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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

    • Emory University

      Foundations of Marketing Analytics

      Skills you'll gain: Pivot Tables And Charts, Customer Analysis, Probability Distribution, Customer Demand Planning, Marketing Analytics, Forecasting, Descriptive Statistics, Microsoft Excel, Social Media Marketing, Exploratory Data Analysis, Probability, Statistical Analysis, Marketing Effectiveness, Target Market, Social Media, Revenue Forecasting, Time Series Analysis and Forecasting, Predictive Modeling, Statistics, Marketing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      516 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis

      4
      Rating, 4 out of 5 stars
      ·
      872 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Johns Hopkins University

      Mathematical Biostatistics Boot Camp 1

      Skills you'll gain: Sampling (Statistics), Bayesian Statistics, Probability & Statistics, Statistical Inference, Statistical Methods, Probability, Probability Distribution, Statistical Analysis, Biostatistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      514 reviews

      Mixed · Course · 1 - 4 Weeks

    • University of California San Diego

      Finding Hidden Messages in DNA (Bioinformatics I)

      Skills you'll gain: Bioinformatics, Molecular Biology, Data Analysis, Computational Thinking, Biochemistry, Biology, Life Sciences, Algorithms, Probability & Statistics

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1K reviews

      Intermediate · Course · 1 - 3 Months

    • Johns Hopkins University

      Algebra: Elementary to Advanced

      Skills you'll gain: Algebra, Mathematical Modeling, Graphing, Arithmetic, Advanced Mathematics, Applied Mathematics, General Mathematics, Mathematical Theory & Analysis, Analytical Skills, Probability & Statistics, Geometry

      4.8
      Rating, 4.8 out of 5 stars
      ·
      723 reviews

      Beginner · Specialization · 3 - 6 Months

    • New York Institute of Finance

      Introduction to Risk Management

      Skills you'll gain: Risk Management, Business Risk Management, Risk Modeling, Operational Risk, Enterprise Risk Management (ERM), Credit Risk, Risk Analysis, Portfolio Management, Capital Markets, Financial Market, Financial Regulation, Financial Modeling, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      685 reviews

      Beginner · Course · 1 - 3 Months

    • Google

      Regression Analysis: Simplify Complex Data Relationships

      Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Advanced Analytics, Correlation Analysis, Data Analysis, Predictive Modeling, Statistical Modeling, Supervised Learning, Variance Analysis, Machine Learning Methods, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      515 reviews

      Advanced · Course · 1 - 3 Months

    • SAS

      Introduction to Statistical Analysis: Hypothesis Testing

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, SAS (Software), Regression Analysis, Exploratory Data Analysis, Statistical Methods, Probability & Statistics, Statistical Modeling, Plot (Graphics), Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      166 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Google

      The Nuts and Bolts of Machine Learning

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Unsupervised Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Random Forest Algorithm, Data Analysis, Performance Tuning, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      505 reviews

      Advanced · Course · 1 - 3 Months

    • University of Alberta

      Sample-based Learning Methods

      Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • University of California, Davis

      GIS Data Formats, Design and Quality

      Skills you'll gain: Spatial Data Analysis, Spatial Analysis, ArcGIS, Geographic Information Systems, Geospatial Mapping, Data Quality, Data Mapping, Data Modeling, Data Storage, Data Sharing, Data Manipulation, Relational Databases, Query Languages

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Kennesaw State University

      Six Sigma Tools for Improve and Control

      Skills you'll gain: Six Sigma Methodology, Process Improvement, Process Optimization, Correlation Analysis, Statistical Hypothesis Testing, Lean Six Sigma, Kaizen Methodology, Quality Improvement, Regression Analysis, Statistical Process Controls, Continuous Improvement Process, Process Capability, Quality Management, Project Management, Cost Benefit Analysis, Statistical Inference, Document Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

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    1…202122…105

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

    • Foundations of Marketing Analytics: Emory University
    • Introduction to Trading, Machine Learning & GCP: Google Cloud
    • Mathematical Biostatistics Boot Camp 1: Johns Hopkins University
    • Finding Hidden Messages in DNA (Bioinformatics I): University of California San Diego
    • Algebra: Elementary to Advanced: Johns Hopkins University
    • Introduction to Risk Management: New York Institute of Finance
    • Regression Analysis: Simplify Complex Data Relationships: Google
    • Introduction to Statistical Analysis: Hypothesis Testing: SAS
    • The Nuts and Bolts of Machine Learning: Google
    • Sample-based Learning Methods: University of Alberta

    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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