Overview

Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today's technology, it's possible to analyze your data and get answers from it almost immediately - an effort that's slower and less efficient with more traditional business intelligence solutions. MATLAB has the tools to work with large datasets and apply the necessary data analysis techniques. This book develops the work with MATLAB for model and fit data to probabuility distributions. Fit probability distributions to sample data, evaluate probability functions such as pdf and cdf, calculate summary statistics such as mean and median, visualize sample data, generate random numbers, and more. Work with probability distributions using probability distribution objects, command line functions, or interactive apps. Probability distributions are theoretical distributions based on assumptions about a source population. The distributions assign probability to the event that a random variable has a specific, discrete value, or falls within a specified range of continuous values. MATLAB Statistics and Machine Learning Toolbox offers several ways to work with probability distributions. Use Probability Distribution Objects to fit a probability distribution object to sample data, or to create a probability distribution object with specified parameter values. Use Probability Distribution Functions to work with data input from matrices, tables, and dataset arrays. Use Probability Distribution Apps and User Interfaces to interactively fit, explore, and generate random numbers from probability distributions. Available apps and user interfaces include: The Distribution Fitter app The Probability Distribution Function user interface The Random Number Generation user interface (randtool)

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9781976229176

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