Bubble Graphsa special kind of Scatter Graph

Working with gym membership stats

City Population

(2016 estimate)

Number of

public gyms nearby

(within 5km)

Gym

Membership

(%)

Perth 47430 12 5

Edinburgh 512150 76 12

Dundee 158200 10 7

Aberdeen 214610 19 18

Stirling 49830 68 5

Greater Glasgow 985290 41 7

Inverness and

Culloden 63220 3 1

We use scatter graphs to try and spot relationships between things.

Every point on a scatter graph has 2 values associated with it.

A bubble graph is a special type of scatter graph which uses bubbles instead of

points.

It uses the size of the area of the bubble to show you a third value.

I would expect cities or areas with larger populations to have more gyms.

Here’s the data from the first two columns in that last table.

Local Population Size Gyms Nearby (within 5km)

47430 12

512150 76

158200 10

214610 19

49830 68

985290 41

63220 3

I’ve used it to plot a scatter graph of population size with the number of gyms.

0 200000 400000 600000 800000 1000000 12000000

10

20

30

40

50

60

70

80

Local population size vs gyms nearby (within 5 km)

Local Population size

Gym

s nea

rby

(<5

km)

When I look at this scatter graph, I’m not seeing what I expected.

It’s not true to say that the bigger the population, the more gyms you find nearby.

There’s a point on the top left which means small population but lots of gyms.

I decide to have a look at population size versus gym membership.

In the very first table population size was in the first column and gym membership

was in the third.

0 200000 400000 600000 800000 1000000 12000000

2

4

6

8

10

12

14

16

18

20

Local population size vs % gym membership

Local population size

% g

ym m

embe

rshi

p

I can’t see a clear correlation here either.

The area with the highest percentage gym membership has just over 20,000 people

living there (the highest point on the scatter graph) but there’s an area with a similar

population (just under 20,000) and it has a much lower percentage of people living in

it with gym membership.

There’s a third scatter graph I could plot to try and help me understand what’s going

on.

I could look at the number of gyms nearby (column 2) and see if there’s a correlation

with the % of the local population with gym membership.

I’m expecting that there might be. If there are lots of gyms in area – and they’re

managing to stay open – there must be a lot of people with gym memberships

paying to keep them open.

0 10 20 30 40 50 60 70 800

2

4

6

8

10

12

14

16

18

20

Number of gyms nearby (< 5 km) vs % gym membership

Number of gyms nearby (< 5 km)

% lo

cal p

opul

ation

with

gym

mem

bers

hip

Again, the correlation I’m expecting just isn’t there. The highest point represents an

area with just under 20 gyms but the highest % of folk with gym memberships (18%).

The point on the far right represents an area with nearly 80 gyms but the

membership is lower (12%).

These 3 scatter graphs let you use two values for each point.

In the original table you can see there are actually 3 values for each point.

Plotting a special kind of scatter graph called a bubble graph will let you use 3 values

for each point. It uses bubbles instead of points and the area of the bubble is used

to represent the third value. The bigger the area of the bubble, the bigger the third

value.

Here’s the data from the first table in a bubble graph.

0 200000 400000 600000 800000 1000000 12000000

10

20

30

40

50

60

70

80

Local population size vs number of gyms nearby(bubble area represents % gym membership)

Local population size

Num

ber o

g gy

ms n

earb

y (<

5 k

m)

It’s still not showing me an easy to spot correlation but there are things I can see

which might help me decide if there’s other information I might gather to help

understand the situation.

It depends on my motivation for doing this.

One of the main reasons we use data to draw graphs is because we are trying to

answer a question or make a decision.

Different organisations will have different motivations for looking into gym

membership.

We run a National Health Service on the basis that it is free for all at point of use (it’s

funded through taxation). It is expensive to run and folk who are physically healthy

and happier (or more contented) will not be as medically expensive to look after.

Local councils have been tasked with the long term goal of helping folk who live in

their area be more active. Research shows this has a positive effect on mental and

physical health.

A local council may be looking at how easy it is for folk to access a gym and how

many people are doing so in their area.

If I was working for Aberdeen Council, I’d be looking at the bubble for Aberdeen on

that bubble graph and be pleased. There are a lot of gyms compared to the size of

the population and a lot of folk have gym memberships.

A fitness business will be looking for opportunities to grow their business and make

money. Is there a location where they might open a new gym? Is there somewhere

with low gym membership where they could offer January sign up discounts?

Comparing the Glasgow and Edinburgh bubbles on the bubble graph I notice that

Glasgow has about twice the population but only half the number of gyms.

If I was working for a fitness business I might be looking at Glasgow as a possible

location for a new business.