Probability Distribution

Probability Distribution is a statistical function that describes all the possible values and likelihoods that a random variable can take within a given range. Coursera's Probability Distribution catalogue teaches you the fundamental concepts of probability theory, including the properties and types of probability distributions like Binomial, Normal, and Poisson distributions. You'll learn about concepts such as expected values, variance, standard deviation, and moments. You'll also learn how to use these distributions to make predictions, analyze data, and solve real-world problems in various fields such as engineering, data science, economics, and risk management. The knowledge gained will allow you to model uncertainties and understand the underlying patterns in complex datasets.
36credentials
2online degrees
121courses

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Explore the Probability Distribution Course Catalog

  • Status: Preview

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Descriptive Statistics, Applied Mathematics, Risk Analysis, Finance

  • Status: Free Trial

    Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistical Methods, Data Analysis, Statistical Inference, Statistical Analysis, Artificial Intelligence

  • Status: Free Trial

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

  • Status: New
    Status: Free Trial

    University of Colorado Boulder

    Skills you'll gain: Probability, Statistical Inference, Estimation, Probability & Statistics, Probability Distribution, Statistical Methods, Statistics, Markov Model, Bayesian Statistics, Data Literacy, Statistical Analysis, Sampling (Statistics), Applied Mathematics, Artificial Intelligence, Generative AI, Data Analysis, Data Science, Theoretical Computer Science, Machine Learning Algorithms, Mathematical Theory & Analysis

  • Status: Free Trial

    Skills you'll gain: R Programming, Statistical Analysis, Combinatorics, Data Analysis, Probability, Statistics, Probability Distribution, Probability & Statistics, Bayesian Statistics, Applied Mathematics, Data Science, Artificial Intelligence and Machine Learning (AI/ML), Simulations

  • Status: New
    Status: Free Trial

    Skills you'll gain: Natural Language Processing, Deep Learning, Large Language Modeling, Text Mining, Semantic Web, Generative AI, PyTorch (Machine Learning Library), Artificial Neural Networks, Python Programming, Cryptography, Generative Model Architectures, Applied Machine Learning, Machine Learning Methods, Unsupervised Learning, Probability Distribution, Machine Learning Algorithms, Algorithms

What brings you to Coursera today?

  • Status: New
    Status: Free Trial

    Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Linear Algebra, Applied Machine Learning, Unsupervised Learning, Regression Analysis, Statistical Methods, Artificial Intelligence and Machine Learning (AI/ML)

  • Status: Free Trial

    Stanford University

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Statistical Inference, Sampling (Statistics), Statistical Methods, Unstructured Data, Natural Language Processing, Algorithms, Computational Thinking, Test Data

  • Status: New
    Status: Free Trial

    Johns Hopkins University

    Skills you'll gain: Algebra, Graphing, Applied Mathematics, Mathematical Modeling, Trigonometry, Probability, Advanced Mathematics, Data Analysis, Logical Reasoning, General Mathematics, Probability Distribution, Mathematical Theory & Analysis, Descriptive Statistics, Arithmetic, Statistics, Engineering Calculations, Calculus, Visualization (Computer Graphics), Geometry, Analytical Skills

  • Status: Free Trial

    Skills you'll gain: Probability, Statistical Hypothesis Testing, Statistical Inference, Probability & Statistics, Probability Distribution, Statistical Methods, Statistics, Bayesian Statistics, Data Literacy, Sampling (Statistics), Applied Mathematics, Data Ethics, Data Analysis, Statistical Analysis, Quantitative Research, Data Science, Theoretical Computer Science, Sample Size Determination, Artificial Intelligence

  • Status: Preview

    Stanford University

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

  • Status: Free Trial

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Data Transformation