Lesson video

Hi, everyone, my name is Mrs. Jenkins.

Welcome to today's lesson, Accurate Data taken from the unit Perfect Pets.

Let's get started.

In today's lesson, our learning outcome is I can check pet data for mistakes and explain why they are wrong.

In our lesson, we have three keywords.

Those words appear throughout the slide deck, so it's really important we understand what they mean before we get started.

Those three words today are accurate, error, and check.

Accurate is something that is correct and without mistakes.

An error is something that is wrong.

And check is to look at something carefully to see if it is correct.

So those words again are accurate, error, and check.

Keep an eye out for them as we move through the lesson.

In today's lesson, accurate pet data, we have two learning cycles.

We have recognize incorrect data and explain why data may not be accurate.

Let's get started with recognize incorrect data.

Data that is correct and without mistakes is accurate.

Sometimes data can be wrong.

When data is wrong, it has an error and is not accurate.

You can recognize incorrect data by checking does anything have two different values?

Does the value make sense?

And is the correct type of data used?

Let's have a little check-in.

Which data about a pet contains an error?

A, height in centimeters: 20 / strength: 4, B, height in centimeters: 20 / height in centimeters: 30, or C, speed: 2 / strength:4.

What do you think?

Have a go.

How did you get on?

I asked which data about a pet contains an error.

A, height centimeters: 20 / strength: 4, B, height is in centimeters: 20 / height in centimeters: 30, or C, speed" 2 / strength: 4.

The answer is B, because you can't have a pet that is both 20 centimeters and 30 centimeters in height.

It needs to be one or the other.

Great job, everyone.

Sometimes errors are easy to spot.

For example, brown is not the correct data for the attribute speed.

So if we have a little check on Sunny's pet card, we can see his name is Sunny, the color is gold, he has 4 legs, he's 1-year-old, his height is 40 centimeters, and then it says speed 1-5: the answer is brown.

Now that's not a speed that is between one and five is it?

So we know that brown must be an error.

Other times you might need to think about what accurate data might look like.

For example, it is unlikely that Puddle the duck is 1,000 centimeters tall.

So we can look at Puddle's pet card.

Puddle, the color is brown, it's 2 legs, 3 years old, and his height is 1,000 centimeters, his speed is 3.

And we can tell that a puddle duck is unlikely to be 1,000 centimeters tall.

Let's have a little check now.

True or false?

If data is written down, it is always accurate.

What do you think?

Have a go.

How did you get on?

I asked you true or false?

If data is written down, it is always accurate.

The answer is false.

And the reason why, data can contain errors.

So it needs to be carefully checked.

Even if we are writing it down, it can still contain errors.

We are going to move on to task A now.

I would like you to look at the pet data below which pieces of data are incorrect?

And circle or list the errors.

So we have three pets.

We have Puddle, who is a duck, Nibbles the hamster, and Pip the cat.

So if we look at our data, Puddle is 25 centimeters, 165 years, really, really strong, and an average speed, a middle speed.

Nibbles the hamster we've got is 100 centimeters tall, 1 years old, not very strong, but extremely, extremely, extremely fast.

We have Pip the cat is 30 centimeters tall, his age in years is fluffy, the strength is quite strong and has no speed.

So have a look at the pet data and circle or list the errors.

Have a go.

How did you get on?

I asked you to look at the pet data below and which pieces of data are incorrect.

Circle or list the errors.

So we had Puddle the duck, Nibbles the hamster and Pip the cat.

We had to look at their height, age, strength, and speed.

So some of the errors we have: Puddle the duck, I think it's very unlikely to have a duck that is 165 years old.

And also I don't think a duck is going to be the strongest of the animals.

So I don't think it will have a five strength.

Then we move on to Nibbles the hamster.

Now 100 centimeters is one meter, that's very tall for a hamster to be.

So I think that is incorrect.

And the speed needed to be between one and five and it says 40 there.

And while hamsters are fast, I don't think that is between one and five.

Then when we have a look at Pip the cat, the age in years is fluffy.

Now that isn't an age in years is it?

Is a description of what the cat might be like.

And we have no answer for the speed.

So that is incorrect as well.

Well done, everyone.

Great job.

We're gonna move on to learning cycle two now.

Explain why data may not be accurate.

Data may not be accurate for different reasons.

It is important to understand why an error has happened.

Aisha says, "Why is this data incorrect?

" Andeep has replied, "Let's check what happened!

" Data may not be accurate because someone recorded the wrong value, measured incorrectly, or used the wrong type of data.

Let's have a little check-in.

Sunny's strength is written as fluffy.

Why is this not accurate?

A, the pet is not that strong.

B, the wrong data type was used.

Or C, the number is too large.

What do you think?

Have a go.

How did you get on?

I asked, I explained Sunny's strength is written as fluffy, why is this not accurate?

A, the pet is not that strong.

B, the wrong data type was used.

Or C, the number is too large.

The answer is B.

The wrong data type was used.

Fluffy is not a recording of strength.

It is what it looks like.

Great job, everyone.

If data is not accurate, comparisons may be unfair or impossible.

For example, if one pet's strength is written incorrectly, it may appear stronger than it really is.

So we have Toffee here.

His color is white and brown.

Legs 4, age 2.

It says his strength is 5, which means he's an extremely strong animal.

Do we think if we compared him to a dog, he would be as strong as a dog?

So just have a think.

And the speed is 3, so in the middle.

When data is not accurate, people should check it carefully.

If there is an error, it can be corrected.

Data does not have to stay wrong.

Okay, let's have a little check in.

True or false?

Once data is written, it cannot be changed.

What do you think?

Have a go.

How did you get on?

I asked you, true or false?

Once data is written, it cannot be changed.

The answer is false.

The reason why, data can be checked and corrected if there are mistakes.

Great job, everyone.

We are going to move onto task B now.

I would like you to look at the pet card data and answer why might this data not be accurate?

What kind of error is in each mistake and how should the data be corrected?

So we have the card for Patch.

It's age is 8, speed: 2, strength: 3, height in centimeters: 45 and color: 5.

For Buddy his age is 4, his speed is 3, his strength is 4, his height in centimeters is 2,000, and his color is brown and white.

Have a go.

How did you get on?

I asked you to look at the pet card data and answer why might this data not be accurate?

What kind of error is each mistake and how should the data be corrected?

So for patch, he was 8 years old, his speed was 2, strength: 3, his height in centimeters is 45 and his color is 5.

And buddy, his age is 4, his speed is 3, his strength is 4, his height in centimeters is 2,000, and his color is brown and white.

So Sam tells us, "Buddy's height is 2,000 centimeters.

The value is too large to be true, Buddy should be measured again.

" And Alex says, "Patch's color is written as 5.

It is the wrong type of data.

The data should be checked and written again.

Great job, everyone.

Well done.

You have worked really hard in today's lesson.

Let's summarize what we have learned.

Data is accurate when it is correct and without mistakes.

Incorrect data can be recognized by checking for errors.

Data may not be accurate because the wrong value was recorded or it was measured incorrectly or the wrong type was used.

Data can be checked and corrected.

Great job, everyone.

You have worked so hard in today's lesson.

I can't wait to learn with you again soon.