Probability & Statistics

Probability and Statistics is a branch of mathematics dealing with the analysis of random phenomena. Coursera's Probability & Statistics skill catalogue teaches you to understand, analyze, and interpret data, patterns, and statistical relationships. You'll learn key concepts such as mean, median, mode, variance, standard deviation, correlation, regression, probability distributions, and hypothesis testing. You will also explore more complex concepts like Bayesian inference, predictive modeling, and machine learning. These skills are crucial for a broad range of fields including data science, economics, engineering, and social sciences.

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Results for "Probability & Statistics"

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

  • Skills you'll gain: A/B Testing, Sampling (Statistics), Data Analysis, Analytics, Statistics, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Probability & Statistics, Advanced Analytics, Probability Distribution, Data Science, Statistical Inference, Statistical Programming, Statistical Methods, Probability, Python Programming

  • Skills you'll gain: Descriptive Statistics, Data Visualization, Statistical Analysis, Data Presentation, Data Analysis, Probability Distribution, Statistics, Statistical Methods, Statistical Hypothesis Testing, Data Science, Statistical Programming, Data Visualization Software, Probability & Statistics, Jupyter, Regression Analysis, Statistical Modeling, Descriptive Analytics, Statistical Inference, Correlation Analysis, Probability

  • Skills you'll gain: Python Programming, Algorithms, Computer Programming, Theoretical Computer Science, Linear Algebra, Mathematics and Mathematical Modeling, Computer Science, Algebra, Object Oriented Programming (OOP), IBM Cloud, Scripting, Probability, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Mathematical Modeling, Data Structures, Data Manipulation, Probability & Statistics, Applied Mathematics, Software Installation

  • Skills you'll gain: Enterprise Risk Management (ERM), Derivatives, Risk Modeling, Risk Management Framework, Portfolio Risk, Financial Market, Credit Risk, Risk Analysis, Financial Trading, Operational Risk, Statistical Modeling, Risk Management, Financial Modeling, Market Liquidity, Correlation Analysis, Statistical Methods, Probability & Statistics, Market Dynamics, Risk Mitigation, Statistical Analysis

  • American Psychological Association

    Skills you'll gain: Sample Size Determination, Statistical Hypothesis Testing, Probability & Statistics, Statistical Methods, Probability Distribution, Statistical Reporting, Statistical Analysis, Quantitative Research, Statistical Software, Correlation Analysis, Statistical Inference, Statistics, Sampling (Statistics), Data Analysis, Analysis, Probability, Analytical Skills, Regression Analysis, Psychology, Research

  • From the course: Prepare for CFA Level 1: Quantitative Methods and Returns·Lesson: Probability Trees and Conditional Expectations

  • From the course: Lean Six Sigma Green Belt Training·Lesson: Probability and Statistics

  • From the course: Discrete-Time Markov Chains and Monte Carlo Methods·Lesson: Conditional Probability for Events and Random Variables

  • Skills you'll gain: Logistic Regression, SAS (Software), Statistical Hypothesis Testing, Statistical Software, Statistical Analysis, Predictive Modeling, Statistical Programming, Statistical Modeling, Statistical Methods, Regression Analysis, Statistical Inference, Probability & Statistics

  • Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistical Methods, Statistics, Statistical Analysis, Data Analysis, Sampling (Statistics), Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference

  • From the course: Deep Learning - Crash Course 2023·Lesson: Basic Probability