Lesson video

Hello, everyone and thank you for joining me here on Oak National Academy once again.

My name is Mr. Ward, and as part of the unit in line graphs and timetables, today, we're going to be looking at both.

Tables of data and line graphs, and taking that information to plot and present the data in an appropriate manner.

Now I hope you are focused, you have all the equipment you need, and you're in a quiet space, where you can give your full attention to today's lesson.

When you're ready to begin, continue the video, because I can't wait to get started.

Hopefully you've had an opportunity to go back and watch some of the previous lessons in this unit that I have taught on line graphs and timetables.

But if you are new today, that's fantastic.

Welcome aboard.

I just got to share with you that in my lessons, Mr. Ward's lessons, I like to start the lesson, with a math joke to get a smile on your face.

Get a little bit of mathematical vocabulary, flowing, and also to put us in the mood for our learning.

And today's maths pun, is this.

I had a strong disagreement with a 90 degree angle yesterday.

Turns out it was right.

And if that doesn't put you in the mood for maths, nothing will.

if you have some work at the end of the lesson, or a mathematical joke that you would like to share with us here at Oak National Academy, we will be sharing the details of how to do that at the end of the lesson so please keep watching the video.

Just on your screen, you'll see a quick rundown of how the lesson will go today and the outline.

We'll just start with a new learning where we introduce the concept of the day, which will be interpreting medal graphs.

Then a go at talk task which we will do and discuss together but you can pause the video at that point, and reflect on the information that's on the screen and have a go independently if you choose to do so.

Then we're going to take our learning and develop it a little bit further by bringing in a additional element to our learning to deepen our understanding.

And then it's over to you.

You're going to have a go an independent task, in which you complete some incomplete tables and present the data in a line graph.

And then, as is custom for Oak National Academy, we'll end the lesson with a quiz.

And hopefully, it will give you the confidence to know that you've embedded a lot of the learning from today's lesson.

Before we start the lesson, it's always good to check that we've got all the equipment that we need.

Now in today's lesson, you are going to need a pencil, a ruler, and some paper or notebook that your school may have provided for you.

Now ideally, we're going to need some grid paper, squared paper, in order to do some of our line graph work on.

The rubber is optional in my lessons because I prefer to see pupils cross out work, to show that they've identified a misconception, and that they've learned where they made mistake, and that's all part of mathematical understanding.

So if you haven't got any of that equipment right now, pause the video, go and get what you need, and then come back and join us and resume the video.

Okay, so if you're ready to begin, so am I and we're going to move into the new learning.

Just to remind you that if you feel I'm going a bit too fast, or you need to go back and check the information, feel free to pause the video any point that you like, until you're comfortable and confident that you can continue the lesson.

As you will see on the first page of our new learning, we're presented with an incomplete line graph, and an incomplete table of data.

And our job is going to be, to complete both the line graph and the data, by taking information from one to finish the other, and then vice versa.

Okay, now most line graphs are created by using data that has been collected and recorded on table.

But sometimes, you'll find, you might be presented with a line graph that has all the information.

But the table is incomplete and you can take information do it the opposite way.

So it does work both ways.

Now, before we can try to stop completing the information, let's just double check that line graph's got everything we need.

It's got a title, team GB gold medals in rowing.

I mean, that's quite straightforward.

And then we've got the x axis down the bottom, which is correctly labelled and Olympic Games years.

So the intervals, it's going to be every four years.

And we've also got a Y axis labelled, which is the number of gold medals.

And the scale appears to be going up in one.

It starts on zero, and each of the grid lines, seems to be going up in one, with a maximum of five there.

The reason it goes up to five which is yes, that in our table of data, there will be no value greater than five in the table that we are creating.

Okay, I'm going to look at my table, I'm going to do that first, I think.

And I'm going to take information that exists on the line graph to fill in the missing blocks on the data table.

So I'm going to start with the years first of all, because I can see that the years fall that's quite straightforward.

So Sydney 2000, Athens is missing, but have a look along my x axis, you can see that Athens is 2004, 2008 and then there's a missing one 2016.

So if it's gone up from blocks of four, I know that London was 2012 or 2012.

So I'm going to fill them in.

Next, I'm going to go and look and finish the Olympic Games column.

Again, now that I've got all the years, it's quite easy to identify the correct, names and the correct cities.

So 2008 was Beijing, and 2016 was Rio.

So I'm going to finish that data off.

And now we're going to complete the number of gold medals.

I can see that three plot points have already been placed on the line graph.

I'm going to start at, there's nothing in Sydney at the moment.

So that's going to be two, but I'm not going to plot it just yet I'm going to finish the table off first.

So I'm going to go, get Athens.

Now I can see, there's a plot point at one gold medal in Athens.

And yet that is empty on the table.

So I'm going to fill that in with one.

Beijing is missing.

And I can see that it went up by two, so they doubled their in 2008 to get two.

And then finally in Rio, it went up again, and they got another medal.

So by the time it really happened, they got three gold medals.

put them in, and my table is now complete.

And now that I've got all that information in my table, I can now transfer that data onto my line graph, connect those plot points, and have a line graph that is complete and I can interpret the information.

Oh, I'm going to plot the meeting points.

We discussed previously that Sydney didn't seem to have a plot point so I can look on my table, two gold medals.

I'm going to put a little plot point there, go, use my ruler, just make sure I'm in the right line and on the right scale.

Yes, I am.

And also, we're missing one for London 2012.

And I can see we were really successful in London 20 what 12.

We won our most amount of gold medals in rowing, and across the five Olympic Games recorded here.

So I'm going to four, and it appears to be the highest point we're going to by connecting our plot points.

So now that I've got all the information for my table, and I've got all my plot points in, I'm going to connect it up.

So I get my ruler, draw a straight line between each individual plot point in order.

One more to go.

And I can see that I've connected all five of those Olympic Games present, and the data is completed.

Now that I have completed my line graph by taking the data that was in the table, I can now start to interpret the information that is presented in front of us, okay.

So I can ask a series of questions, or make a series of statements.

Here's some example questions.

Again, pause the video if you need a little bit more time.

If not, let's go through the questions.

Which year was the least successful, for GB rowing team? Well, I can see that the lowest data point was in Athens when they only achieved one gold medal.

So the answer for that would be Athens in 2004.

How many rowing gold medals did GB win over the five years in total? And when we talk about the five years, we're talking about the five years worth of Olympic Games, so don't count this as five years, It's five lots of Olympic Games.

So I'm going to count.

So there was two in Sydney, there was one in Athens, that's three.

There was two in Beijing so that's three plus two which is five.

There was four in London so that's five plus four, which is nine.

And then there was three in Rio.

So I've got nine plus three.

So in total, there were 12 gold medals won by the GB rowing team.

And finally, the last question on the slide, is pretty tricky.

And you're going to have to try and remember how we work out average and mean.

What was the average number of medals won across the five Olympic Games? Feel free to pause the video if you'd like a few extra moments to try to work the average number of medals out.

In order to do that question, you need to work out the total number of medals, which was 12, which we had also worked out question two, and then divide it by total number of Olympic Games within the data.

So 12 divided by five will give you 2.

4 medals.

And that is a correct calculation.

Of course, you don't get half medals in the Olympics.

So depending on the content of the question, you may be required to round that up or down, and in this case, you would round down to two medals, if you're looking at four medals.

And the beauty of is not only can you use it interpret past events, but you can also predict what might happen in the future, based on how the data has been changing from time to time or event to event.

To think at the data that is presented, what predictions might you make about the next Olympics in Tokyo 2020? Now I'm sure you've come up with some very evidence based predictions by using the data presented.

I have also been interpreting that information and I've come up with two different predictions which are opposed of each other.

They are contradictory.

But that's because the information here I think could go one of two ways.

So just give me some examples of predictions that you could make or make to that are little bit different.

My first prediction is, that based on the data from London 2012, to 2016, and by reducing the amount of gold medals that GB won, I'm actually predicting that in 2020, that GB will win three medals or less, because the data suggests there has been a decrease in the amount of productivity and we said that with such a small sample, only won Olympic Games, then actually, who knows, is open to interpretation.

However, if I look historically, on the line graph, I can see that in the past, there has been evidence of improvement after a poor year.

So if we look, in 2000 GB won two medals, and then they dropped to only one medal in 2004.

However, they then picked it back up and improved, in Beijing, to get two more medals.

And then in 2012, they got four medals, they doubled the amount that they won over four years.

So my second prediction is this, based on that historic data, I predict, they're actually going improve in 2020, they're going to win four gold medals, because the data suggests that they have in the past, come from a bad year, and improved, and increased their productivity.

We're now going to look at talk task.

Just a reminder that when we have taught tasks in school, we often have groups or pairs that we're able to discuss it with.

Now, if you have somebody in the house, that is willing to spend a few minutes on these slides with you, fantastic, get them over and start talking mathematically with them and pause the video.

However, if you are on your own, you can still have a go, you still pause the video and spend some time reflecting on the information in front of you.

If you don't feel comfortable doing that, feel free to continue the video, and we can discuss it with me as we look at the mathematics on the task.

What you can see on your screen is very reminiscent of the opening page in today's lesson.

Here you have an incomplete line graph, and you have an incomplete table.

So you need to complete the table, and then transfer that information and plot it accurately onto the line graph.

So that then able to interpret the information, to make factual statements and predictions, based on the patterns and events that you can see.

Okay, let's just spend a few moments going over your answers as to make sure you're on the right lines.

If you made any misconceptions, just cross reference your answers with the screen.

In the table, we can see that that number of medals for Sydney was two.

Athens was the Olympic Games missing and so, and that had three gold medals and that was plotted already on our incomplete line graph.

Beijing the missing year was 2008.

London was obviously 2012.

And Rio we were missing 2016.

So now I've got a complete data table, I can transfer that information, and plot it onto my line graph, and then connect the data points together.

So I put my eight, eight and six, and I get my ruler, and I accurately connect all those lines with straight lines to provide the line graph.

So now that I've got that information, you can make some practical statements and predictions about the data.

So my three factual statements that I picked out, GB won 27 gold medals over the last five Olympic Games, I just added all them together as a total.

Number two, GB won more gold medals in 2008 than in 2000 and 2004 combined, because in Sydney and Athens, they won a total of five, whereas in Beijing, they won eight.

So an increase of three.

And finally GB won fewer gold medals in 2004 than 2016.

I think that's quite clear, that the difference of two into, sorry.

Of three in 2004 and we saw it again.

A difference of three in 2004 and a difference of six in 2016.

So there was three extra gold medals, so they increase their productivity by 100%.

And my predictions based on information here, but it's interesting that they, at both Beijing and London, that they got a total of eight, they didn't improve in London from Beijing, and then it starts to tail off.

So it suggests to me that eight was probably the peak of their performance, and therefore I'm predicting that in Tokyo 2020, that GB will win six or less medals, because the data suggests that the number of gold medals is slowly stagnating or decreasing.

So I predict that actually, they may continue to decrease in their productivity.

Well done everyone so far.

having a fantastic lesson.

There's a lot of information being presented and you're doing a really good job and staying focused and completing the line graphs and tables.

We're now going to take our understanding a little bit deeper by introducing a second line graph for comparisons on the pages.

I'd like you to spend a moment or two, looking at the two line graph in front of you.

If you feel like you need to pause the video and spend a bit of extra time looking and discussing it, feel free to do so.

I'd like you to notice, why do you think the data looks the same? And what do you notice about the two line graphs? Well, first of all, you should definitely check the title, to see what the information is about.

On the left hand side you'll notice that it is the same data we've been looking at earlier in the lesson, Team GB gold medals in rowing.

And on the right hand side is Team GB gold medals in cycling.

So, we comparing two different sports, but at the same Olympics over time.

What you will see is that the labels are the same, and that therefore it's the same Olympic Games, and the data itself looks remarkably similar, we can make some comparison statements that are quite similar.

So for instance, on both Olympic Games, the data, the amount of gold medals won, increased between 2004 and 2008.

But the grand gold medals dropped from 2012 to 2016 in both charts, both line graphs sorry.

On the left hand side, it dropped by one, and on the right hand side, it dropped by two.

So the data lines do look similar, not the same, but they do look similar.

There are some comparisons that we can make.

However, I'm hoping you've noticed, why does it look the same? There is something a little bit different.

And that's to do with the levels of value.

So the scale on both sides, on both Y axes, is still going to come once, both sides are going to come once.

However, on the left hand side, the maximum value it put in place is five.

Whereas on the right hand side for cycling, the maximum value presented is nine.

And therefore the line graphs look the same size, but the scale is different.

And that is resulted in the data looking slightly squashed.

So what happens if I change that data? And if I try to use a similar size scale than I do, for my rowing? Now you can see the data has been presented in a slightly different way.

So what can you say about the data now? And what comparisons can we make? And finally, what questions does this line graph or this comparison of the two line graphs create? Again, you might want to pause the video, spend a little bit of time on this slide.

So you've had some time to look at the two line graphs and suggest what the data now suggests or shows us what's the same and what's different? Well, the data itself has not changed, that is still the same, the data points are plotted exactly the same, but the shape of the line graph is different, because we've stretched out our values, if you will, we increased the scale for rowing, and therefore it went up to nine and not five.

So there's a lot of empty space and I'm going to show you over here, this space wasn't okay.

So when we look at the two directly with the same scales, we can see that team GB were more successful in cycling, across the two sports.

The labels are the same, the titles are the same.

The only thing that changes is how the data is presented visually.

It gives us a bit of a clearer understanding.

We can see that it's easy to notice that there was a big jump, a bigger jump between Athens and Beijing, than it was at any point in the rowing.

We can also still see that there was a drop between London and Rio, as there was a drop between London and Rio in rowing.

However, that drop is more obvious because it's a bigger drop of two in cycling than it is in rowing cause it's a lot less steep.

more of a gentle incline, cause it dropped by one.

And it asks us, questions we can create, and I'm sure you've come up with some ideas.

A couple of examples might be, you know, what's the total amount of medal in total from rowing and cycling? What's the range of medals in both rowing and cycling? And finally, what is the total number of medals won, for individual sports? So how many did we win in cycling, how many rowing, and therefore, which was the most successful sport over the course of the five Olympic Games? And now it's over to you.

be your opportunity to complete an independent task, using some of the learning that we've shared today.

On your screen, you will see, not one but two incomplete line graphs, and two incomplete data tables.

Your task, is to do something very similar to what we've been doing all throughout the lesson.

You need to complete the tables, and then plot that data onto the line graph so that you have two complete line graphs and two complete sets of data.

Then you can use that data, to answer the questions that come at the end of the task.

If you would like an extension, you can then creates three factual statements that you can make about each of the graphs provided.

I'm going to give you the graph, in bigger format that you can see.

Line graph number one is Team GB gold medals in athletics, and line graphs number two, is team GB gold medals in sailing.

So like the previous lesson or the previous activities throughout the lesson, we are comparing the same Olympic Games, but two different sports within team GB.

And here are the questions which you must answer using the data that you have plotted.

Hopefully accurately on your line graphs.

Please pause the video now, and take as long as you need to complete the task to the best of your ability.

When you feel confident that you've completed the work and you're happy with what you've produced, resume the video, and we can share the answers together.

Best of luck.

Welcome back everybody.

And we're just going to briefly spend a little bit of time checking our answers.

So hopefully your line graph and completed table should look like it does in front of you for athletics.

There was two missing values, four and two, which you then could plot onto the line graph and hopefully your data when connected, looks very similar or identical to what is in front of you.

Make sure you've correctly labelled your x and y axis.

And in the two missing values with three and two, and that allows you to plot all of the points accurately, and then connect them together.

And again, your line graph should look very similar to this.

Now I take my two line graphs so I could put them side by side so I can see, and allows me to make some comparison statements.

I can also answer the questions about each individual line graph.

Looking at the answers there, number three was an open answer of course.

You have to predict based on what the data told you.

For sailing, I thought there would be one medal, based on what the data was telling me, but there might be a drop.

And in athletics, I thought they would improve because there's been evidence of improvement in the past every time they've had a bad Olympics, got better.

And therefore, I'd say because they dropped from 2012 to 2016, there would be an improvement for 2020.

Well done everybody for some fantastic independent work there, You did really, really well.

And for those of you who would like a little bit more of an extension or a bit more of a challenge, not quite had enough today, there is a challenge slide here, but you may pause the video, read the instructions, and have a go independently at home.

If you'd like to send in your challenge work, feel free to share it with Oak National Academy.

Details which I'm going to share with you at the end of this lesson.

almost brings us to the end of another fantastic lesson.

You've been great.

I really enjoyed teaching you once again.

It's time though for you just to check that that information has embedded and you feel confident with line graphs and timetables, and it's time for the quiz.

So when the video slides finish, have a go at the quiz.

Good luck.

As I mentioned previously start of the lesson, you can share some of your brilliant work, or some of your terrible stroke excellent mathematical jokes, with us here at Oak National Academy.

I'm looking forward to reading some of the work that you've been completing.

So if you would like to share some work or jokes, please ask your parent or carer to share your work on Twitter tagging @OakNational and #LearnwithOak.

I can't wait to see what you've been producing.

All right, everybody.

That brings us to the end of our lesson.

Thank you so much for sticking by me.

There's a lot of information there, but we got there in the end.

I think you're going to leave today's lesson with a lot more confidence and familiarisation with line graphs and tables.

Thank you for your hard work.

Enjoy the rest of your day.

And I hope to see you again soon here on Oak National Academy.

So from me Mr. Ward is goodbye and have a great rest of the day.

Bye bye.