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# Need help with scatter graph watch

1. I have some government statistics I would like to lay out on a scatter graph to show a correlation between welfare spending and shoplifting over time (2006-2016). However, I'm hopeless at maths and advanced graphs, so I don't know how to exactly plot this data. I'm not too sure if I should add the years, it seems incorrect without them. The X and Y-axis represent the shoplifting and welfare statistics.
2. (Original post by IrnBruMan)
I have some government statistics I would like to lay out on a scatter graph to show a correlation between welfare spending and shoplifting over time (2006-2016). However, I'm hopeless at maths and advanced graphs, so I don't know how to exactly plot this data. I'm not too sure if I should add the years, it seems incorrect without them. The X and Y-axis represent the shoplifting and welfare statistics.
Could you clarify the data you have? What are these 'welfare statistics' and how are you measuring 'shoplifting'?

It would be helpful if you could provide a data table - can be with made-up data under the same headings if you don't want to share the data
3. (Original post by kingaaran)
Could you clarify the data you have? What are these 'welfare statistics' and how are you measuring 'shoplifting'?

It would be helpful if you could provide a data table - can be with made-up data under the same headings if you don't want to share the data
I'm measuring welfare spent in each year from 2006 to 2015 (I lack data for 2016) in terms of how much percent of the overall government expenditure of that year it consisted of (i.e £2 billion in 2006 of an overall expenditure of, say £100 billion, so 2% of overall expenditure). I can't show it in actual values because then the data would be incorrect as the overall expenditure has increased over the years.

In terms of shoplifting, I'm measuring it by how many recorded cases there were in each year.

From looking at the data, each year, apart from in 2013, when welfare decreased, shoplifting increased. And when welfare increased or remained the same, shoplifting decreased. That's a negative correlation is it not but the graph I made is showing a positive one. I think it might have to do with the values.

Here's the data, it's all available to the public anyway so I don't mind sharing it:

2006: shoplifting - 28,247, welfare - 7.4% of total expenditure that year.
2007: shoplifting - 28,750, welfare - 7.3%.
2008: shoplifting - 29,186, welfare - 7%.
2009: shoplifting - 32,048, welfare - 6.7%.
2010: shoplifting - 30,332, welfare - 6.7%.
2011: shoplifting - 29,660, welfare - 6.7%.
2012: shoplifting - 29,758, welfare - 6.3%.
2013: shoplifting - 26,449, welfare - 6.3% (actually decreased but small enough for there to be no percentage change).
2014: shoplifting - 27,693, welfare - 6.1%.
2015: shoplifting - 27,364, welfare - 6.2%.
2016: shoplifting - 28,424, welfare - no data, though doesn't matter.
4. (Original post by IrnBruMan)
I'm measuring welfare spent in each year from 2006 to 2015 (I lack data for 2016) in terms of how much percent of the overall government expenditure of that year it consisted of (i.e £2 billion in 2006 of an overall expenditure of, say £100 billion, so 2% of overall expenditure). I can't show it in actual values because then the data would be incorrect as the overall expenditure has increased over the years.

In terms of shoplifting, I'm measuring it by how many recorded cases there were in each year.

From looking at the data, each year, apart from in 2013, when welfare decreased, shoplifting increased. And when welfare increased or remained the same, shoplifting decreased. That's a negative correlation is it not but the graph I made is showing a positive one. I think it might have to do with the values.

Here's the data, it's all available to the public anyway so I don't mind sharing it:

2006: shoplifting - 28,247, welfare - 7.4% of total expenditure that year.
2007: shoplifting - 28,750, welfare - 7.3%.
2008: shoplifting - 29,186, welfare - 7%.
2009: shoplifting - 32,048, welfare - 6.7%.
2010: shoplifting - 30,332, welfare - 6.7%.
2011: shoplifting - 29,660, welfare - 6.7%.
2012: shoplifting - 29,758, welfare - 6.3%.
2013: shoplifting - 26,449, welfare - 6.3% (actually decreased but small enough for there to be no percentage change).
2014: shoplifting - 27,693, welfare - 6.1%.
2015: shoplifting - 27,364, welfare - 6.2%.
2016: shoplifting - 28,424, welfare - no data, though doesn't matter.
I think you could plot the years on your horizontal axis and have two vertical axis (on the same graph), one with the number of cases and one with the percentage of expenditure (use a different scale for each). That can help bring out the comparison a bit more and allows you to cover everything that you want?
5. (Original post by kingaaran)
I think you could plot the years on your horizontal axis and have two vertical axis (on the same graph), one with the number of cases and one with the percentage of expenditure (use a different scale for each). That can help bring out the comparison a bit more and allows you to cover everything that you want?
Thank you.

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