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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: New
      New
      Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistics and Data Analysis with R

      Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Regression Analysis, Statistical Programming, Probability Distribution, Statistical Analysis, R Programming, Data Import/Export, Statistical Modeling, Statistical Methods, Plot (Graphics), Statistics, Data Manipulation, Analysis, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Stanford University

      Game Theory

      Skills you'll gain: Game Theory, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Behavioral Economics, Probability, Economics, Markov Model, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Bayesian Statistics: Time Series Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Statistical Modeling, Statistical Analysis, Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      16 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Using Descriptive Statistics to Analyze Data in R

      Skills you'll gain: Descriptive Statistics, R Programming, Statistical Reporting, Data Quality, Data Cleansing, Statistical Methods, Data Manipulation, Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      93 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      R Programming

      Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      22K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Statistical Programming, Data Visualization Software, Data Cleansing, Data Manipulation, Exploratory Data Analysis, Data Import/Export, Package and Software Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Kinesiology, Injury Prevention, Statistical Machine Learning, Analytics, Data Analysis, Statistical Analysis, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      257 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Visualization, SQL, Predictive Modeling, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Big Data, Matplotlib, Statistical Analysis, Pandas (Python Package), IBM Cognos Analytics, Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Predictive Modeling, Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Flask (Web Framework), Exploratory Data Analysis, Data Wrangling, Unit Testing, Natural Language Processing, ChatGPT, Data Analysis, Jupyter, Artificial Intelligence, Unsupervised Learning, PyTorch (Machine Learning Library), OpenAI

      4.6
      Rating, 4.6 out of 5 stars
      ·
      87K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Software Engineering Fundamentals

      Skills you'll gain: Software Development Life Cycle, Software Architecture, Linux Commands, Bash (Scripting Language), Shell Script, Git (Version Control System), GitHub, Flask (Web Framework), Software Design, Unit Testing, Version Control, File Management, Jupyter, Scrum (Software Development), Application Development, Application Deployment, Python Programming, Data Structures, Collaborative Software, Web Scraping

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Survey Data Collection and Analytics

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Surveys, Survey Creation, Research Methodologies, Data Collection, Statistical Analysis, Statistical Software, Interviewing Skills, Data Integration, Data Ethics, Research Design, Stata, R Programming, Data Quality, Statistical Modeling, Qualitative Research, Descriptive Statistics, Statistical Programming, Data Cleansing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to statistics

    statistics with python
    statistics for data science
    statistics for business
    statistics for data analysis
    statistics with r
    statistics in psychological research
    statistics for data science with python
    statistics and data analysis with excel, part 1
    1…789…107

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

    • Statistics and Data Analysis with R: University of Colorado Boulder
    • Game Theory: Stanford University
    • Bayesian Statistics: Time Series Analysis: University of California, Santa Cruz
    • Using Descriptive Statistics to Analyze Data in R: Coursera Project Network
    • R Programming: Johns Hopkins University
    • Data Analysis with R Programming: Google
    • Sports Performance Analytics: University of Michigan
    • IBM Data Analyst: IBM
    • IBM Generative AI Engineering: IBM
    • Natural Language Processing: DeepLearning.AI

    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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