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    Statistics Courses

    Statistics courses can help you learn how to collect, analyze, and interpret data to make informed decisions in fields like science, business, and healthcare.

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    Find the Best Statistics Course for Your Goals

    • G

      Google

      The Power of Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      780 reviews

      Advanced · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Advanced Statistics for Data Science

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling, Sample Size Determination

      4.4
      Rating, 4.4 out of 5 stars
      ·
      761 reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Presentation, Data Visualization Software, Sampling (Statistics), Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Probability Distribution, Statistical Methods, Applied Machine Learning, Object Oriented Programming (OOP), Data Analysis

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • S

      Stanford University

      Probabilistic Graphical Models

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Hardware Architecture, Systems Architecture, Artificial Intelligence, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • I

      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Visualization, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      319 reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Presentation, Data Analysis, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Ethics, Business Workflow Analysis, Stakeholder Communications, Professional Networking, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Advanced · Course · 1 - 3 Months

    • G

      Google

      Regression Analysis: Simplify Complex Data Relationships

      Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Advanced Analytics, Correlation Analysis, Data Analysis, Predictive Modeling, Statistical Modeling, Supervised Learning, Variance Analysis, Machine Learning Methods, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      519 reviews

      Advanced · Course · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Bayesian Network, Bayesian Statistics, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      488 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics: Capstone Project

      Skills you'll gain: Bayesian Statistics, Technical Communication, R Programming, Statistical Analysis, Statistical Modeling, Data Analysis, Advanced Analytics, Time Series Analysis and Forecasting, Markov Model, Statistical Methods, Predictive Modeling, Sampling (Statistics), Probability Distribution

      Advanced · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Probabilistic Deep Learning with TensorFlow 2

      Skills you'll gain: Generative AI, Tensorflow, Deep Learning, Image Analysis, Bayesian Statistics, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Dimensionality Reduction

      4.7
      Rating, 4.7 out of 5 stars
      ·
      108 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Columbia University

      Causal Inference

      Skills you'll gain: Statistical Inference, Regression Analysis, Statistical Methods, Estimation, Statistical Modeling, Machine Learning, Experimentation, Data Collection, Probability & Statistics, Research Design, Program Evaluation, Decision Making

      3.4
      Rating, 3.4 out of 5 stars
      ·
      99 reviews

      Advanced · Course · 1 - 3 Months

    Searches related to statistics

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    12345

    In summary, here are 10 of our most popular statistics courses

    • The Power of Statistics: Google
    • Advanced Statistics for Data Science: Johns Hopkins University
    • Google Advanced Data Analytics: Google
    • Probabilistic Graphical Models: Stanford University
    • Self-Driving Cars: University of Toronto
    • IBM AI Enterprise Workflow: IBM
    • Foundations of Data Science: Google
    • Regression Analysis: Simplify Complex Data Relationships: Google
    • Probabilistic Graphical Models 2: Inference: Stanford University
    • Bayesian Statistics: Capstone Project: University of California, Santa Cruz

    Why Learn Statistics?

    Statistics is the science of collecting, analyzing, and interpreting data to uncover patterns and inform decisions. It’s essential in fields like business, healthcare, social science, and data analytics. Learning statistics can help you make sense of data, support evidence-based thinking, and contribute to smarter outcomes in any field.

    Frequently Asked Questions about Statistics

    Top statistics courses include Introduction to Statistics from Stanford University, Business Statistics and Analysis from Rice University, and Statistics with Python from the University of Michigan. These courses cover descriptive statistics, probability, hypothesis testing, and statistical modeling.‎

    Yes. Many statistics courses offer a free audit option, allowing you to access video lessons and reading materials without payment. If you want to complete assignments or earn a certificate, you’ll need to pay or apply for financial aid.‎

    You’ll learn how to collect, interpret, and present data; calculate key metrics like mean and standard deviation; and apply statistical techniques such as regression analysis, probability distributions, and confidence intervals. Some courses also include hands-on practice with Excel, R, or Python.‎

    Not necessarily. Many Coursera statistics courses are designed for beginners and explain core concepts step by step. Some basic comfort with numbers is helpful, but you don’t need advanced math experience to get started.‎

    Yes. Statistics is essential in fields like business, healthcare, data science, psychology, and research. Learning statistics on Coursera can help you analyze data, make informed decisions, and gain skills that are valuable in both academic and professional settings.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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