**Unit 5**

Topics:

**Remarks on the Concept of “Probability” **link:Probability Intro

- Learning Objectives

- Define symmetrical outcomes
- Distinguish between frequentist and subjective approaches
- Determine whether the frequentist or subjective approach is better suited for a given situation

**Basic Concepts **link:Basic Concepts

- Learning Objectives

- Compute probability in a situation where there are equally-likely outcomes
- Apply concepts to cards and dice
- Compute the probability of two independent events both occurring
- Compute the probability of either of two independent events occurring
- Do problems that involve conditional probabilities
- Compute the probability that in a room of N people, at least two share a birthday

**Permutations and Combinations **link:Permutations and Combinations

- Learning Objectives

- Calculate the probability of two independent events occurring
- Define permutations and combinations
- List all permutations and combinations
- Apply formulas for permutations and combination
- Describe the gambler’s fallacy

**Binomial Distribution **link:Binomial Distribution

- Learning Objectives

- Define binomial outcomes
- Compute the probability of getting X successes in N trials
- Compute cumulative binomial probabilities
- Find the mean and standard deviation of a binomial distribution

**Poisson Distribution **link:Poisson

- Learning Objectives

- Use the Poisson distribution to calculate the probabilities of various numbers of “successes” based on the mean number of successes

**Multinomial Distribution **link:Multinomial

- Learning Objectives

- Define multinomial outcomes
- Compute probabilities using the multinomial distribution

**Hypergeometric Distribution **link:Hypergeometric

- Learning Objectives

- Use the hypergeometric distribution to calculate probabilities when sampling without replacement

**Base Rates **link:Base Rates

- Learning Objectives

- Compute the probability of a condition from hits, false alarms, and base rates using a tree diagram
- Compute the probability of a condition from hits, false alarms, and base rates using Bayes’ Theorem

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