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Probability Calculation for Discrete Probability Functions

We will cover following topics

Introduction

In the realm of probability theory, the ability to calculate the likelihood of different events occurring is crucial. A discrete probability function provides a systematic way to assign probabilities to individual outcomes. In this chapter, we’ll explore how to calculate the probability of specific events using a discrete probability function. By mastering this skill, you’ll gain the foundation to make informed decisions in scenarios where uncertainty plays a role.


Discrete Probability Functions

A discrete probability function, often denoted as $P(X)$, is a mathematical model that assigns probabilities to discrete outcomes of a random variable $X$. Each outcome is associated with a certain probability, and the probabilities for all possible outcomes sum up to 1.

To calculate the probability of a particular event A occurring, we use the formula: $P(A)=\frac{\text { Number of favorable outcomes for event A }}{\text { Total number of possible outcomes }}$

Example: Consider a standard six-sided die. The event $\mathrm{A}$ is rolling an even number. There are three favorable outcomes (2, 4 and 6), and the total number of possible outcomes is six. Therefore, the probability of event $\mathrm{A}$ is:

$$P(A)=\frac{3}{6}=\frac{1}{2}$$


Calculating Joint Probabilities

For two events A and B, the joint probability of both events occurring can be calculated using the formula:

$$P(A \cap B)=P(A) \times P(B \mid A)$$

Example: Let’s take the example of drawing two cards from a standard deck of 52 playing cards. Event $A$ is drawing a red card on the first draw, and event $B$ is drawing a red card on the second draw after the first draw resulted in a red card. If we draw without replacement, the probability of event $\mathrm{A}$ is $P(A)=\frac{26}{52}$. After drawing a red card, there are 25 red cards left in a deck of 51 cards, so the probability of event $B$ given that event $A$ has occurred is $P(B \mid A)=\frac{25}{51}$. Therefore, the joint probability of both events is:

$$P(A \cap B)=P(A) \times P(B \mid A)=\frac{26}{52} \times \frac{25}{51}$$


Conclusion

Calculating probabilities using a discrete probability function is an essential skill in the field of probability and statistics. It enables us to quantify the likelihood of specific outcomes and events. By understanding the formulas and concepts discussed in this chapter, you’ll be better equipped to analyze uncertain situations and make well-informed decisions based on the probabilities associated with different events.


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