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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
      I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Generative AI, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Data Cleansing, Data Access, Deep Learning, Data Analysis, Applied Machine Learning, Predictive Modeling, Statistical Analysis, Statistical Inference, Statistical Hypothesis Testing, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 3 - 6 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

    • C

      Coursera Project Network

      Basic Statistics in Python (Correlations and T-tests)

      Skills you'll gain: Exploratory Data Analysis, Box Plots, Correlation Analysis, Data Visualization, Scatter Plots, Data Cleansing, Data Manipulation, Pandas (Python Package), Statistical Hypothesis Testing, Descriptive Statistics, Statistical Analysis, Data Analysis, Probability & Statistics, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      34 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U
      I
      I

      Multiple educators

      Data Science Foundations

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

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

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      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
      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, Machine Learning Algorithms, Plotly, 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

      Arizona State University

      Design of Experiments

      Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Design Strategies, Probability & Statistics, Data Analysis, Mathematical Modeling, Data Transformation, Descriptive Statistics, Probability Distribution, Statistical Hypothesis Testing, Variance Analysis, Quality Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      360 reviews

      Beginner · Specialization · 3 - 6 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
      Status: AI skills
      AI skills
      M

      Meta

      Meta Marketing Analytics

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Marketing Analytics, Bayesian Statistics, Descriptive Statistics, Marketing Effectiveness, Statistical Hypothesis Testing, Target Audience, Marketing Strategies, Data Cleansing, Pandas (Python Package), Data Modeling, Data Analysis, Data Visualization Software, Spreadsheet Software, A/B Testing, Data Collection, Marketing, Interviewing Skills

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.8K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Statistics for Genomic Data Science

      Skills you'll gain: Biostatistics, Bioinformatics, Exploratory Data Analysis, Statistical Analysis, Statistical Methods, Statistical Hypothesis Testing, Statistical Modeling, R Programming, Probability & Statistics, Statistical Inference, Regression Analysis, Data Pipelines, Data Transformation, Data Processing

      4.2
      Rating, 4.2 out of 5 stars
      ·
      373 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Amsterdam

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sampling (Statistics), Probability & Statistics, Regression Analysis, Statistical Inference, Statistical Analysis, Quantitative Research, Probability Distribution, R Programming

      4.3
      Rating, 4.3 out of 5 stars
      ·
      598 reviews

      Mixed · Course · 1 - 3 Months

    Searches related to statistics

    statistics with python
    statistics for data science
    statistics with r
    statistics for data analysis
    statistics for data science with python
    statistics in psychological research
    statistics for business
    statistics foundations
    1…456…106

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

    • IBM Machine Learning: IBM
    • Bayesian Statistics: Duke University
    • Basic Statistics in Python (Correlations and T-tests): Coursera Project Network
    • Data Science Foundations: University of London
    • Basic Inferential Statistics for Psychology: American Psychological Association
    • Mathematics for Machine Learning: Imperial College London
    • Data Science: Johns Hopkins University
    • Design of Experiments: Arizona State University
    • Statistics for Data Science Essentials: University of Pennsylvania
    • Meta Marketing Analytics: Meta

    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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