Lesson video

This lesson is called Continuous and Discontinuous Variation: Practical and is from the unit Variation, Differences within Species.

Hi there, my name's Mrs. McCready and I'm here to guide you through today's lesson.

So thank you very much for joining me and I hope you're looking forward to today's lesson because today we're going to do a practical.

So we're gonna have a look at describing and measuring examples of discontinuous and continuous variation in various different features.

And I hope you're ready to get up and about and measuring and sampling.

Now we're gonna come across a number of keywords in today's lesson and they're listed on the screen now.

If you want to pause the video and make a note of them, please do so, but I will introduce them to you as we go.

So in our lesson today, we're going to firstly do a practical on discontinuous variation.

Then we're going to do another practical on continuous variation.

So are you ready?

I am, let's go.

So we know that there is great variety of all the various different living organisms that are present on earth and we know that there are millions of species in existence.

Each species is unique from every other species.

We also know that within each species there are many, many members and all of those individuals are also unique too.

So there is incredible variety on earth.

Now we know that there's variety, but how is it that we actually differ?

What differences are there between us?

Now some of these features, some of these variations, some of these differences have limited specifications.

There's limited variety and they can fall into specific categories.

For instance, eye color, ear lobe attachment or whether you can roll your tongue or not are all examples of variation where there are only a very specific and quite small number of differences between individuals.

Now these types of variation are called discontinuous variation because we can categorize individuals according to the feature that they've got.

So we can either put them into say category X or category Y or category Z.

And we can therefore distribute our data based on that feature.

It's categorical, it's either one category or another category or a third one for instance.

So usually with discontinuous variation, like ear lobe attachment or the color of eyes, that sort of thing, we end up getting a name for the category as opposed to a numerical measurement.

So you're either blood group A, or blood group B or blood group AB or blood group O.

There are no numbers involved in that.

You've either got blue eyes or green eyes or brown eyes for instance.

There's no numbers in that.

So these are categories, your category X or category Y or category Z for instance.

And these are all features of variation, which is discontinuous.

So which of these examples are discontinuously various.

Floppy or pointed dog ears, the circumference of tree trunk, the weight of an insect wing, the naturally present cow horns or not, whether peas are wrinkled or smooth, and the maximum height of an adult.

Which ones are examples of discontinuous variation do you think?

Come back to me in five seconds.

Okay, so have you spotted that floppy or pointed dog ears is a form of discontinuous variation.

So are whether cow horns are present naturally or not, and whether peas are wrinkled or smooth, they are either or types of discontinuous variation.

So as a class you are going to collect data on one feature that has discontinuous variation.

For instance, ear lobe attachment.

So is the bottom of the ear lobe, that's the fleshy bit at the bottom, where a normal ear piercing would go into.

Is that unattached, and so quite floppy and loose, or is it attached and quite thin and constricted?

And you can see some examples of those types of attachment or unattachment in the pictures on screen.

So you are either going to do that or you are going to collect discontinuous variation by identifying whether you as a class, individuals within the class can tongue roll.

So can you not tongue roll at all?

And you can't really move your tongue very much.

I mean obviously for talking, but you can't contort it into a different shape.

Can you only curl it into a straw?

So I can do that but I can't pucker it at the very end of my tongue like shown in the picture there.

Can you see how it's all puckered up and folded?

So which one of you?

Can you roll your tongue into a straw?

Can you puck it at the end or can you not any of that at all?

So one of those two examples, that's what you are going to collect variation about from your class.

So you're gonna collect this variation, the data, as a table and you're gonna collect it as a tally.

So for ear lobe attachment, you're either going to have the fact that it's attached or unattached and then your tally or for tongue rolling, either that you can't roll your tongue, you can roll it into a straw only or you can pucker it and then a tally against that.

So before you get started, just have a look at these explanations of discontinuous data.

So who is right, Andeep, Sam or Jun?

Andeep says, "Discontinuous variation has a maximum of three categories, X, Y, or Z.

" Sam says discontinuous variation can have lots of in between values like 0.

03, 0.

24, 0.

62, 0.

87.

" And Jun says, "Discontinuous variation has specific categories, no in-betweens and may not be numerical.

" So who is right?

Just pause the video and come back to me in five seconds time.

Okay, so have you spotted that Jun is correct here.

He has correctly defined discontinuous data as having specific categories, no in-betweens, and may not be numerical.

Excellent, well done.

So what you need to do is firstly as a class decide which type of data you are going to be collecting.

You're gonna collect the attachment of the ear lobe or the ability or not to tongue roll.

Firstly decide that and then draw a table to collect that data into.

You'll need the feature and the tally.

Then once you've got your data, you'll need to go round each member of the class and record whether their ear lobes was attached or not or whether they can tongue roll into a straw, pucker, or not at all.

So pause the video and come back to me when you are ready to carry on.

Okay, so your data might look a bit to like this.

So if you have looked at ear lobe attachment, then you might have got say three members of the class who have attached ear lobes and the rest, say 27 for instance, who have not got attached ear lobes, they are unattached.

Or perhaps for tongue rolling, maybe seven people couldn't roll their tongue and 14 could roll it into a straw but nothing else.

And then nine people could puck their tongue completely at the end, pinch it up.

Okay, so let's have a look.

We've collected our discontinuous data.

So what we're now gonna have a look at is continuous data.

So we've seen how some variation is either/or or that.

You know, it's categorical.

And we've seen some examples, we've collected some data of that, but there is also plenty of data and actually far more data which is much more varied and can take an almost infinite a number of values within a particular range.

For instance, your height could be literally any value at all and you could get right down to the nanometer between a normal range of its lowest value and its highest value.

And anything in between would be perfectly acceptable.

Or you could do a similar thing with body mass for instance.

Again, within a normal range, any value in amongst that would be perfectly acceptable.

And the same with foot length as well.

So these types of variation have infinite number of values and there's no discrete categories and therefore we call that type of data continuous variation.

And we usually plot continuous variation as either a line graph or a histogram.

Because the data is broad, there's many different sub variations within it and so we can lay it out in a numerical form.

So which of these features are examples of continuous variation?

Is it color of flower, length of leaf stalk, massive apple, the cat fur pattern, whether they're tabby plain, or blotched, the length of the cattail or fingerprint shapes.

Which ones do you think are examples of continuous variation?

I'll give you five seconds to decide.

Okay, so have you decided that continuous variation is exemplified by things like the length of the leaf stalk, the mass of the apple, and the length of the cat's tail?

Well done if you spotted those three.

So what you are going to do now is collect as a class data from a feature that has continuous variation.

So you are either going to collect data on the height of each individual or you are going to collect data on the mass of a set of apples that you've been given.

So you are going to record your data in a table, but this time you're going to record each individual in their own row.

So individual number one and their height or the mass, individual two, their height or the mass and so on and so forth for the number of people or the number of apples that you've got.

Quick check of understanding, whose explanation this time is correct about continuous data?

So the same three lads are discussing it, Andeep, Sam and Jun.

Andeep this time says, "Continuous variation has an infinite number of individuals.

" Sam says, "Continuous variation can have lots of in between values like 0.

03, 0.

24, 0.

62, 0.

87.

" And Jun says, "Continuous variation has specific categories but is numerical.

" So who is correct?

I'll give you five seconds to decide.

Okay, so did you decide that Sam's correct this time by describing continuous variation as having lots of in between values, such as 0.

03, 0.

24, 0.

62, 0.

87.

Well done.

So firstly, you'll as a class need to decide which type of data you are going to collect.

Are you going to collect the height of each individual within the class or are you going to collect the mass of a set of apples that you've been given?

So decide that and then draw a table to collect the data, noting down row per individual person or apple.

And the appropriate title for the data column, you are either measuring height in centimeters or the mass of the apple in grams.

Once you've got the table ready, then you can go round each individual person or apple and collect the data and write it into the table against their individual row.

So pause the video, come back to me when you are ready.

Okay, so hopefully you've had enough chance to go round the whole class, you've collected all your data or you've gone through all of the apples that you've been given and you've measured all of their masses.

So your data now might be something along these lines.

So I've listed each individual and their various different heights or the individual apples and their specific masses.

Okay, so well done.

That was quite a lot of data to collect in today's lesson.

So we've seen how some features are discontinuously various and therefore they have very limited variations which fall into discreet and particular categories.

Examples include eye color and pea texture, for instance.

And the data on how often features with discontinuous variation occur in a population can be collected as a tally.

And that's what you did in today's lesson.

Whereas with continuous variation, these values can take any value within a normal range.

And examples include things like length, height, width, mass, and circumference.

And these are all measured as numerical values.

So you've got your data, you've collected all of that from your classmates or from apples, and I hope you've enjoyed doing so.

I certainly have.

Thank you very much for joining me and I hope to see you again soon, bye.