# Counting and Probability - Introduction

You've probably heard people say things like:

Teen mother

- The
**chance**of rain tomorrow is 75%. - Teen mothers who live with their parents are
**less likely**to use marijuana than teen moms in other living arrangements. - He won the lottery!
- There is longstanding evidence that children raised by single parents are
**more likely**to perform poorly in school and partake in ‘deviant’ behaviors such as smoking, sex, substance use and crime at young ages. [Source] - She'll
**probably**take the offer. - Life insurance is so expensive for someone over 50.

All of these statements are about **probability**. We see words like "chance", "less likely", "probably" since we don't know for sure something will happen, but we realise there is a very good chance that it will.

In the case of the lottery (or Toto), there is a very good chance that some things (like a win) will not happen!

To decide "how likely" an event is, we need to count the number of times an event could occur and compare it to the total number of possible events. Such a comparison is called the **probability **of the particular event occurring.

The mathematical theory of counting is known as **combinatorial analysis**.

## In this Chapter

### Counting

### Probability

### Probabilities of 2 or more Events

- 7. Conditional Probability
- 8. Independent and Dependent Events
- 9. Mutually Exclusive Events
- 10. Bayes’ Theorem

### Probability Distributions

- 11. Probability Distributions - Concepts
- 12. Binomial Probability Distributions
- 13. Poisson Probability Distribution
- 14. Normal Probability Distribution

We begin the chapter with a reminder about Factorial Notation »

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