Random Variables Part 5

A random variable is a fundamental concept in probability and statistics. It is essentially a numerical value assigned to the outcomes of a random experiment, where the value depends on chance. In simpler terms, it's a variable whose values are outcomes of a random phenomenon. Types of Random Variables - Discrete Random Variables: These take on a countable number of distinct values. For example, the number of heads when flipping a coin three times can be a discrete random variable. - Continuous Random Variables: These can take any value within a specified range or interval. For instance, the height of students in a class or the time taken to run a race. Properties of Random Variables - Expected Value (Mean): Represents the average value or central tendency of the random variable over many trials of the experiment. - Variance: Measures the spread or dispersion of the values of the random variable, indicating how far they tend to be from the mean. - Probability Distribution: Defines how probabilities are distributed across the values of the random variable (e.g., Probability Mass Function for discrete variables, Probability Density Function for continuous variables). - Independence: Two random variables are independent if the outcome of one does not affect the outcome of the other. - Additivity: The sum of expected values of two random variables equals the expected value of their sum. Random variables part-4 https://youtu.be/LiLZqurRKJk 👆 Keep watching my videos @statisticswithgeetha7794