We usually create charts to make a point or communicate a specific message.
Sometimes we need charts just to provide a visual support for our claims.
For example, you will find people seeing the sales are increasing at 10 percent along with the budget,
or that the jobs in this industry are exploding while using charts to compare different fields.
You must have heard people communicating these kind of messages using charts.
The important point here is that there should be a message from your chart without a message.
Your chart will just be a picture dump into a presentation slide.
And in today's world, with abundance of easy techniques to create charts, we are encountering more
cases of random, irrelevant data just dumped into the charts without any message or relevant outcome.
After completing this course, I'm sure that you will be able to avoid such instances and will be able
to point out random data dumps from the impactful and meaningful graphs.
So let's start with our topic of communicating a message from a attack we first need to assign a category
to the message that we are going to communicate out of several categories that we have.
And later on in this course, we will learn how to choose the best type, depending on the underlying
message category.
So let's look at these categories first.
The first category is when we want to compare one item to another item, for example, a chart may compare
sales in each of the companies sales regions.
So we may want to compare the sales performance in the north region versus this old region, second
is comparing data over time.
For example, a chart may display sales by month and indicate the trend over time.
Stories making relative comparisons, an example of this is a common pie chart, which we see during
election results.
The pie charts display the percentage of votes or the seats won by the different parties in the election
scenario, the type of messages comparing data relationships.
We may want to explore the relationship between two variables a common example of a relationship between
variables marketing, expenditure versus sales.
So you may want to see if increasing the marketing expenditure is increasing your sales or not.
The fifth category is frequency convergence, a common example of frequency comparison can be a histogram
displaying how many students have scored between 80 to 100, how many have scored between 60 to 80,
and how many of them have scored below 60.
The last category that we are going to talk about is identifying outliers and unusual situations.
If you have thousands of data points, creating a chart may help identify those data points which are
not representative.
That is data points which are recorded or miscalculated or having some issue with them.
For example, if you are manufacturing tennis balls of certain radius, you can plot the radius of all
the manufactured balls over a chart to easily find all the only manufactured balls which are having
different dimensions.
I hope with this you will be able to assign your message to one of these categories.
Take some time to identify the last chart that you drew in your job and try to assign the message that
you communicated in that chart into one of these categories.
Think about it for the next five seconds.
In the next lecture, we will look at different elements of charts so that we can start a journey of
different types.