Univariate Data

Not to be confused with Bivariate data

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In mathematics, univariate data is a form of stress release for mathamatitions, where by the collection of data can be used to make pretty little pictures and alledgly, show some sort of information (in most cases the pictures are pornographic and lead to another form of stress relief).

Collecting data

The first, and perhaps most important part of this unique art form is to collect some sort of data that (in theory) will tell someone some information about something. Common examples are;

• The amount of people the CEO of CBS has slept with
• The amount of cases of deep vain thrombosis that have occurred from people playing cricket
• Number of red cars that are driving on a black road
• Number of carrots a person can launch out of their slingshot at once

It is important to collect at least a weeks worth of data (1 year for the CEO example) in order to make sure that the picture looks, you know, nice.

Identifying the data

For some unknown reason (usually to shut mathamatitions up)

“Oi!”

~ Mathematics on that last comment

you need to place your data into a category before you can start drawing the picture (note that the category must be identified accuratly and that the category you pick will dictate what you can draw... go figure).

There are 2 types of data: numerical and catergorical.

Numerical Data (number data)

Numerical Discrete data

This is when your 'data' is in whole numbers... except for when it's in shoe sizes because for some reason, thats considered a whole number, because it measures your whole foot.

Continuous data

This can be used when you have data that has lots of decimals, but this is rarely used, since rounding is frowned upon and nobody likes dealing with numbers such as 9.955739386758348939483475583925852047502758.

Categorical data (word data)

Nominal

This is when your data has no apparent order (very common), or when your data is about a nominated Prime Minister or President.

Ordinal

When the data has some sort of order (rare) or when the data is about an order you made at McDonalds.

Displaying the data (aka drawing)

Once this is all sorted out, you can now start drawing your picture. There are 5 different graphs drawings you can make, however the most common are;

• Frequency Histograms with polygons
• Box Plots
• Stem and Leaf plots.

Statistics show that 90% of people thought that this was written in French so if you cannot understand it, then you're not alone.

Frequency Histograms with polygons

A bridge using a frequency histogram + polygon

This is the most common drawing you'll see. It can also be used to draw city scapes. You may remove the histogram and leave the polygon (for the slow people: remove the bars and keep the line) to draw your heart rate (this technology is used everyday in hospitals)

Box Plots

Look, it doesn't take a genius to work these out, you draw them to make pictures of boxes or cats.

Stem and leaf plot

One of the finer examples of a stem and leaf plot

Clearly one of the more pretty forms of displaying data, it can be used to draw trees, flowers and tell you if the person who drew is colour blind.

See also

• Telemarketing