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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
      K

      Kennesaw State University

      Six Sigma Tools for Analyze

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Process Analysis, Probability Distribution, Process Capability, Statistical Process Controls, Lean Methodologies, Probability & Statistics, Process Improvement, Quality Improvement, Process Mapping, Statistical Analysis, Systems Of Measurement, Data Analysis, Statistics, Risk Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Plot (Graphics), Statistical Programming, Statistical Visualization, Ggplot2, R (Software), Dimensionality Reduction, Data Visualization Software, Knitr, Data Sharing, GitHub, Machine Learning

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistics, Statistical Analysis, Applied Mathematics, Advanced Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      188 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Literacy

      Skills you'll gain: Surveys, Survey Creation, Data Literacy, Data Visualization, Data Analysis, Peer Review, Research Design, Statistics, Sampling (Statistics), Regression Analysis, Descriptive Statistics, Research, Probability, Quantitative Research, Analytics, Probability Distribution, Analysis, Correlation Analysis, Statistical Inference, Statistical Hypothesis Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      255 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Methods, Statistical Inference, Statistical Hypothesis Testing, Data Processing, Data Access, Statistics, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Machine Learning, Probability & Statistics, Data Transformation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      D

      DeepLearning.AI

      DeepLearning.AI Data Analytics

      Skills you'll gain: Data Storytelling, Web Scraping, Google Sheets, Data Visualization, Data Presentation, Spreadsheet Software, Large Language Modeling, Tableau Software, Data Literacy, Dashboard, LinkedIn, Pandas (Python Package), Time Series Analysis and Forecasting, Probability & Statistics, Extract, Transform, Load, Statistical Analysis, Statistics, Data Manipulation, Data Analysis, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      169 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, 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

    • Status: Preview
      Preview
      U

      University of London

      Foundations of Data Science: K-Means Clustering in Python

      Skills you'll gain: Data Visualization, Matplotlib, Probability & Statistics, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Data Analysis, Machine Learning Algorithms, Descriptive Statistics, Machine Learning, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      730 reviews

      Beginner · Course · 1 - 3 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, Scrum (Software Development), Software Engineering, Linux, Application Deployment, Data Import/Export, Programming Principles, Web Scraping, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Preview
      Preview
      E

      EDUCBA

      Quantitative Finance with SAS: Apply, Analyze & Evaluate

      Skills you'll gain: SAS (Software), Descriptive Statistics, Market Data, Financial Data, Risk Modeling, Regression Analysis, Statistical Hypothesis Testing, Correlation Analysis, Data Analysis Software, Statistical Analysis, Financial Market, Time Series Analysis and Forecasting, Trend Analysis, Financial Analysis, Variance Analysis, Forecasting

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Visualization, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Quality, Data Analysis, Data Visualization Software, Spreadsheet Software, Exploratory Data Analysis, SQL, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.6K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Preview
      Preview
      E

      Emory University

      Math for MBA and GMAT Prep

      Skills you'll gain: Regression Analysis, Data Visualization, Business Mathematics, Descriptive Statistics, Microsoft Excel, Statistics, Business Analytics, Excel Formulas, Statistical Analysis, Algebra, Calculus, Arithmetic, Business

      4.3
      Rating, 4.3 out of 5 stars
      ·
      47 reviews

      Beginner · Course · 1 - 3 Months

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

    • Six Sigma Tools for Analyze: Kennesaw State University
    • Data Science: Foundations using R: Johns Hopkins University
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
    • Data Literacy: Johns Hopkins University
    • Exploratory Data Analysis for Machine Learning: IBM
    • DeepLearning.AI Data Analytics: DeepLearning.AI
    • Probabilistic Graphical Models: Stanford University
    • Foundations of Data Science: K-Means Clustering in Python: University of London
    • Applied Software Engineering Fundamentals: IBM
    • Quantitative Finance with SAS: Apply, Analyze & Evaluate: EDUCBA

    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.

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