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www.mathcentre.ac.uk/.../8.1%20Differentiation%201st%20principles%20Tangent.mp4

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    In this video, we're going to be
    looking at how to differentiate
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    very simple functions from first
    principles. So to begin with,
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    what we want to have a look at
    is a straight line.
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    A straight line has a constant
    gradient, or if we prefer its
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    rate of change of y with respect
    to x is a constant.
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    If we take the straight line y
    equals 3x + 2,
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    we can look at its gradient.
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    We take two points and look at
    the change in y divided by the
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    change in x.
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    When x changes from -1 to 0,
    y changes from -1 to 2,
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    and so the gradient is 3.
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    No matter which two points on
    the line that we use, the value
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    of the gradient is always the
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    same. It is always 3.
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    Now we can see that in another
    way, by looking at a table of values.
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    So let's take x ranging
    in values from -3 up to 3.
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    And let's have a look at 3x.
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    Which is simply the values of x
    we've got multiplied by 3.
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    And then add 2 to those values
    to give us the function
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    y equals 3x + 2.
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    Now as we look at this table
    of values, what we see is that
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    for every unit increase in x we
    always get 3 units increase in y.
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    So as we go from -3 to -2,
    y goes from -7 to -4.
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    As we go from 0 to 1, y goes
    from 2 to 5.
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    For every unit increase in x we
    get the same increase in y of 3 units.
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    And so the gradient of this
    straight line is 3 or
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    the rate of change of y with
    respect to x is also 3.
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    Now, nice as it is that a straight
    line has a constant gradient
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    and that y is changing at a
    constant rate with respect to x,
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    this is not always the case.
    So for instance when
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    you are in a car and you press
    the accelerator, you watch the
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    needle on the speedometer. The
    needle doesn't go up gradually,
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    it doesn't go up constantly. The
    rate of increase of the speed varies.
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    Similarly the acceleration due to gravity,
    now near the surface of the Earth,
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    we assume that it's constant.
    But Newton actually showed that
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    it was proportional to 1 over
    r squared, where r was the
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    distance that we were away from
    the surface of the earth. So we
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    can see that as we move further
    away from the surface of the
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    Earth, the acceleration due to
    gravity gets less, but it
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    doesn't change constantly. It
    doesn't change uniformly.
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    So to see what's happening we
    need to look at some very simple curves.
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    For a curve, we can see that if
    we join any pair of points, we
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    get a straight line.
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    But when we join different pairs
    of points, we tend to get very
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    different straight lines with
    very different gradients.
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    We can see this again by looking
    at very simple curve y equals x squared
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    and looking at a table
    of values for it from -3 again
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    up to +3. So now let's calculate
    the value of
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    the function y equals x squared
    at each of these values.
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    Now let's have a look how the
    value of the function is
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    changing as the value of
    x changes. So if we have a
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    unit increase in x from -3 to
    -2, we find that this time
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    the value of y is gone down
    from 9 to 4, so it's gone down
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    by 5 units. Not a problem if
    that decrease is going to be
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    sustained. But when we look at
    the next unit.
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    From -2 to -1, we find that it's
    gone down from 4 to 1,
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    y has decreased by 3.
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    And in the next unit it is
    decreased by 1, but then it
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    starts to increase again so we
    can see that for a very, very
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    simple function like y equals X
    squared, y is not changing
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    constantly with respect to x.
    Now this is not a problem so
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    long as we can find a way of
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    calculating it. To start that
    process, let's just have a look
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    at a sketch of y equals x squared.
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    And let me pick this
    point on the curve.
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    Now as we look at that look at
    this very tiny little bit,
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    that's almost straight, and if I
    was to home in and magnify, it
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    would be almost more straight
    and it would appear to be
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    straighter and straighter so as
    we homed in closer and closer to
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    the point what we would see
    would be much more like a
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    straight line. What straight
    line might we be able to take
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    to represent that sort of
    local straightness? And the
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    answer would have to be a
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    tangent. Through the point.
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    And that gives us what we need,
    because this tangent is a
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    straight line and we know that a
    straight line has got a constant
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    gradient, and so this is the
    definition that we make.
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    That the gradient
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    of a curve
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    y equals a function of x
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    at a given point
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    is equal
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    to the gradient
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    of the tangent
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    to the curve
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    at that point.
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    So notice we haven't defined the
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    gradient of the curve globally,
    so to speak,
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    we've said that at any particular
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    point, the gradient of that
    curve is going to be the same
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    as the gradient of the
    tangent. So now what we want
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    to see is how can we use this
    definition to help us actually
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    calculate that gradient at any
    particular point?
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    Let's take a fixed point P on
    our curve and a sequence of
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    Points Q1, Q2 and so on. Getting
    closer and closer to P.
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    We see that the lines from
    P to each of the Qs gets
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    nearer and nearer to being
    a tangent as the Qs come
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    nearer and nearer to P.
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    So if we calculate the gradient
    of one of these lines and let
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    the point Q Approach P along the
    curve than the gradient of the
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    line should approach the
    gradient of the Tangent.
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    And hence the gradient of
    the curve.
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    So let's now try and set up
    a calculation for the curve
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    y equals x squared at the point x
    equals 3, so that this
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    calculation represents what
    we've just seen.
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    So first of all, I'll
    sketch the curve.
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    So there is y equals x squared.
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    Here will take our point.
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    Where x is equal to three. I'm
    going to take a point Q,
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    which is near to P on the
    curve and I'm going to join up
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    those two points with a straight line.
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    So there's my point, P as
    my point Q and I'm going to take
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    a triangle formed by dropping a
    perpendicular down to reach the
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    horizontal through P. So that will
    give me a little right angle
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    triangle with the right angle at
    the point are.
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    Now I'm going to take
    small values of PR.
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    So that I get the coordinate
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    of Q. So let's line that up.
    PR will be first of all 0.1,
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    then 0.01, 0.001
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    and finally 0.0001.
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    So what will be the x coordinate
    of Q, x coordinate of Q?
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    Well, it will just be 3 + whatever PR is
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    so that will be 3.1, 3.01, 3.001
    and 3.0001.
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    Now I've got the x coordinate of Q,
    let's calculate the y coordinate of Q.
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    So that means we've got to
    square each of these,
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    so our first result will be 9.61
    when we square that.
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    Next is 9.0601.
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    Next 9.006001
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    and the next 9.00060001.
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    So what's the change in y
    for each of these?
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    In other words, what's QR?
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    We know that the base for where
    P is is if x is equal 3 at P,
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    y must be equal to 9.
    So QR, the increase in y
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    we can get by taking 9 away
    from each of these.
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    That's 0.61, 0.601, 0.006001,
    0.00060001.
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    So now we need to
    calculate the gradient of
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    each of these little segments
    PQ. So what is that gradient?
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    will it be the increase in y, which is
    QR, over PR, which is the increase in x.
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    So we've got 0.61 divided
    by 0.1. So to do the first one
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    I'll write it down 0.61 divided
    by 0.1, that is 6.1.
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    If we do the same calculation
    here, the answer is 6.01.
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    Do the same calculation here
    and it's 6.001.
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    And do the same calculation here
    and it's 6.0001.
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    So let's just have a look what's
    happening here. This gradient
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    seems to be getting nearer and
    nearer to 6. And 6, perhaps by coincidence
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    is 2 times by 3, where 3 is the x value
    at this point, P.
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    So we need to do this
    calculation again, but we need
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    to do it in general.
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    So let's set that situation.
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    We take our axes.
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    And we plot our curve
    y equals x squared.
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    Take my point P on the curve
    and P is (x,y).
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    And I take a point Q a little
    further along the curve.
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    How far along the curve is it?
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    Well, I'm going to increase x by
    a very small amount.
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    So we got the same triangle.
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    As we had in the calculation.
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    So there's R.
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    And I am increasing x, to get to R,
    by a very small amount and
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    that small amount is going to be
    written as delta x.
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    Now I cannot emphasize enough
    that delta x is not delta times by x.
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    It is a single symbol on its own,
    and it represents a small change in x.
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    What's that resulted in? Its pushed the
    point further along the curve to Q,
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    and so we've got a change in y
    of delta y
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    So that the coordinates of Q are now
    x + delta x and y + delta y.
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    Now. We've got the
    diagram labeled up.
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    And so what we need to be able
    to do is do some calculation.
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    What do we know? We know that
    this is the graph of the curve
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    y equals x squared.
    So here at the point Q we know that
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    y + delta y is equal to
    x + delta x all squared.
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    This we can multiply out. It will
    give us x squared plus 2x delta x,
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    and I'm going to put that
    in a bracket to emphasize the
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    fact that delta x is a
    single symbol,
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    plus delta x all squared.
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    But what else do we know? Will we
    know at this point P that y is
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    equal to x squared.
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    So y + delta y is equal to this but
    the y part is equal to x squared.
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    So that tells us therefore that the
    change in y, delta y, is this bit here:
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    2x delta x plus delta x all squared.
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    So let's now calculate the gradient of
    this line PQ.
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    The gradient of PQ,
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    well, it's QR over PR
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    or the change in y,
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    delta y, over the change in x.
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    And we've got expressions
    for both of these:
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    delta x is delta x and delta y is this.
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    So we've got delta y over delta x
    is equal to...
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    Let's remember that this was 2x
    delta x plus delta x all squared
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    and that was all over delta x.
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    Now, delta x is a common factor here.
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    Let's take it out as a common factor:
    2x + delta x
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    times by delta x; all over delta x.
    Now delta x is a small positive
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    amount of x, so we can
    cancel it out there and there.
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    So we have delta y over delta x
    is equal to 2x + delta x.
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    Now remember what we're doing.
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    We've calculated the gradient of
    this line PQ and we're going to let
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    Q come nearer and nearer to P
    along the curve.
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    So we're letting delta x
    tend to 0,
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    until this secant or cord, PQ,
    becomes the tangent.
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    And so we can say that the gradient
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    of
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    the tangent
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    at P is equal to...
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    Now we have to use some
    mathematical language.
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    What happens to this expression as
    delta x approaches 0?
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    Well, it would seem that if
    delta x got smaller and smaller
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    and smaller and smaller
    and smaller, it got to zero.
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    This would become 2x. We are
    approaching a limit of 2x and so
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    we use some mathematical
    language to help us say that. So
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    we say that this is the limit,
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    as delta x tends to 0,
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    of delta y over delta x
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    is equal to
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    the limit as delta x tends to 0
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    of 2x + delta x
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    And if delta x is going off to 0,
    this is just 2x and notice that
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    agrees with what we had before.
    When we said that the gradient
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    was 2 times by 3 equal 6 at
    the point where x is equal to 3.
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    Now we could do this
    calculation in just the same
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    way for all kinds of
    different curves, but it
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    would become a bit of a bind
    if we had to keep writing
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    this down all the time. So we
    have a special symbol for
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    this phrase, the limit.
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    as delta x tends to 0 of
    delta y over delta x.
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    And we write that as dy by
    dx and we say d y by d x
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    and that's a symbol all on its
    own as a unit which stands for
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    the limit as delta x tends to 0
    of delta y over delta x,
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    and in the case we've just
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    looked at, y equals X squared,
    dy by dx we've just seen is equal to 2x.
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    Now. Another video in the
    sequence will show how this is
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    done for y equals sine x and the
    processes that we go through.
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    We often use function notation
    y equals f of x.
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    So in function notation,
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    our point P, which
    was the point x, y,
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    becomes the point
    x, f of x.
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    Our point Q, which remember
    was x + delta x, y + delta y
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    Well, this remains as x + delta x
    for the x coordinate,
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    but the y + delta y. Well that's the
    function of x + delta x.
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    And so if we want to have a look
    at what we've done before, if
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    you remember, then we take
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    the change in y, that's delta y.
    So the change in y is:
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    what we had here, at Q,
    minus, what we had at P.
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    So that's f of x + delta x minus f of x,
    and so our gradient delta y over delta x
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    is f of x + delta x minus f of x
    all over delta x.
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    So dy by dx
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    is the limit as delta x tends to 0
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    of the change in y divided
    by the change in x that gave rise to it.
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    Which is the limit
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    as delta x tends to 0
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    of f of x + delta x
    minus f of x all over delta x
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    So, if we are using the language
    of functions. That's the
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    language that we use and
    sometimes for functions when
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    we're differentiating them
    instead of using the symbol
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    dy by dx, sometimes use
    the symbol a dash to indicate
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    that we've differentiated
    with respect to x.
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    Let's just take one
    example using this
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    notation, f of x is equal to the
    function 1 over x.
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    Have a sketch of this curve for
    positive values of x.
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    There it is coming down like
    that. So if I take
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    a point P and I increase
    the value of x by a small
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    amount to give me a second
    point Q on the curve. Then
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    I can see that in fact,
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    there's my delta x.
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    And there's delta y, so for all
    delta x still means a small
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    positive increasing x, delta y
    just means the change in y and
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    we can see that this is actually
    a decrease. Let me complete.
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    This triangle by drawing in
    that secant, PQ and let's
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    have these coordinates,
    this is x, y.
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    And this is. x + delta x
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    and then f of x + delta x.
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    So let's have a look what we've
    got: delta y is the change in y
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    and so it's f of x + delta x
    minus f of x.
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    And so delta y over delta x is
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    f of x + delta x minus f of x,
    all divided by delta x.
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    And this is the gradient of
    this line PQ.
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    OK, what is f of x + delta x
    well, f of x is 1 over x so
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    this is 1 over
    x + delta x.
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    minus f of x, which is just
    1 over x,
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    all divided by
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    delta x.
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    Here we have two fractions and we are
    subtracting them, so we need a
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    common denominator and that
    common denominator will be
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    x times, x + delta x.
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    So I've multiplied this by, this
    x + delta x, I have
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    multiplied it by x, so I must
    multiply the 1 by x.
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    Minus, and I've multiplied the x
    by x + delta x, so I must
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    multiply the 1 by x + delta x
    and then this is all
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    divided by delta x.
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    So let's look at the top, x - delta x,
    minus delta x.
  • 27:52 - 27:58
    So I've got x - x that goes out.
  • 27:59 - 28:05
    And I got on that line there - delta x.
  • 28:06 - 28:11
    All over, well, I'm dividing by
    that, and by that, so effectively
  • 28:11 - 28:14
    I'm dividing by both of them.
  • 28:19 - 28:22
    So there we've got them both
    written down.
  • 28:22 - 28:26
    Now delta x is a small positive quantity,
  • 28:27 - 28:33
    so I can divide top and bottom there
    by delta x, canceling delta x out.
  • 28:36 - 28:50
    So delta y over delta x is equal to
    -1 over, x + delta x, times by x.
  • 28:50 - 28:54
    Let me just multiply that
    denominator out so I
  • 28:54 - 29:01
    have x squared plus
    delta x times by x.
  • 29:03 - 29:13
    dy by dx is equal to the limit
    as delta x tends to 0 of
  • 29:13 - 29:16
    delta y over delta x.
  • 29:17 - 29:22
    Which will be the limit
    as delta x tends to 0
  • 29:23 - 29:31
    of -1 over x squared plus
    delta x times by x.
  • 29:32 - 29:36
    Equals... Let's have a look at
    what's happening in this denominator.
  • 29:36 - 29:47
    As delta x becomes very, very small
    x times by delta x is also very very small
  • 29:47 - 29:51
    and very much smaller than x squared.
  • 29:51 - 29:57
    So as delta x goes off to 0, this term
    here goes away to 0 and
  • 29:57 - 30:00
    just leaves us with the x squared.
  • 30:00 - 30:05
    So our limit is -1 over x squared.
  • 30:07 - 30:11
    And that's our calculation done
    in function notation to find the
  • 30:11 - 30:19
    derivative, as we call dy by dx,
    or the gradient of the curve at a point.
  • 30:20 - 30:24
    Now, the calculations that we've
    done or all quite complicated.
  • 30:25 - 30:28
    You need to do one or two
    to practice the method and
  • 30:28 - 30:33
    to see what's going on with
    it - to see how it's actually working.
  • 30:33 - 30:38
    But, to do most of your differentiation,
    there are a set of rules that you
  • 30:38 - 30:43
    can follow that will help you do the
    differentiation much more quickly.
Title:
www.mathcentre.ac.uk/.../8.1%20Differentiation%201st%20principles%20Tangent.mp4
Video Language:
English
Duration:
30:45

English subtitles

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