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    • Statistics

    Statistics Courses Online

    Study statistics for data analysis and interpretation. Learn about descriptive statistics, probability, and inferential statistics.

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    Explore the Statistics Course Catalog

    • 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 Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Introduction to Machine Learning

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

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

      Beginner · Specialization · 3 - 6 Months

    • 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, Risk Analysis

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

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to Software Engineering

      Skills you'll gain: Software Development Life Cycle, Development Environment, Software Engineering, Software Development Tools, Software Architecture, Software Design, Programming Principles, Unified Modeling Language, Agile Methodology, Software Development, Scrum (Software Development), Cloud Development, Integrated Development Environments, Back-End Web Development, Front-End Web Development, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Beginner · Course · 1 - 3 Months

    • K

      Kennesaw State University

      Six Sigma Black Belt

      Skills you'll gain: Statistical Process Controls, Lean Six Sigma, Six Sigma Methodology, Lean Methodologies, Process Improvement, Team Management, Process Capability, Lean Manufacturing, Data Collection, Knowledge Transfer, Team Building, Statistical Hypothesis Testing, Meeting Facilitation, Quality Improvement, Continuous Improvement Process, Performance Measurement, Conflict Management, Sampling (Statistics), Team Leadership, Organizational Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      709 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics: Capstone Project

      Skills you'll gain: Bayesian Statistics, Technical Communication, R Programming, Statistical Analysis, Statistical Modeling, Data Analysis, Time Series Analysis and Forecasting, Markov Model, Statistical Methods, Predictive Modeling, Sampling (Statistics), Probability Distribution

      Advanced · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Executive Data Science

      Skills you'll gain: Data Quality, Exploratory Data Analysis, Employee Onboarding, Data Management, Team Motivation, Technical Communication, Data Analysis, Data Presentation, Project Management, Interviewing Skills, Data Science, Data-Driven Decision-Making, Management Training And Development, Organizational Leadership, Data Strategy, Team Management, Analytical Skills, Project Implementation, Team Building, Project Design

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 1 - 3 Months

    • 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

    • D

      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Linear Algebra, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    • S

      Stanford University

      Divide and Conquer, Sorting and Searching, and Randomized Algorithms

      Skills you'll gain: Algorithms, Graph Theory, Data Structures, Theoretical Computer Science, Computational Thinking, Analysis, Programming Principles, Probability & Statistics, Probability

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.3K reviews

      Intermediate · Course · 1 - 4 Weeks

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    1…111213…105

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

    • Meta Data Analyst: Meta
    • IBM Introduction to Machine Learning: IBM
    • Six Sigma Yellow Belt: Kennesaw State University
    • Six Sigma Tools for Analyze: Kennesaw State University
    • Introduction to Software Engineering: IBM
    • Six Sigma Black Belt: Kennesaw State University
    • Reinforcement Learning: University of Alberta
    • Bayesian Statistics: Capstone Project: University of California, Santa Cruz
    • Executive Data Science: Johns Hopkins University
    • Big Data: University of California San Diego

    Frequently Asked Questions about Statistics

    Statistics courses on Coursera can help equip you with analytical skills and mathematical knowledge to effectively interpret data:

    • Understanding of statistical theory, including probability, distributions, and hypothesis testing.
    • Skills in applying statistical methods to real-world problems across various industries.
    • Proficiency in using statistical software tools like R, Python, or SPSS to analyze and visualize data.
    • Techniques for designing experiments and surveys to collect data efficiently.
    • Knowledge of regression analysis, ANOVA, and other statistical models.
    • Insights into big data analytics, including machine learning algorithms driven by statistical principles.
    • Application of statistics in specialized fields such as biostatistics, econometrics, or psychological statistics.‎

    Statistics courses on Coursera are designed to accommodate learners at different stages of their educational or professional journey:

    • Introductory courses are suitable for those new to statistics, offering foundational knowledge and basic application skills.
    • Intermediate courses build upon basic statistics knowledge, introducing more complex analyses and applications.
    • Advanced courses cater to individuals with a solid background in statistics, focusing on specialized topics or advanced analytical techniques. ‎

    Coursera provides various educational pathways to help validate your skills in statistics:

    • Professional certificates that can help you demonstrate your competence in statistical analysis.
    • Specialized course certificates that focus on particular aspects of statistics, such as data science or predictive analytics.
    • Degree programs and professional qualifications that prepare you for roles involving extensive use of statistics.

    These credentials are intended to enhance your professional qualifications and assist you in advancing your career in fields reliant on statistical analysis.‎

    Studying statistics on Coursera can prepare you for a variety of roles in data-intensive sectors:

    • Data Analyst: Utilize statistical tools and methods to interpret data and inform business decisions.
    • Statistical Consultant: Provide expertise to organizations on statistical methods, data collection, and analysis.
    • Biostatistician: Apply statistics to biological sciences and public health.
    • Econometrician: Use statistical techniques to study economic data and trends.
    • Quality Control Analyst: Implement statistical methods to assess product quality and maintain standards.‎

    Yes, Coursera offers a variety of free courses across many topics, including statistics. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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