Lesson video

Hello, my name is Chloe and I'm a geography field studies tutor.

This lesson is called Field Work: Presenting survey data, and it forms part of the Geography: what makes a geographer? unit of work.

In this lesson, we're going to be looking at how we can present data in a manner that makes it more meaningful and makes it easier to analyse.

Let's get started.

By the end of this lesson, you will be able to present survey data using a range of data presentation techniques.

There are some key words for us to review first of all.

Let's look, first of all, at the term itself, data presentation.

This is the graphical way that data is shown to help the reader better understand it.

Spatial data is data that has a distinct location associated with it.

A bar chart is a form of data presentation where bars are drawn to represent the size of a piece of data, and a radial graph is a type of data presentation in which scaled data can be presented.

This lesson is in two parts.

First of all, we're going to be looking at how you can choose a data presentation technique, and then we're going to be looking at appropriate data presentation techniques for an environmental quality survey.

So here we are within our inquiry cycle.

We have an inquiry question and we have collected some data and we are now onto the stage of presenting it.

Data presentation is about understanding data as well as being able to draw different techniques.

So in terms of data presentation, what we need to do is think about why geographers present data, the types of data that geographers are working with, and then actually think about the techniques themselves, bar charts and radial graphs, as well as maps, are going to be covered in this lesson.

Raw data is data that has not been processed.

The data that has been recorded on an environmental quality survey used in the field is raw data.

Geographers present their raw data to make it easier to identify patterns and relationships.

While the end result of the presentation may be attractive to look at, this is not the purpose of data presentation.

It's all about allowing the data to shine so that we can see what it actually means.

So good data presentation uses a clear colour scheme, not one that is designed to look pretty.

It will have a scale and units clearly marked if necessary.

So in this case, I have a bar graph.

So yes, I do need to have a scale and I need to have units on my axes.

Every piece of data presentation will have an appropriate title.

Look carefully at how I have structured this particular title.

I have said "A bar chart to show environmental quality scores at site number 5." So I've said what the data presentation method is and what it intends to show.

Good data presentation will also allow the geographer to easily read and understand the data.

So true or false? Data presentation should focus on making the data attractive to the reader.

Is that true or false? Pause the video and have a think and then come back to me.

So is it all about making it attractive? No.

But why not? Well done if you recognise that the purpose of data presentation is to allow geographers to identify patterns and relationships in the data.

It is certainly not about making the data look pretty or attractive.

Data should be presented in a way that is appropriate for the type of data that's being handled and the relationship the geographer is trying to highlight.

For example, Laura is trying to show how noise levels vary across her town.

This is spatial data, so it's best presented using a map.

You can see here she's got a base map of her town and you've got the sites marked where she collected her noise levels, her decibel levels, and you can see she's then marked on the map the decibels at each particular site.

Other types of data presentation can only be used with certain types of data.

Discrete data can be placed into distinctive categories.

Here's an example of some discrete data.

Now this is data from a traffic count and it shows the different types of vehicles that were counted during the traffic count.

This means that presenting this data needs to show this separation between the categories.

So if discrete data is all about this idea of distinctiveness in the categories, the data itself needs to be presented so you can see that separation.

So if you look at this particular bar chart, you can see that the bars stand with a gap between them to show that the categories are distinctive.

So let's just have a little bit more of a thought about discrete data.

In this example, we've got a traffic count where we're looking at different types of vehicles.

This is discrete data because a car cannot be a bike and a lorry, it can only be a car, so it can only fit into one category, therefore it is discrete.

The data collected during an environmental quality survey is a series of scores.

So remember, we are scoring our environmental quality on a scale of one to five.

In this case, this means the data is discrete.

Only the values of one, two, three, four, or five could be chosen.

You couldn't, for example, choose for noise, a value of two and three.

It could only be one of those options.

As Sam says here, a site could not have a total score of both 16 and 20.

It can only be one type, so therefore it's discrete.

Let's check our understanding of that.

How might the type of data affect the data presentation method the geographer chooses? Is it A, some types of data are more reliable than others, B, the data presentation method needs to be large enough to include all the data, C, the type of data tells the geographer what the relationship is, or is it, D, some data presentation methods only work with certain types of data.

Pause the video and have a really close think about those different options and then come back to me.

Let's see what answer you chose.

Well done if you recognise that it was D.

Yes, some data presentation methods only work with certain types of data.

So that is how the type of data affects the data presentation method.

Our first task of this lesson: think carefully about your environmental quality survey data.

What do you want the data to show you? What type of data are you dealing with? And then by considering your answers to question one and two, what type of data presentation might be suitable? Now, don't worry if you don't know the precise names of any particular data presentation technique.

You can just describe them in terms that you do know.

So three tasks.

Think about your environmental quality survey data that you already have.

What do you want the data to show? What type of data is it? And therefore, what type of data presentation might you choose? This is gonna take a little bit of thought, so do pause the video, maybe have a chat with other people about what their ideas are and then come back to me.

Let's take a look at what your answers may have included.

First of all, I wanted you to think about what you wanted the data to actually show you, and, hopefully, you recognised that you wanted your environmental quality data to show you which area of the school site had the highest and lowest scores.

You then had to comment on what type of data you are dealing with.

Well done if you realised that your environmental quality data scores were from one to five and they covered six different locations where the data was collected.

Then, by considering your two answers, what type of data presentation might be suitable? Well, here's some ideas.

So the scores could be compared using a chart to show their values, or the scores could be shown on a map to show how the scores relate to different areas of the school site.

Yes, remember, you are dealing with spatial data, so a map would be suitable here.

Let's now move on to the second part of this lesson and look at appropriate data presentation techniques.

In terms of our data that we've got, environmental quality scores, we're going to be looking at bar charts, radial graphs, and maps.

Let's start with the bar charts.

So this is one way that we can show the scores quite easily.

The x axis shows the site numbers.

You can see them there, one, two, three, four, five, six.

While the y axis can show the value of the total scores, and they range from 5 to 25.

Now look at my site numbers there.

You can see the values for the total scores for each site, and the bars are the height according to those scores.

So at site number one, the total score was 15.

So you can see that my bar goes up to, on the y axis, goes up to the 15 value.

The taller the bar, the greater the environmental quality score.

So a very quick interpretation of this, I can see that site number four has the highest environmental quality score because it's the tallest bar.

Alternatively, a bar chart could be drawn individually for each of the survey sites.

So for my data, I got six survey sites.

I would need to draw six individual bar charts.

Here's one for site 1.

You can see now that my x axis, which before, had the different site numbers, now shows the different criteria.

The y axis still shows the scores, but instead of total score, it's now the individual scores for each of those criteria.

So instead of going from 5 to 25, they now go from one to five instead.

But the same principles apply in terms of how I draw it.

In my raw data chart, there, you can see that the criteria for smells has a score of five.

So on my bar chart, the bar rises up to the five value on the y axis.

Let's check our understanding.

Izzy has drawn this bar chart of her environmental survey data.

Oh dear.

But what mistakes has she made? Look carefully at it.

Is it that one bar is not the right height? Is it that that the y axis is not labelled? Is the scale too small? Or are the bars the wrong colour? Think very carefully.

Do pause the video and then I'll come back to you with the right answer.

Okay, what do you think? Well, well done if you recognise there's actually two right answers here.

Izzy has not labelled her y axis.

Yes, she's put the units on, she's given it a one to five, but we don't actually know what that one to five means.

We need to have an idea here that this is about the scores for her environmental quality survey.

And well done if you are eagle eyed and you recognise that one of the bars is not actually the right height, Let's check.

Noise is one, litter is four, views is, oh dear, views has actually been drawn so it's at the value of three when it should be of the value of two.

So that bar has not been drawn to the right height.

A more complex graph that we could use is a radial graph, and this uses a really unusual set of axes.

The number of y axes radiate out from a central point, so it looks like a bit of a, like a star kind of shape.

Each of these axes has a scale to suit the range of possible environmental quality scores.

So we know in our survey we're scoring from one to five.

So one, my scale here is closest to the centre and five is further out.

Each axis is labelled with environmental quality criteria.

So we've got noise, litter, views, smells, and maintenance.

So you can see each of those sit on each of those y axes.

The scores are then plotted on the axes themselves.

So you can see that noise has a score of one, litter, a score of four, views, a score of four, smells, five, and maintenance, two.

So you can see how those scores have been plotted on that particular, or for that particular site.

The points can then be joined together to form a polygon shape.

Now, that's actually really useful.

Let me show you how.

The size of the polygons can then be compared for the different sites.

So we've got them now, all six of our sites have been mapped out in terms of radial graphs, and you can see that actually they're very, very different shapes.

The larger the polygon, the higher the environmental quality at that site.

I can see instantly that site 4 has a much higher environmental quality than site 2 because this polygon shape is much bigger on site 4 than it is on site 2.

Let's check our understanding now.

On the radial graph for site 6, what score was given for maintenance? Is it one, two, three, four, or five? Remember, one is the ring that is closest to the centre and five is the one which is furthest out.

Check the graph carefully and then come back to me with the right answer.

So what do you think? Did you get it right? It's three.

So maintenance has a score of three.

Well done if you got that.

Our environmental quality data includes spatial data.

Remember, we had locations where the surveys actually took place.

So we know we are dealing with spatial data.

This means a map can be used to present this data, and I would strongly recommend that whenever you are dealing with spatial data, you try to use a map.

So what you could do is simply place the total scores for each survey site on the map itself.

So I've literally just written them on.

So you can see that 24, a score of 24 was down on the playing field.

As I get closer to the tennis courts there, or netball courts, we've got a score of 16.

So I can actually just see what the total score was for the different sites.

I could try and be a little bit more clever with my data presentation.

Here I've got circles, which have been sized proportionally to their environmental quality scores.

So you can see that the larger the circle, the larger the environmental quality total score was at that particular site.

Already I can start to see there's maybe a bit of a pattern happening here.

Is it the case that the smaller circles are closest to the school building? In other words, have I got low environmental quality close to the school building and better environmental quality as I move further away from it? Now, if I want to be really clever, I could take this step further.

Do you remember I drew those six different radial graphs, one for each site.

Maybe I could actually place those onto the map as well.

I now can compare the radial graphs with each other, but I can also compare the size of those polygons with the different features that are on the map.

Is it the case for example, that the area with the largest polygon is the one that's nearest to the woodland, or is the smallest one the one that's nearest to the road? I can start to see patterns developing between features and scores.

Let's check our understanding now.

Complete the sentences with the missing words.

You're gonna want to pause the video, have a read of the paragraph below, and then see if you can fill in those three missing words.

Then come back to me and I'll tell you the right answers.

Right.

Let's see what you got.

"Where a data set contains spatial data, geographers should use a map to present the data.

The map can show the total environmental quality scores, shapes that are proportional in size to the total score value or individual graphs layered onto the map in the right position." Our final practise task today.

So for this task, you can either produce a bar chart, a radial graph, or a map of your school site with the environmental quality score values on it.

There are some resources available to help you do this.

Make sure your data presentation includes all the elements of data presentation that make it both readable and correct as a map or a graph.

Now, you are gonna want to pause the video here, so do take your time over this.

Make sure that your data presentation is both accurate and that it follows the common conventions of that technique.

Now, of course, with the options available to you, there's going to be some variety in what your bar charts, radial graphs, or maps look like, but there are some common elements that you're going to want to make sure you have included.

Double check these with me.

Make sure you've included a title.

Make sure that your data is accurately plotted.

Is your data clear and easy to read? Make sure what you've labelled any axes that you are using with a title and units, this is if you are using a bar graph or a radial graph.

And if you've chosen to display your data using a map, make sure it includes a key.

Let's summarise our learning from today's lesson.

Geographers present data so they are able to see trends and patterns within it.

They choose techniques that are appropriate for the type of data and the conclusions they wish to make from it.

Environmental quality survey data is both discrete and spatial.

This means that presentation techniques such as bar charts, radial graphs, and maps can be used to present it.

Well done.

There were quite a variety of different data presentation techniques there for you to get your head around.

I must confess, data presentation is probably my favourite element of the field work inquiry.

It's just great when you start to see your data come to life on the page and you start to wonder whether your conclusions, your hypotheses, are going to be really meaningful.