To decide which one to use, depends on what is it that you want to highlight and

communicate to others.

Now let's add an additional category to each graph.

This additional category will be used to represent the total value

of all the other exported material to China in 2015.

How will our graphs change?

So let me display this new graph side by side.

These are the graphs which have the top ten exports

plus the eleventh category to represent all the other exports.

Which one do you like better and why?

The pie chart in this case, provides a better visual display of the relationship

of the top ten categories to one another as well as to all the others.

Pie chart shows the top five is slightly more than half of all exports.

Pie charts are most useful when you want to compare

the relative sizes of the various categories to one another, and

when we want to know the relationship of all categories.

The bar chart is more useful when you want the actual values displayed,

and not as useful when we want to include all possibilities as was in this example.

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