Track your progress across all skills in your objective. Mark your confidence level and identify areas to focus on.
Track your progress:
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📖 = included in formula booklet • 🚫 = not in formula booklet
Track your progress:
Don't know
Working on it
Confident
📖 = included in formula booklet • 🚫 = not in formula booklet
Differentiation
Track your progress across all skills in your objective. Mark your confidence level and identify areas to focus on.
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Track your progress:
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Working on it
Confident
📖 = included in formula booklet • 🚫 = not in formula booklet
dxdy is the rate of change of y with respect to x. That is, dxdy tells us how much y changes in response to a change in x.
If y=f(x), then dxdy=f′(x).
The IB may test your understanding of the gradient of the curve as the limit of
as (x2−x1) goes to zero.
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For a curve y=f(x), f′(x) is the gradient or slope.
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You can graph f′(x) using the following steps:
Press the Y=
key.
In one of the available function lines (e.g. Y_1
), enter the expression for f(x).
In another available line (e.g. Y_2
), input the derivative function usingMATH
then 8:nDeriv(
in the following format:
To enter Y1, press VARS
then scroll to Y-VARS
and select FUNCTION
then Y1.
Press GRAPH
to display both the original graph f and the derivative f′.
The graph of f′ may take a little bit longer depending on the original function.
After graphing f′, you may use all the other graphing functions on the calculator (intersect, zero, and value).
The limit x→alimf(x) is the value f(x) approaches as x approaches a.
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Given a table of values:
The product and quotient rules are given by
L:mx+c is tangent to f(x) at x=a means
Using point slope form the equation of the tangent is:
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The normal to f(x) at x=a is the line that passes through (a,f(a)) and is perpendicular to the tangent:
Using point slope form the equation of the tangent is:
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Stationary points are often local extrema.
If f′(a)=0, f is decreasing to the left of a (f′(x)<0), and f is increasing to the right of a (f′(x)>0), then (a,f(a)) is a local minimum.
If f′(a)=0, f is increasing to the left of a (f′(x)<0), and f is decreasing to the right of a (f′(x)>0), then (a,f(a)) is a local maximum.
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Optimisation problems require you to find a minimum or maximum value by producing a function f(x), taking its derivative, solving f′(x)=0, and confirming which stationary point(s) are minima or maxima.
The derivative of the derivative of a function is its second derivative:
Inflexion points occur when f′′(x)=0 and f′′(x) changes sign. 🚫
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We determine concavity by the sign of f′′:
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At a stationary point (f′(a)=0),
If f′′(a)>0, then f has a local minimum at x=a.
If f′′(a)<0, then f has a local maximum at x=a.
Using the second derivative to classify a stationary point is often called the second derivative test.
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When f′ crosses the x-axis f has a maximum (f′′<0) or minimum (f′′>0)
When f′′ crosses the x-axis, f has an inflexion point.