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Covers sample space, Venn diagrams, probability rules, and conditional probability.
Probability is a fundamental concept in Additional Mathematics that deals with the likelihood of events occurring. It's essential to understand probability rules and conditional probability to make informed decisions in various aspects of life.
A sample space is the set of all possible outcomes of an experiment or random phenomenon. It represents the entire population under consideration. For example, if we are tossing a coin, the sample space would be {heads, tails}.
An event is a subset of the sample space that contains one or more outcomes. The probability of an event is a number between 0 and 1 that represents the likelihood of the event occurring. It can be calculated using the formula P(event) = (number of favorable outcomes) / (total number of outcomes).
The probability of an event is additive, meaning that the probability of one or more events occurring is the sum of their individual probabilities. The probability of an event is also non-negative and does not exceed 1. Additionally, the probability of the certain event (the sample space) is always 1.
Two events are independent if the occurrence or non-occurrence of one event has no effect on the probability of the other event. The probability of both events occurring is the product of their individual probabilities, P(event A and event B) = P(event A) × P(event B).
Two events are dependent if the occurrence or non-occurrence of one event affects the probability of the other event. The probability of both events occurring is not simply the product of their individual probabilities, but rather requires considering the conditional probability.
The conditional probability of an event given another event is the probability that the first event occurs, given that the second event has occurred. It can be calculated using the formula P(event A | event B) = P(event A and event B) / P(event B).
Bayes' theorem is a mathematical formula used to update the probability of an event based on new information. It states that P(event A | event B) = P(event B | event A) × P(event A) / P(event B).
A Venn diagram is a graphical representation of sets and their relationships. It consists of overlapping circles, each representing a set or event. The intersection of two circles represents the event that occurs when both events occur.
Probability has numerous real-world applications in fields such as insurance, finance, medicine, and engineering. For example, it is used to calculate the risk of natural disasters, predict stock market trends, and determine the effectiveness of medical treatments.
What is the range of values that a probability can take?
What is the sum of the probabilities of all possible outcomes in a sample space?
What is the probability of an event occurring given that another event has occurred?
Are events that occur independently of each other classified as?
What is the probability rule for independent events?
What is the probability of an event occurring if it's equally likely to occur or not?
What is the probability rule for dependent events?
What is the formula to calculate conditional probability?
What is the probability of an event occurring if it's equally likely to occur or not, and the events are independent?
Explain how probability is used in finance to make informed decisions about investments. (Marks: 20, Key Points: The probability of an event occurring is the number of favorable outcomes divided by the total number of possible outcomes; Independent events are those where the occurrence of one event does not affect the probability of another event.) ( marks)
Discuss how conditional probability is used in medicine to predict the effectiveness of a treatment. (Marks: 20, Key Points: The probability of an event occurring given that another event has occurred; Conditional probability is used to update the probability of an event based on new information.) ( marks)