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IBDP Math AI: Functions, Statistics, and Geometry

Master key concepts for IBDP Math Applications and Interpretation, including linear models, bivariate statistics, Voronoi diagrams, and hypothesis testing.

20 cards

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#1

Front

Linear Regression Model Equation

Back

The equation of the line of best fit is $y = ax + b$, where $a$ is the slope (gradient) and $b$ is the y-intercept. On the GDC, this is derived from two-variable statistics to model the trend between dependent ($y$) and independent ($x$) variables.

#2

Front

Pearson’s Product-Moment Correlation Coefficient ($r$)

Back

A measure of the strength and direction of a linear association between two variables. The value ranges from $-1$ to $1$. If $r = 1$ or $-1$, it indicates a perfect linear relationship. If $r = 0$, there is no linear correlation.

#3

Front

Interpreting the Coefficient of Determination ($R^2$)

Back

$R^2$ represents the proportion of the variance in the dependent variable ($y$) that is predictable from the independent variable ($x$). For example, if $R^2 = 0.85$, then 85% of the variation in $y$ is explained by the model, while 15% is due to other factors.

#4

Front

Voronoi Diagrams: Key Definitions

Back

A Voronoi diagram partitions a plane into regions based on distance to points in a specific subset of the plane (seeds). Each region (cell) consists of all points closer to one seed than to any other. The boundaries are called perpendicular bisectors.

#5

Front

Missing Data in Voronoi Diagrams

Back

To find the coordinates of a missing site (seed) in a Voronoi diagram: 1. Identify the vertices of the missing cell. 2. The missing site is the circumcenter of the triangle formed by the vertices of that cell. 3. Use perpendicular bisectors of the triangle's sides to locate the center.

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