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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

    • Status: Free Trial
      Free Trial
      A

      American Psychological Association

      Statistics in Psychological Research

      Skills you'll gain: Descriptive Statistics, Plot (Graphics), Graphing, Statistical Visualization, Statistical Hypothesis Testing, Probability & Statistics, Statistical Inference, Quantitative Research, Statistics, Sample Size Determination, Data Analysis, Scatter Plots, Psychology, Research Design, Experimentation, Scientific Methods

      4.6
      Rating, 4.6 out of 5 stars
      ·
      50 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Bayesian Statistics

      Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Data-Driven Decision-Making, Probability Distribution

      3.8
      Rating, 3.8 out of 5 stars
      ·
      797 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Statistical Inference

      Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics), Sample Size Determination, Data Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Statistics For Data Science

      Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference

      3.9
      Rating, 3.9 out of 5 stars
      ·
      33 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      A

      American Psychological Association

      Basic Inferential Statistics for Psychology

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Zurich

      An Intuitive Introduction to Probability

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

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.9K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Statistics for Data Science Essentials

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I
      U
      I

      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Correlation Analysis, Web Scraping, NumPy, Python Programming, Probability & Statistics, Data Structures, Predictive Modeling, Big Data, Data Visualization Software, Data Collection, Data Science, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      113K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with Python

      Skills you'll gain: Predictive Modeling, Exploratory Data Analysis, Data Wrangling, Data Analysis, Data Import/Export, Pandas (Python Package), Statistical Modeling, Data-Driven Decision-Making, Data Manipulation, Scikit Learn (Machine Learning Library), Regression Analysis, Feature Engineering, Matplotlib, Data Cleansing, NumPy, Descriptive Statistics, Supervised Learning, Data Pipelines

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to statistics

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    1…456…107

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

    • Statistics in Psychological Research: American Psychological Association
    • Bayesian Statistics: Duke University
    • Statistical Inference: Johns Hopkins University
    • Statistics For Data Science: Coursera Project Network
    • Mathematics for Machine Learning: Imperial College London
    • Data Science: Johns Hopkins University
    • Basic Inferential Statistics for Psychology: American Psychological Association
    • Algorithms: Stanford University
    • An Intuitive Introduction to Probability: University of Zurich
    • Statistics for Data Science Essentials: University of Pennsylvania

    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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