Lesson video

Hi everybody and welcome to today's lesson.

I'm Mrs. Brookes and today I'm gonna be talking to you about data collection and data presentation.

Now, I'm sure in lots of your other subjects and including your PE lessons, you have often looked at some data and how to collect that and also how to present it well.

But for today's lesson we're just gonna really hone in on those two skills and the terms linked to those skills so that we're fully prepared for the exam if we get questions around data.

So our outcome for the lesson is, we should be able to describe how data is collected and then look at some various methods to present and plot the data accurately to show what it needs to show.

Now, there are two main keywords we need to be aware of.

One of those is quantitative data.

And when we see that word, we need to be reminded that this is very much about a measurement or a quantity.

It very much is a fact, number, there's no opinion around it.

Now, in contrast, we also have qualitative data and we often look at that data as being subjective rather than being that objective or that quantity or that measure.

And that kind of data, because it's subjective, will involve opinions and those opinions will often be more based around the quality of something, such as a performance, rather than the quantity.

And everything we do throughout today's lesson will very much come back to those two types of data.

So we have two parts of the lesson.

The first one is where we describe those two terms and make sure we feel very confident in those descriptions.

And then we build on that and look at how we present certain types of data, whether that be in a table, in a bar chart, or a line graph.

So we are starting our lesson with Lucas.

And Lucas is telling us that as part of his PE class, he's been asked by his teacher to complete a survey on the hobbies and those activities that the students or the children do outside of school.

And this is because the teacher would like to collect data on how active or the amount of physical activity is done outside of the school environment.

And some of those children were also then asked to attend a five-minute interview where they could talk through the results of their survey.

So I really like that Lucas has shared that with us because he has basically described two methods of data collection, and we're gonna talk about those two methods in a bit more detail.

So we'll start first with that quantitative data.

So he said to us that he and others have been asked to do a survey or a questionnaire and that was basically providing a measurement, a fact about the amount of times they may do sport and physical activity at school or how long they're doing it for.

So you can see there's some really good examples of questions there from the survey such as, well, which sport do you take part in? Are there particular days of the week when that happens? When you are there, how long do you spend on that sport or that hobby? So you can see from that that's very much a quantity, it's a fact, it's an objective measure, 'cause the answers were very much numerically based.

And here's an example of exactly that.

Now, Lucas didn't tell us, but I can now share with you that he's in a class of 30 and therefore this table at the minute shows the sports or the hobbies that those children are doing outside of school.

You can see for yourself there we have a real breadth of activities, football, park run, skateboarding, yoga, boxing, dance, and cheerleading.

And underneath it shows the number of students that are involved in that activity.

Now, that can also be presented as a bar chart.

So you can see quite clearly there we have the sports and activities along the bottom and then we have the number of students up the side there.

And Alex is just reminding us, and thank you Alex, that when we are drawing a bar chart and if we get asked to do so, the bars on the chart need to be drawn with equal width.

So you can see there in that purple formatting, all those bars are of equal width for each sport.

So this is a good opportunity for us to just have our first checkpoint.

And we're being asked here, which of the following terms are associated with quantitative data? Is that A, facts, B, opinion, C, description, and D, numbers? I'll give you five seconds to decide.

Absolutely, well done.

It is actually A and D.

Both of those terms we would definitely associate with quantitative data, often because it's a numerical answer or response, and those numbers are objective and largely based around facts.

Remember though, Lucas said that following that quantitative data collection, there was also a second method being used and that was around qualitative data.

And that was because Lucas was saying that some of them would then have an interview.

Now, that interview would then be very much more subjective and those questions that were asked were a little bit more open-ended.

So the children, the students, were asked questions where they would be able to describe a bit more about the activity that they're involved in.

And you can see some examples there exactly of that.

So you know, they may be asked the way they could tell them more about what they do and what that involves.

Maybe asking why.

So why do they take part in that, you know, why do they enjoy it? Maybe asking to dig in a little bit more deeper and saying what's the real fun part you like? What's your favourite part? And we've got some examples of this 'cause Lucas attended that interview, and Lucas was one of the students that actually is involved in dance and he shares with us here that he's part of a street dance group or a street dance class.

And we can see here he goes on to kind of give more subjective opinion or description about what that means for him.

So he tells us that the sessions are all very different and it will really depend on the dance or the choreography that they're working on at that moment.

The part that he really likes is the opportunity that he gets to be creative and he's often spending time with friends and using different rhythms and different music and trying to bring that music to life.

And he really likes the free dance section where, as a group, they kinda almost battle with each other.

So we can see a really different picture here, rather than that kind of the table and the bar chart showing us the numbers and the facts, we get a real feel now for Lucas and his motivations and his enjoyment about the activity that he actually does outside school.

And the teacher wanted to collect that.

We'll really wanna see about those motivations and why those students are kind of wanting to take part in that activity.

And actually the teacher could go a little bit further than that if they wanted to find out more, and as part of that qualitative data collection, they could complete an observation, so actually go watch Lucas or be involved, you know, ask the dance teacher or the group to come in and do some taster sessions and they'd then get a real feel more so about what that involves and that subjectivity about taking part, in this instance, in street dance.

So we've looked at different ways of collecting data and for this checkpoint here, which of these is an example of a survey which is a method of collecting data? Is it image A, B, or C? Yes, well done.

We can see image A, it actually looks like someone using a pen and going through a paper-based survey in order to find out some facts and some numbers.

Not always on paper, you know, given the current trend in technology, a lot of these surveys can be online and there are lots of platforms that do this for us and you then submit on your device and then in the background, that's already presenting the data in a way such as a table or a graph.

But that particular image is just looking at that paper-based version.

Now, to make sure we're definitely feeling confident with this, another little checkpoint here, which of these comments from Lucas is describing quantitative data? So Lucas, for A, tells us that the bar chart showed 26% of the class taking part in football.

He then goes on to say that his friend participates in ballroom dancing and does state being able to compete, he likes the competition element, as a main part of his motivation to continue to do that.

And finally, the dancers in the class were on average training three times a week.

So which of those comments from Lucas are examples of quantitative data? Well done if you noticed that we've got two there, we've got both A and C, and that's because they're looking at those numbers, those facts that have come out from that survey method of data collection.

So to summarise, there are many ways of collecting data and the ones that we've learned about through Lucas are those questionnaires, those surveys, conducting that interview, and maybe doing that observation.

And these methods can collect both quantitative data, so where we get those numbers and those facts, and they can also, including the surveys, can get qualitative data.

So there's more open-ended questions where you might be asking for descriptions and opinions.

So to consolidate our learning, that's gonna bring us onto our first task.

There are three questions linked to this task and as you can see from the image there, that's very much designed around food choices and diet.

And we would like you to design four questions that you could ask in a survey to collect data about food choices in one day.

Now, there's only four questions, but we need those questions to collect both quantitative or qualitative data.

So could you really be creative in your question choice to see if you could capture those two types? And in doing so, the third part of the task is, can you link that to a description about the difference between those two types of data? Pause the recording and come back to me when you're done.

Welcome back everyone.

How did you do? Now, imagine the questions could be quite varied.

So these are just some examples of the kind of questions you could capture or pop in a survey, whether that's a paper-based one or one that takes place online.

Could be that you do ask how many pieces of fruit and veg they eat per day.

We know that is something that gets asked frequently, given the recommendation of five a day.

It could be if you are asking whether someone does make sure they eat breakfast, how much water are they consuming are also something that can be quite pivotal to avoid that state of dehydration.

And you can also see we've got a different question there for question four, in terms of, well, when you snack in the day, which is your favourite, and why is this? And we can see there that question one and three are real good examples of quantitative data 'cause they definitely deal with the numbers and the facts, is it a yes or is it four or is it two litres? But then question four is that slightly different one, isn't it? 'Cause you've got that qualitative data as it's very much asking the individual to describe their opinion on their favourite snack.

And beyond today, that could be something that you want to just ask yourself or maybe ask someone else to remind yourself of that quantitative and that qualitative data.

So now we feel confident with that.

Let's go onto the second part of the lesson where we're gonna talk more about that data presentation and we're gonna look at those three types, a table, a bar chart, we've seen some of that in that first part of the lesson, and also those line graphs.

Now, we're gonna continue to use Lucas as our example.

We know Lucas is a dancer and he continues to go on and tell us that as part of his training, he's been asked to do some fitness tests.

He's also been asked to collate some data on how active, how many minutes he's active in the session, and also his heart rate in one particular session.

So we've got some really good examples of the type of data that could be taken, in this instance, from an individual in that dance environment.

And as we said though, that's the really good thing, 'cause we can use that to practise our methods of how to present that data well.

The fitness tests he did complete were the vertical jump, so this has taken you back to some of that key learning about fitness test protocols.

We've got a nice little image there as a quick recap for you, the sit and reach test, and also that hand grip dynamometer.

So with that vertical jump test looking at power, sit and reach test looking at that kind of lower back and hamstring flexibility, and finally that hand grip dynamometer looking very much at that maximal or that static grip strength.

And here we have our first lot of quantitative results and they are presented really simply in a table by showing what the test is and the result with the correct units.

And as we can see there, that's really easy to read and it's very common that we would often see that kind of data, maybe with an additional column where you would then possibly compare Lucas to those norms for males from 15 to 16-year-old.

And that gives you some type of an insight as to where you are with that component of fitness, but actually really quite nice and easy to read.

On a similar level, we've also got here a table.

This has got a little bit more complexity to it, 'cause you can see we've got the weeks, we've got the sessions per week, and then the number of minutes that Lucas was actually active each session.

So you can kind of pick out the number of minutes in that session per week.

Now, I think this then starts to look slightly better in this format, 'cause that can be pottered, sorry, plotted onto a bar chart similar to like we saw in that first part of that lesson.

And Alex is reminding again that those bars are equal in width, but is also saying to us here, "What is missing from the bar chart?" We can see those equal, we can see those active minutes.

But well done if you realised, and this is quite crucial, 'cause we wouldn't want to avoid these in an exam question or we wouldn't want to ignore them, we need those labels, we need those titles of the axes.

So we can see there, on the x axis, as we refer to it, or the horizontal axis, we've got the dance sessions, so we can see there, there are six in total across the three weeks.

And then our green arrow there is pointing towards the time and that's on our y axis, or our vertical axis.

And that is the time that they were active.

And you can see there in brackets that it's really important they use the units.

So in this instance they were looking at number of minutes.

And I'm sure this is stuff you've done many, many, many times in maths or some of your other subjects.

So it's just now reminding you to make that transfer and make sure you include it in any kind of PE lesson or PE question where this is what is being asked of you.

So first checkpoint here, which of the following is the correct description of a bar chart? Is it A, B, C, or D? I'll give you five seconds to just check those options and decide on which one you think is correct.

Well done.

Drawn with equal width on the axis.

So in order to get our bars that are equal in width, we need those marks along the x axis to allow us to do so.

A similar question here, but this time we're gonna go true or false.

Bar charts in exam questions will have the x and y axes already labelled.

Do we think that's true or false? Well done if you identified that as false.

They can be left blank.

That could be the skill that's being checked.

And then you need to just be aware that, to access all those marks, both those axes need to be labelled correctly.

So you need to get that x axis, the horizontal one, correct and that y axis, and that will be the one that will often have some units.

There could be units on the x axis as well.

So make sure that we don't fall foul to that and then miss out on some of those key marks.

We've got some more quantitative data here from Lucas and this is now looking at heart rate.

So we can see here that the heart rate's been taken in five-minute intervals, just through one of the sessions in session five.

You can see it goes from 0 to 40 minutes and that heart rate is taken and the units have been included correctly in that little BP and M, which if you remember back to some of that key learning from paper one, that stands for beats per minute.

Now, in this instance that data could be put in a bar chart or it could be also demonstrated using a line graph.

So we can see here, there we've already got our blank graph and with our title, which is very clear that that's heart rate during a dance session.

What would our x and y axes be? Well done.

Your y axis is the heart rate and you can see there we've got that bpm in brackets, and that x axis is time, and also need the units, now in terms of minutes.

We can see that's a shortened version of minutes which we are aware of seeing often when we reference minutes in that way.

This might be an opportunity for you to pause the recording and you actually have a go at now plotting that line graph and you just need to be really careful that you'd make sure the right heart rate is plotted at the right timeframe.

And when you've got all that for those 40 minutes, you would then connect those plots or those points with a line.

And here's a little bit of a ta-da, this hopefully is what you have come up with and this is how it should look in terms of that plotted bits of quantitative data and how they've been connected.

And as Alex is sharing with us there, absolutely this is really showing, probably in a clearer way, how Lucas's heart rate had changed throughout the session.

And then from that we can then start to do a little bit of data analysis and understand why that heart rate was changing.

A nice little link there onto some future learning.

But for now, we are just gonna go onto our final task of the lesson and we're gonna reference this time, well, Lucas, but one of his classmates, and she's a skateboarder and she's also collected some quantitative data.

That data is based on the number of successful runs she had while skateboarding over a period of six sessions.

And we're also gonna look at some heart rate, a little bit like what we did with Lucas during one particular session.

So from that data, you are gonna have to draw a bar chart to show those successful runs and then plot a line graph to show the heart rate during one of those sessions.

And as Alex is about to remind us, we have to remember to label our axes correctly.

This is the data I would like you to use.

So again, you've got, there's a number of runs over those six sessions and then you've got that data, that heart rate, in session two, this was, out of those six.

Pause the recording, I know that's gonna take quite a little bit of time, and come back to me when you've got both of those graphs drawn.

Welcome back.

How did you guys do? So our first task was to draw our bar chart.

Hopefully you can now look at that one on the right there and compare it to yours, and I hope that you've got those bars of equal width.

And also, as you've got that little bit of checklist along the left there, is the labelled x axis correct? It's the skateboarding session.

Is that y axis correct? That number of runs.

And then is the bar chart hitting the right numbers taken from the table? And that's a really good skill that, once you've drawn it, you just go back and check that each bar is the right number by comparing it to the table.

And for the second part of the task, does your line graph look similar to this? We can see our title and our x and y axes again.

Quite rightly, the y axis has got the units, the BPM, and those points have been plotted and then connected as well as possible with a line.

So well done on completing both of those tasks.

In summary, we now know there are a number of methods of collecting data.

We talked about surveys, questionnaires, interviews, observations, and in that second part of the lesson, also that kind of testing and monitoring, 'cause that often will bring up some data that we need to then present.

Those methods might provide that quantitative data.

Remember that's numerical, it's objective, and it's really based on facts.

In contrast with our qualitative data, which is very much around subjectivity and involving those opinions and descriptions.

And then that quantitative data we've built into our learning there about how we represent that well in either a table, a bar chart, and a line graph.

And the most important message from this in summary is, are we giving ourselves opportunity to practise that and making sure that they are drawn correctly and those axes are labelled correctly or accurately, which then means if we ever get some questions on these, we'll do all of those skills as well as we can.

Thank you so much for joining me today.

I've really enjoyed talking through types of data and data presentation, and I look forward to seeing you on the next lesson.