# HL AI – Probability

## Venn diagrams

## Probability 2

## Normal distributions

## Errors

## Probability 1

## Discrete Probability

## Poisson Distribution

## Review

## Tree diagrams

## Binomials

## Confidence Levels

## Traffic Light Coding for Unit

Make your own copy and share with your students.

##### Learning Outcomes

Understand set notation for number, union, intersection, contained in, element, inverse, null and universal. |

Be able to draw and shade Venn diagrams with the use of set notation. |

Solve problems by use of sets and Venn diagrams. |

Understand the the terms mutually exclusive and independent. |

Find simple probabilities involving one or two events, using the terms AND and OR. |

Draw tree diagrams to represent probabilities. |

Use the independence formulae to solve problems of independent probability. |

Find conditional, or ‘given that’ probabilities. |

Use Venn diagrams to solve probability problems. |

Draw and interpret tree diagrams, using them for conditional and independent events. |

Discrete random variables and their probability distributions. |

Expected value (mean) for discrete standard variables. |

Binomial distributions, including mean and variance of these distributions. |

Normal distribution diagrammatic representation and using this for non-GDC calculations. |

Using a GDC to find probabilities based on knowing the mean and standard deviation. |

Finding z-values with normal distributions, and using for inverse calculations. |

Poisson distributions, mean, variance, and sums of poisson distributions. |

Confidence intervals for normal distributions with and without a known standard deviation. |

Test for critical values and regions with normal distributions. |

Calculating Type I and Type II errors, includes link with Statistics module. |