Transformations of an unknown function f(x)

Translations and scaling/reflections of an unknown function f(x)

Sine Functions - Sinusoids

Translations and scaling/reflections of the sine and cosine functions

Exponential graph with variable Base

Graph in the form y = k(a^(x+b))+c

Differentiation from First Principles - Visualisation

Visualisation of gradient between two points becoming gradient of curve at a single point

Finding the 'Line of Best Fit'

The linear regression model is based on the sum of the squares of the vertical residuals minimised
How does the gradient (m) and y-intercept (b) of your line affect the residuals?
The Least Squares process to find a 'Line of Best Fit' to model your data depends on minimizing the sum of the squares of the vertical residuals.[br][br]Adjust the gradient and y-intercept values to try and find the best fit, then compare your answer to the linear regression model.[br][br]The six points A-F are also moveable.

Planes defined by Cartesian Equation

The equation of the plane is ax+by+cz=d
Cartesian Equation and axes intercepts
Change the values of the coefficients a, b, c and d.[br][br]What happens when any of a, b, c are zero? Two of them? Three of them?[br][br]What happens when d = 0?

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