**Probability
Theory** |
**Description** |

Introduction to
Probability |
To
introduce probability theory through simple experiments. To
use the formula for finding
the probability of an event. To find the probabilities of events with equally
likely and non-equally likely outcomes. |

Certain and Impossible Events |
To
understand the theory behind certain and impossible events. To
classify experiments accordingly. To compute
related probabilities. |

Sample Spaces |
To determine the sample space of an experiment by
examining each possible outcome. |

The Complement of an Event |
To define
and identify the complement of an event. To find related probabilities. |

Mutually Exclusive Events |
To understand the
theory behind mutually exclusive and non-mutually exclusive events. To classify an experiment
accordingly. Venn
diagrams and other visuals are used. |

Addition Rules for Probability |
To find the
probability of mutually exclusive events by applying the addition rule. |

Independent Events |
To
understand the theory behind independent events. To use the multiplication rule to
compute related probabilities. |

Dependent Events |
To
understand the theory behind dependent events. To use a modified version of the multiplication rule to
compute related probabilities. |

Conditional Probability |
To
understand the theory behind conditional probability. To derive the formula for finding conditional
probabilities, and to compute related probabilities. |

Practice Exercises |
To complete 10 additional
exercises as practice. To assess students' understanding of all
probability theory presented. |

Challenge Exercises |
To solve 10
additional problems that challenge students' understanding of
probability theory. Problems
are drawn from real-life situations. To hone students' problem-solving skills. |

Solutions |
To review complete
solutions to all exercises in this unit. Includes the problem,
step-by-step solutions, and final answer for each exercise. |