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Hello.
My name's Mrs. Jones, and I'm really pleased you decided to join this lesson today.
In this lesson, we will look at combining and comparing data.
When you're trying to find answers to a question, you might need to look at more than one dataset, and this means comparing what we see in one dataset with another.
This can help us to find similarities between them that can help answer a question.
It helps us see the full story.
It's important to look at more than one dataset to make sure we do get the full picture to answer the question.
So let's get started and learn about combining and comparing datasets.
Welcome to today's lesson.
Today's lesson is called Combining and Comparing Data from the unit Data Detectives, and by the end of this lesson, you'll be able to combine data from different sources to find new information.
There are three keywords to today's lesson.
Dataset.
Dataset is a collection of related data.
Compare.
Compare is look at two or more things to find similarities and differences.
Conclusion.
Conclusion is a decision reached using evidence.
There are two sections to today's lesson.
The first is Compare Datasets and the second is Combine Data to Draw Conclusions.
So let's start with Compare Datasets.
At Oak Academy Zoo, a rhino called Ruby is missing.
We have already found out that she had a vet appointment.
We are going to combine data to find out more.
Combining datasets means using evidence from more than one source.
When we compare datasets, we look for the same names, matching times, or linked places.
This dataset shows the vet appointment times.
We can see that Mango had an appointment at 9:15.
So you can see there in the vet appointment list, Mango Monkey was at 9:15, and we know that Ruby Rhino was at 11:15.
This dataset shows where Mango was moved and when.
Mango went from the enclosure to the vet and then back from the vet to the enclosure.
We can see a transport log here, and we have Mango Monkey from the enclosure to the vet at 9 o'clock, and then Mango Monkey from the vet to the enclosure at 10:00.
By comparing the datasets, we can see that Mango left the monkey enclosure at 9:00, had a vet appointment at 9:15, returned to the monkey enclosure at 10 o'clock.
When the datasets are combined, the full story appears.
This dataset shows the location of the vet center and the monkey enclosure.
You can see on the left, we have the monkey island, which is the monkey enclosure, and on the bottom right, we have the vet center.
You can also see the elephant habitat up the top right, a cafe in the middle on the right, and the rhino enclosure on the bottom left.
The zoo map reveals that the vet center is inside the zoo.
This supports the movement recorded in the transport log.
Each data set shows a different part of the story.
The vet schedule shows the appointment time.
The transport log shows movement.
The map shows the locations.
One dataset on its own does not explain everything.
Let's have a quick check.
Which two datasets could be compared to find out when Mango left her enclosure?
Is it A, the vet schedule, B, the zoo cafe menu, C, transport log, D, zoo weather report?
Pause the vide and have a think.
Which two datasets could be compared to find out when Mango left her enclosure?
And then we'll go through the answer.
Let's check your answer.
The answer was A, vet schedule and C, transport log.
Well done if you got those correct.
The transport log shows Mango left at nine o'clock.
The vet schedule shows her appointment at 9:15.
The transport log shows Mango returning at 11 o'clock.
Let's have a quick check.
True or false?
Comparing datasets means looking at only one dataset carefully.
Pause the video and have a think, is that true or false?
And then we'll go through the answer.
Let's check your answer.
The answer was false.
Well done, if you got that.
Why is it false?
Pause the video and have a think.
Can you explain why that is false?
And then we'll go through the answer.
Let's check your answer.
Comparing means looking at two or more datasets to find links between them.
Well done if you got that correct.
Let's do the activity.
Compare the datasets.
Look at the vet schedule and the transport log for Ruby.
Circle the information about Ruby that appears in each dataset and write one sentence explaining the link.
You have the transport log on the left and we have Mango Monkey leaving the enclosure to the vet at nine o'clock.
Mango Monkey going from the vet to the enclosure at 10 o'clock.
Ruby Rhino going from the enclosure to the vet at 11 o'clock.
Zoe Zebra going from the field to the stable at 11:30.
And the vet appointment list has Mango Monkey at 9:15, Percy Panda at 10:15, Ruby Rhino at 11:15, and Kiki Koala at 12:15.
Pause the video to complete this activity, and then we'll go through the answers.
Let's have a look at the answers.
So we circle the information about Ruby that appears in each dataset.
You can see here we've got Ruby Rhino going from the enclosure to the vet at 11:00, and we have the vet appointment list, and we have Ruby Rhino at 11:15.
Well done if you got that part right.
The second part was write one sentence explaining the link.
And Sofia's put, "The link is that Ruby appears in both datasets and the times are close together, 11:00 and 11:15.
" Well done if you got those correct.
Let's move on to the second part of today's lesson, Combine Data to Draw Conclusions.
When you combine datasets, you use evidence from more than one source to form a conclusion.
No single dataset explains everything.
Each dataset gives one part of the explanation.
When evidence from different datasets fits together, a clearer explanation can be formed, so on the left here, we have the vet schedule, the transport log, and the zoo map, and when those are all combined together, we can get the conclusion.
Let's have a quick check.
Which statement best explains combining datasets?
A, using only one source, B, listening to a rumor, C, using evidence from multiple sources.
Pause the video to consider your answer and then we'll go through it.
Let's have a look at the answer.
The answer is C, using evidence from multiple sources.
Well done if you got that correct.
When the datasets are combined, you can see that Ruby left the enclosure at 11 o'clock, Ruby had a vet appointment at 11:15, the vet center is in a known location within the zoo.
Jacob says, "All three records match.
" This dataset shows the vet treatment notes.
So we have vet treatment notes, and we have the animal, Mango Monkey at 9:15, and the notes say, "Annual vaccine and checkup all well.
" We have Percy Panda at 10:15, and the notes say, "Check up all well," and we have Ruby Rhino at 11:15, and the notes say, "Sore paw.
Thorn removed and medicine given.
Overnight stay for monitoring.
" Sofia says, "This shows what happened at the appointments.
" When the treatment notes are added, you can see that Ruby left the enclosure at 11:00.
Ruby has a vet appointment at 11:15.
Ruby is staying overnight.
The vet center is inside the zoo.
Jacob says, "Now we have the full story.
" The information is not clear from one dataset alone.
It becomes clear when the datasets are combined.
Sofia says, "One record wasn't enough.
" When data from different sources connects, new understanding appears.
This is how conclusions are formed.
Now we have the vet schedule, transport log, zoo map, and treatment log, and all that can help us draw the conclusion.
Let's have a quick check.
True or false?
You form a conclusion using evidence from more than one dataset.
Is that true or false?
Pause the video and have a think if that's true or false and then we'll go through the answer.
Let's check your answer.
The answer is true.
Well done if you got that correct.
Ruby was transported from her enclosure to the vet center at 11:00 for her 11:15 appointment.
She is staying overnight after treatment for a thorn in her foot.
This conclusion is based on multiple datasets.
So we can see here at 10:30, Ruby was last seen.
11:00, transport, 11:15, vet appointment, and an overnight stay.
Let's do the activity.
Using the vet schedule, transport log, zoo map, and treatment notes, write one sentence explaining what happened to Ruby.
Write one sentence explaining how the datasets support your conclusion.
The datasets that you want to have a look at for the vet schedule, transport log, zoo map, and treatment notes are available in the additional material for this lesson.
So pause the video and have a go at that activity, and then we'll go through the answers.
Let's have a look at the answers.
Ruby was transported from her enclosure to the vet center at 11 o'clock for her 11:15 appointment.
She didn't return to her enclosure.
This conclusion is supported by the transport log for movement and time, the vet schedule for the appointment time, the zoo map for the location of the vet center, and the vet treatment log of what happened at the vet's.
Well done if you got that correct.
In summary, a dataset is a collection of related data.
Data can be combined from different datasets.
When you compare datasets, patterns and links can appear.
Comparing data can help you notice new information that was not clear before.
Using evidence from more than one dataset helps you draw a clear conclusion.
Well done for completing this lesson, Combining and Comparing Data.
