Archives for normal distribution
The Central Limit Theorem (CTL) in statistics states that, regardless of the distribution of the variable in the population, the sampling distribution of the mean will approximate a normal distribution with a sufficiently large sample size.
Different distributions of data and their properties is one such area of statistics in which a data scientist has to have crystal clear clarity.
In the field of unsupervised learning, probabilistic models which represent the probability of the presence of clusters within the overall population can be considered as mixture model.
Probability distributions are important in machine learning and data analysis. Not only data scientists but also also researchers and scientists from many other fields deal with probability distributions on a day to day basis. To put it simply, probability distribution is a simply a function which informs us of the likelihood of obtaining the possible […]
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