# Bar Graphs

A

**Bar Graph**(also called Bar Chart) is a graphical display of data using bars of different heights.Imagine you just did a survey of your friends to find which kind of movie they liked best:

Table: Favourite Type of Movie | ||||

Comedy | Action | Romance | Drama | SciFi |
---|---|---|---|---|

4 | 5 | 6 | 1 | 4 |

We can show that on a bar graph like this:

It is a really good way to show relative sizes: we can see which types of movie are most liked, and which are least liked, at a glance.

We can use bar graphs to show the relative sizes of many things, such as what type of car people have, how many customers a shop has on different days and so on.

You can create graphs like that using our Data Graphs (Bar, Line, Dot, Pie, Histogram) page.

## Histograms vs Bar Graphs

# Histograms

**Histogram**: a graphical display of data using bars of different heights.

It is similar to a Bar Chart, but a histogram groups numbers into

**ranges**.The height of each bar shows how many fall into each range.

And you decide what ranges to use!

Notice that the horizontal axis is continuous like a number line:

The range of each bar is also called the

**Class Interval**In the example above each class interval is

**0.5**Histograms are a great way to show results of continuous data, such as:

- weight
- height
- how much time
- etc.

But when the data is in

**categories**(such as Country or Favourite Movie), we should use a Bar Chart.## Frequency Histogram

A Frequency Histogram is a special graph that uses vertical columns to show frequencies (how many times each score occurs):

Here I have added up how often 1 occurs (2 times), how often 2 occurs (5 times), etc, and shown them as a histogram. |

Bar Graphs are good when your data is in

**categories**(such as “Comedy”, “Drama”, etc).But when you have continuous data

**(such as a person’s height) then use a Histogram.**It is best to leave gaps between the bars of a Bar Graph, so it doesn’t look like a Histogram.

# Pie Chart

**Pie Chart**: a special chart that uses “pie slices” to show relative sizes of data.

Imagine you survey your friends to find the kind of movie they like best:

Table: Favourite Type of Movie | ||||

Comedy | Action | Romance | Drama | SciFi |
---|---|---|---|---|

4 | 5 | 6 | 1 | 4 |

You can show the data by this Pie Chart:

It is a really good way to show relative sizes: it is easy to see which movie types are most liked, and which are least liked, at a glance.

You can create graphs like that using our Data Graphs (Bar, Line and Pie) page.

Or you can make them yourself …

## How to Make Them Yourself

First, put your data into a table (like above), then add up all the values to get a total:

Table: Favourite Type of Movie | |||||

Comedy | Action | Romance | Drama | SciFi | TOTAL |
---|---|---|---|---|---|

4 | 5 | 6 | 1 | 4 | 20 |

Next, divide each value by the total and multiply by 100 to get a percent:

Comedy | Action | Romance | Drama | SciFi | TOTAL |
---|---|---|---|---|---|

4 | 5 | 6 | 1 | 4 | 20 |

4/20 = 20% | 5/20 = 25% | 6/20 = 30% | 1/20 = 5% | 4/20 = 20% | 100% |

Now to figure out how many degrees for each “pie slice” (correctly called a sector).

A Full Circle has

**360 degrees**, so we do this calculation:Comedy | Action | Romance | Drama | SciFi | TOTAL |
---|---|---|---|---|---|

4 | 5 | 6 | 1 | 4 | 20 |

20% | 25% | 30% | 5% | 20% | 100% |

4/20 × 360° = 72° | 5/20 × 360° = 90° | 6/20 × 360° = 108° | 1/20 × 360° = 18° | 4/20 × 360° = 72° | 360° |

Now you are ready to start drawing!

Draw a circle.

Then use your protractor to measure the degrees of each sector.

Here I show the first sector …

Finish up by colouring each sector and giving it a label like “

**Comedy: 4 (20%)**“, etc.(And don’t forget a title!)

## Another Example

You can use pie charts to show the relative sizes of many things, such as:

- what type of car people have,
- how many customers a shop has on different days and so on.
- how popular are different breeds of dogs