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    • Applied Statistics

    Applied Statistics Courses Online

    Understand applied statistics for data analysis and interpretation. Learn statistical methods and tools for various industries.

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    Explore the Applied Statistics Course Catalog

    • I

      IBM

      AI Foundations for Everyone

      Skills you'll gain: Prompt Engineering, ChatGPT, Large Language Modeling, Generative AI, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, IBM Cloud, Private Cloud, Data Loss Prevention, Applied Machine Learning, Deep Learning, WordPress, Artificial Neural Networks, Governance, Machine Learning, Generative AI Agents, Automation, Digital Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 Months

    • A

      American Psychological Association

      Statistics in Psychological Research

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      45 reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM IT Project Manager

      Skills you'll gain: Stakeholder Engagement, Software Development Life Cycle, Agile Software Development, Project Management Life Cycle, Resource Management, Risk Management, Peer Review, Earned Value Management, Stakeholder Management, Agile Methodology, Project Risk Management, Team Motivation, Kanban Principles, Project Schedules, Resource Planning, Development Environment, Information Technology, Sprint Retrospectives, Interviewing Skills, Project Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • R

      Rice University

      Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

      Skills you'll gain: Descriptive Statistics, Probability & Statistics, Probability Distribution, Business Analytics, Microsoft Excel, Data Analysis, Statistical Analysis, Box Plots, Sampling (Statistics), Correlation Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.6K reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      IBM Applied DevOps Engineering

      Skills you'll gain: CI/CD, Istio, Open Web Application Security Project (OWASP), Continuous Integration, Agile Software Development, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Kubernetes, Code Coverage, OpenShift, Cloud Applications, Containerization, Agile Methodology, Behavior-Driven Development, DevOps, Secure Coding, Grafana, System Monitoring

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.1K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Tableau Software, Relational Databases, Star Schema, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Relational Databases, Stored Procedure, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Analysis Software, Data Cleansing, Data Visualization Software, GitHub, Business Analysis, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      99K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      Y

      Yale University

      Understanding Medical Research: Your Facebook Friend is Wrong

      Skills you'll gain: Probability & Statistics, Research Design, Medical Science and Research, Statistics, Data Literacy, Statistical Analysis, Scientific Methods, Clinical Research

      4.9
      Rating, 4.9 out of 5 stars
      ·
      2.2K reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Summary Statistics in Public Health

      Skills you'll gain: Biostatistics, Statistical Visualization, Epidemiology, Medical Science and Research, Quantitative Research, Descriptive Statistics, Statistical Methods, Data Literacy, Probability Distribution, Public Health, Statistical Analysis, Clinical Trials, Sample Size Determination

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Applied Data Science with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Shiny (R Package), Data Wrangling, Dashboard, Exploratory Data Analysis, Relational Databases, Data Analysis, Ggplot2, Database Design, Data Presentation, SQL, Plot (Graphics), Leaflet (Software), Data Transformation, Database Management, Data Manipulation, Web Scraping, R Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Data Visualization Software, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Presentation, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Applied Statistics learners also search

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    1…8910…197

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

    • AI Foundations for Everyone: IBM
    • Statistics in Psychological Research: American Psychological Association
    • IBM IT Project Manager: IBM
    • Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions: Rice University
    • IBM Applied DevOps Engineering: IBM
    • IBM Business Intelligence (BI) Analyst: IBM
    • Introduction to Data Science: IBM
    • Understanding Medical Research: Your Facebook Friend is Wrong: Yale University
    • Summary Statistics in Public Health : Johns Hopkins University
    • Applied Data Science with R: IBM

    Frequently Asked Questions about Applied Statistics

    Applied statistics is the use of statistical techniques to solve real-world data analysis problems. In contrast to the pure study of mathematical statistics, applied statistics is typically used by and for non-mathematicians in fields ranging from social science to business. Indeed, in the big data era, applied statistics has become important for deriving insights and guiding decision-making in virtually every industry.

    The increased reliance on data and statistics to help understand our world has made the careful application of these techniques even more essential; too often, statistics can be used erroneously or even misleadingly when methods of analysis are not properly connected to research questions. Thus, a major aspect of applied statistics is the accurate communication of findings for a non-technical audience, including specifics about data sources, relevance to the problem at hand, and degrees of uncertainty.

    That said, the statistical approaches used in this field are the same as in the study of mathematical statistics. Rigorous use of statistical hypothesis testing, statistical inference, linear regression techniques, and analysis of variance (ANOVA) are core to the work of applied statistics. And, as in other areas of data science, Python programming and R programming are often used to analyze large datasets when Microsoft Excel is not sufficiently powerful.‎

    Demand for data-driven insights is growing fast across all fields, making a background in applied statistics the gateway to a wide variety of careers. Financial institutions and companies of all kinds rely on business analytics to guide investments and operations; political candidates and advocacy groups need to conduct surveys and understand public polling data to understand popular opinion on today’s issues; and even sports teams are increasingly hiring experts in applied statistics to make decisions regarding personnel as well as in-game strategy.

    While many jobs in applied statistics may require only a bachelor’s degree in fields such as mathematics or computer science, high-level roles often expect a master’s degree in statistics. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the need to analyze fast-growing volumes of electronic data.‎

    Yes, with absolute certainty. Coursera offers courses and Specializations in applied statistics for business, social science, and other areas, as well as related topics such as data science and Python programming. These courses are offered by top-ranked universities and leading companies from around the world, including the University of Michigan, the University of Amsterdam, and the University of Virginia, and IBM. Regardless of whether you’re a student looking to learn more about this exciting field or a mid-career professional upgrading their skill set, the combination of a high-quality education and the flexibility of learning online makes Coursera a great choice.‎

    It's very helpful to have strong math skills, analytical skills, and experience solving problems before starting to learn applied statistics. It's also good to have experience and a good comfort level with technology and computers. Previous experience in statistics is also helpful, although not required. You may also benefit from having prior experience using Excel spreadsheets as you begin to learn applied statistics.‎

    People best suited for roles in applied statistics are analytical thinkers. They enjoy problem-solving by taking available data and analyzing it to arrive at solutions. They also have effective communication skills so that information can flow clearly to all stakeholders within an organization. Organization and multitasking come easily to people best suited for roles in applied statistics because these individuals need to deal with large amounts of information and manage their time and resources efficiently. People well suited for these roles also pay close attention to detail to make sure the outcomes they're tasked with delivering meet or exceed expectations.‎

    While the use of applied statistics can be found in almost every industry, learning applied statistics may be especially interesting to you if you're seeking a career in the insurance, web analytics, or energy sectors. These are some of the top industries that currently utilize applied statistics. However, a person in any position in which data is gathered and analyzed to create solutions, innovations, or improvements would benefit from learning applied statistics, from coaches and hospital administrators to bloggers, data scientists, and bankers. If you would like to know how to ensure you're collecting the right data, how to analyze data correctly, and how to effectively report your findings so they can be applied in real-world situations, learning applied statistics may be right for you.‎

    Online Applied Statistics courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Statistics skills. With a wide range of Applied Statistics classes, you can conveniently learn at your own pace to advance your Applied Statistics career skills.‎

    When looking to enhance your workforce's skills in Applied Statistics, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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