Covariance and Correlation- Covariance and correlation both measure linear relationship between two variables. However, they differ at some points. In this post I will explain covariance and correlation and how they differ from each other. Covariance between two variables is written as Cov(X,Y) and is defined as Calculation of Covariance If you look at the […]
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Variance of a Continuous Random Variable If X is a random variable having mean μ , then variance of random variable X is denoted as Var(X) and read as variance of X and defined as. Var(X)=E[(X-μ)²] Where Variance of a random variable measures dispersion, that means how for values spread out from mean or expected
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Expectation of a Continuous Random Variable Expectation of a continuous random variable is defined as Suppose a continuous random variable X is uniformly distributed on [a, b]. Density function of uniformly distributed random variable X is Expectation of uniformly distributed random variable X is See Video See Also: Expectation in Statistics Expectation of a Discrete
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Mathematical or Classical Probability- If a random experiment is conducted which results in n exhaustive, mutually exclusive, and equally likely outcomes and there are m favorable cases of occurrence of an event E. Then probability of happening event E is P(E)=m/n Suppose you are tossing a coin and want to get probability of getting head
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1-Random Experiment- If an experiment is conducted then the outcome will not be unique but it may be from possible list of outcomes. Example- If you are tossing two coins the possible outcomes would be {TT, TH, HT,HH}. 2- Events- Outcome of a random experiment is called events, if you are tossing two coins then
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