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Not your average video:
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Exam Preparation: Complete unit reviews designed for final exam preparation with all key concepts covered systematically.
Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.
Distributions & Random Variables
Watch comprehensive video reviews for Distributions & Random Variables, designed for final exam preparation. Each video includes integrated problems you can solve alongside detailed solutions.
Not your average video:
Interactive Problems: Solve problems alongside the video with step-by-step guidance and detailed solutions.
Exam Preparation: Complete unit reviews designed for final exam preparation with all key concepts covered systematically.
Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.
Not your average video:
Interactive Problems: Solve problems alongside the video with step-by-step guidance and detailed solutions.
Exam Preparation: Complete unit reviews designed for final exam preparation with all key concepts covered systematically.
Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.
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SL 4.7
A discrete random variable takes from a finite set of values:
Each possible value has an associated probability. These are often presented in a table:
Notice that the row of probabilities add to 0.3+0.5+0.2=1. This is called the law of total probability, and captures the since X must be one of these values, the probability of X being one of these values is 1.
Example
Find the value of k in the following probability distribution
By the law of total probability:
SL 4.7
A discrete random variable takes from a finite set of values:
Each possible value has an associated probability. These are often presented in a table:
Notice that the row of probabilities add to 0.3+0.5+0.2=1. This is called the law of total probability, and captures the since X must be one of these values, the probability of X being one of these values is 1.
Example
Find the value of k in the following probability distribution
By the law of total probability: