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Integrating standard functions
Integrating f(ax + b)
Integration with trigonometric identities
Reverse chain rule
Integration by substitution
Integration by parts
Integration using partial fractions
Finding areas using integration
The trapezium rule
Solving differential equations
Modelling with differential equations
Differentiating sin x and cos x
Differentiating exponentials and logarithmic functions
The chain rule
The product rule
The quotient rule
Differentiating inverse functions
Differentiating trigonometric functions
Parametric differentiation
Implicit differentiation
Second derivatives: Concave and convex functions
Connected rates of change
Quantitative or numerical data can be categorised into discrete or continuous data. Data that can take any value within a given range is continuous data, e.g. "Time taken". Data that can only have specific values is called discrete data, e.g. "Number of students in a class".
Qualitative data is data which has a non-numerical value, e.g. "eye colour" or "type of plant". Quantitative data is data which has a numerical value, e.g. "Number of students" or "Time taken to run a race."
Data can be categorised as qualitative or quantitative. Within quantitative data, numerical data can be categorsied as either discrete or continuous.
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