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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

    • Placeholder
      Status: New
      New
      E

      Edureka

      Python and Statistics Foundations

      Skills you'll gain: Matplotlib, Probability & Statistics, Plotly, Statistical Analysis, Statistical Methods, Data Visualization Software, Statistical Hypothesis Testing, Data Manipulation, Seaborn, Data Science, Programming Principles, Pandas (Python Package), Statistics, Descriptive Statistics, Data Analysis, NumPy, Exploratory Data Analysis, Probability, Python Programming

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      R Programming

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

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

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      Process Data from Dirty to Clean

      Skills you'll gain: Data Cleansing, Sampling (Statistics), Data Integrity, Data Quality, Data Validation, Data Analysis, Data Processing, Data Manipulation, SQL, Data Transformation, Spreadsheet Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Statistics and Data Analysis with Excel, Part 2

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Sampling (Statistics), Statistical Methods, Microsoft Excel, Probability & Statistics, Data Analysis, Regression Analysis, Probability Distribution, Statistical Modeling

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Illinois Tech

      Bayesian Computational Statistics

      Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Modeling, Statistical Analysis, Statistical Software, Statistical Programming, Statistical Methods, Regression Analysis, Statistical Inference, R Programming, Numerical Analysis, Markov Model, Probability, Simulations, Probability Distribution

      Build toward a degree

      Intermediate · Course · 1 - 3 Months

    • A

      American Psychological Association

      Statistics in Psychological Research

      Skills you'll gain: Data Visualization, Descriptive Statistics, Plot (Graphics), Graphing, Data Presentation, Statistical Hypothesis Testing, Probability & Statistics, Statistical Inference, Quantitative Research, Statistics, Statistical Analysis, Statistical Methods, Sample Size Determination, Data Analysis, Sampling (Statistics), Scatter Plots, Psychology, Research Design, Diversity Programs

      4.6
      Rating, 4.6 out of 5 stars
      ·
      44 reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      Status: Free
      Free
      U

      Universidad Nacional Autónoma de México

      Estadística y probabilidad

      Skills you'll gain: Descriptive Statistics, Statistics, Data Analysis, Statistical Methods, Correlation Analysis, Statistical Analysis, Data Presentation, Probability, Data-Driven Decision-Making, Quantitative Research, Regression Analysis, Probability Distribution, Exploratory Data Analysis, Graphing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Interactive Data Visualization, Statistical Analysis, Automation, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      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, Data Processing, Statistical Methods, Data Manipulation, Data Analysis Software, Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Placeholder
      Status: New
      New
      U

      University of Michigan

      Statistics with Python Using NumPy, Pandas, and SciPy

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Probability & Statistics, NumPy, Probability, Probability Distribution, Statistical Analysis, Data Analysis, Exploratory Data Analysis, Histogram, Scatter Plots, Regression Analysis, Pandas (Python Package), Linear Algebra, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder
      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, Advanced Analytics, Statistical Modeling, Statistical Analysis, Statistical Methods, Statistical Inference, Regression Analysis, Data Analysis, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      16 reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      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, Statistical Inference, Sampling (Statistics), Probability Distribution

      Advanced · Course · 1 - 4 Weeks

    Statistics learners also search

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    1…678…105

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

    • Python and Statistics Foundations: Edureka
    • R Programming: Johns Hopkins University
    • Process Data from Dirty to Clean: Google
    • Statistics and Data Analysis with Excel, Part 2: University of Colorado Boulder
    • Bayesian Computational Statistics: Illinois Tech
    • Statistics in Psychological Research: American Psychological Association
    • Estadística y probabilidad: Universidad Nacional Autónoma de México
    • Applied Data Science: IBM
    • Using Descriptive Statistics to Analyze Data in R: Coursera Project Network
    • Statistics with Python Using NumPy, Pandas, and SciPy: University of Michigan

    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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