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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
      U

      University of Pennsylvania

      Customer Analytics

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Marketing Analytics, Predictive Analytics, Customer Insights, Customer Analysis, Business Analytics, Customer Data Management, Analytics, Marketing, Data Collection, Market Research, Regression Analysis, Consumer Behaviour, Correlation Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      12K reviews

      Mixed · 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
      ·
      92 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
      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
      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, Advanced Analytics, Statistical Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      256 reviews

      Intermediate · Specialization · 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, Unit Testing, Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Exploratory Data Analysis, Artificial Intelligence, Data Wrangling, ChatGPT, Natural Language Processing, Data Analysis, Jupyter, Unsupervised Learning, PyTorch (Machine Learning Library), Generative AI Agents, Data Ethics

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

      Beginner · Professional Certificate · 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, Big Data, Jupyter, 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
      U

      University of California San Diego

      Big Data

      Skills you'll gain: Apache Spark, Apache Hadoop, Data Integration, Exploratory Data Analysis, Big Data, Graph Theory, Data Pipelines, Database Design, Data Modeling, Regression Analysis, Applied Machine Learning, Data Presentation, Scalability, Data Mining, Data Processing, Statistical Analysis, Data Management, NoSQL, Database Management Systems, Network Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      14K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      BI Foundations with SQL, ETL and Data Warehousing

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Bash (Scripting Language), Shell Script, Dashboard, File Management, Star Schema, Unix Shell, IBM DB2, Business Intelligence, Interactive Data Visualization, Databases, Stored Procedure, Relational Databases

      4.6
      Rating, 4.6 out of 5 stars
      ·
      24K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Geographic Information Systems (GIS)

      Skills you'll gain: ArcGIS, GIS Software, Spatial Data Analysis, Spatial Analysis, Data Storytelling, Geographic Information Systems, Data Presentation, Data Sharing, Geospatial Mapping, Public Health, Land Management, Heat Maps, Metadata Management, Data Quality, Community Health, Data Mapping, Data Visualization Software, File Management, Network Analysis, Data Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.3K 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 with r
    statistics for data analysis
    statistics for data science with python
    statistics in psychological research
    statistics for business
    statistics foundations
    1…789…106

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

    • Customer Analytics: University of Pennsylvania
    • Using Descriptive Statistics to Analyze Data in R: Coursera Project Network
    • R Programming: Johns Hopkins University
    • Data Analysis with R Programming: Google
    • Natural Language Processing: DeepLearning.AI
    • Sports Performance Analytics: University of Michigan
    • IBM Generative AI Engineering: IBM
    • IBM Data Analyst: IBM
    • Big Data: University of California San Diego
    • BI Foundations with SQL, ETL and Data Warehousing: IBM

    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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