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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 relevant and irrelevant data.
Sometimes you can look at lots of data, and not all data can help you answer the question.
This is why it's important to know which data is relevant to your question.
So let's get started and learn about looking at and using relevant data and knowing when some data is irrelevant.
Welcome to today's lesson.
Today's lesson is called Selecting Relevant Data from the unit Data Detectives.
And by the end of this lesson, you'll be able to explain which data is relevant to a question and why.
There are two keywords to today's lesson.
Relevant, relevant is useful for answering a question.
Irrelevant, irrelevant is not useful for answering a question.
There are two sections to today's lesson.
The first is identify relevant data.
And the second is explain why some data is irrelevant.
So let's start with identify relevant data.
At Oak Academy Zoo, a rhino called Ruby is missing.
We will look at different data sets to decide which are useful.
Data is relevant when it helps you answer a question.
For example, what time does the school day start?
Sofia says "The school's start time answers the question.
" You can see in the table here we have school start time, 8:45.
Playground rules, no running.
Lunch menu, pasta.
Day of the week, Tuesday.
So which part of that is relevant to help us answer the question, what time does school day start?
That's that first line there.
It says, "School start time at 8:45.
" Data is irrelevant when it does not help you answer the question.
Jacob says, "The playground rules, the lunch menu, and the day of the week are all irrelevant to the question, what time does the school day start?
" Let's have a quick check.
Which piece of information is most relevant for answering the question, what time does the school day start?
Is it A, the lunch menu?
B, the playground rules, or C, the school start time.
Pause the video and have a think.
Is it A, B or C that is relevant to answering the question, what time does the school day start?
Pause the video, have a think, then we'll check your answer.
Let's check your answer.
The answer is C, the school start time.
Well done if you got that correct.
Whether data is relevant depends on the question.
The same data can be relevant for one question and irrelevant for another.
Jacob says, "If the question was about what was for lunch, the lunch menu would matter.
" You can see in the table here, the school start time at 8:45 is now not relevant, it's irrelevant.
What we're looking at is the lunch menu and can see that it's pasta.
And that is the relevant answer, the relevant information, that relevant data that helps us answer that question.
What is the lunch?
Interesting data is not always relevant data.
To decide if data is relevant, you must keep the question in mind.
Finding out what is for lunch is interesting, but it doesn't answer the question of what time school starts.
Let's have a quick check, true or false?
If data is interesting, it must be relevant.
Pause the video and have a think if that is true or false.
If data is interesting, it must be relevant.
Pause the video, have a think, and then we'll go through the answer.
Let's have a look at the answer.
The answer is 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?
Then we'll go through an answer.
Let's have a look at the answer.
Data is only relevant if it helps you answer the question.
Interesting data does not always help.
Well done if you got that correct.
Explaining why data is relevant is important.
You can explain why data is relevant by giving a reason.
The school start time helps because it answers the question, what time does the school day start?
Choosing relevant data helps investigations stay clear and focused.
You can see here that they've pulled out the detail, that relevant information, the school start time, 8:45.
Let's do the activity.
Here is some information about the school day.
So the information on the table is that we have a school start time of 8:45, school finish time of 3:15.
Playground rules, no pushing.
Lunch menu, fish and chips, and day of the week, Wednesday.
There are two questions.
What time does the school day start?
What time does the school day end?
Circle the relevant data and explain why it is relevant.
Pause the video and have a go at that activity, and then we'll go through the answer.
Let's have a look at the answer.
So Jacob says, "The school start time and finish time are the only relevant rows in the table.
" You can see them circled here, school start time, 8:45, and school finish time, 3:15.
Well done if you got those correct.
Let's move on to the second part of today's lesson.
Explain why some data is irrelevant.
The question is, why did Ruby leave her enclosure?
Different data sets are available.
Not all of them will help you answer the question.
Why did Ruby leave her enclosure?
Here is the first data set, the zoo weather report.
We can see here at 8:30, it was cloudy.
9:30, cloudy, 10:30, sunny, 11:30, sunny.
Sofia says, "The weather report is interesting, but does it help answer why Ruby left her enclosure?
" Jacob says, "It tells us what the weather was like, but there is nothing about Ruby there.
" This dataset is the zoo cafe menu.
And here we have a sandwich, costs three pound, soup, two pound, chips, £2.
50, sausage roll, three pound.
Sofia says, "The cafe menu shows me what food I can get, but does it tell us about anything about Ruby?
" Jacob says, "It does not explain why Ruby is missing from the enclosure.
" This dataset is the temperature log for the rhino enclosure.
At 8:00, it was 18 degrees, 9:00, 18 degrees, 10 o'clock, 18 degrees, 11 o'clock, 18 degrees, 12 o'clock, 18 degrees.
Is this one going to help us?
Sofia says, "The temperature log is interesting, but the temperature doesn't change all morning.
" And Jacob says, "I don't think the temperature report tells us why Ruby left.
" Let's have a quick check.
Which sentence best explains what makes data relevant?
Is it A, relevant data is data that is interesting.
B, relevant data is data that is easy to read.
C, relevant data is data that helps answer the question.
Pause the video and have a think if the answer is A, B, or C, and then we'll go through the answer.
Let's have a look at the answer.
The answer is C.
Relevant data is data that helps answer the question.
Well done if you got that correct.
This data is the vet's appointment list.
And here we've got Mango Monkey at 9:15, Percy Panda at 10:15, Ruby Rhino, 11:15, Kiki Koala at 12:15.
Is this data helping us, is it relevant or irrelevant?
Sofia says, "The vet's appointment list includes Ruby and a time.
" Jacob says, "I think the vet's appointment list tells us why Ruby left her enclosure.
" You can see there that Ruby Rhino had an appointment at 11:15.
The vet's appointment list is relevant because it helps to answer the question.
You can see there Ruby Rhino, 11:15.
The other data sets are irrelevant because they do not help explain Ruby's movement.
Sofia says, "They don't answer the question of where Ruby has gone.
" Sofia says, "I always thought that if we had more data, we would get better answers.
" And Jacob says, "Only data that is relevant helps us to answer a question clearly.
" Let's have a quick check, true or false?
More data always gives better answers.
Is that true or false?
Pause the video and have a think if that is true or false.
Does more data always give us better answers?
And then we'll go through the answer.
Let's check the answer, the answer is false.
Why is that false?
Pause the video and have a think.
Could you explain why that is false?
And then we'll go through the answer.
Let's check your answer.
Only data that is relevant helps you answer a question clearly.
Well done if you got those correct.
Let's do the activity.
Look at the data sets and answer the question.
Why did Ruby leave her enclosure?
Explain which dataset was relevant and why.
And you can see here the datasets are available in the additional material for this lesson.
So have a look at those datasets and you will think about that question.
Why did Ruby leave her enclosure, can we answer that?
And can we explain which dataset was relevant and why?
Pause the video.
Have a look at those datasets and answer those questions and then we'll go through an answer.
Let's have a look at an answer.
Sofia said, "I used the vet's appointment list to see that Ruby was at the vet when we could not find her in the enclosure.
The vet's appointment list was the relevant data set.
" Well done if you got that correct.
In summary, relevant data helps you answer the question being asked.
Some data is more relevant to a question than other data.
Irrelevant data does not help you answer the question, even if it is interesting.
Choosing relevant data helps investigations stay clear and focused.
Well done for completing this lesson, Selecting Relevant Data.
