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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

    • Status: New
      New
      Status: Free Trial
      Free Trial
      I

      IBM

      IBM Digital Marketing and Growth Hacking

      Skills you'll gain: Search Engine Marketing, Keyword Research, Google Ads, Digital Advertising, Web Analytics and SEO, Online Advertising, Digital Marketing, Target Audience, Digital Media Strategy, Advertising Campaigns, Pay Per Click Advertising, Search Engine Optimization, Email Marketing, Content Marketing, Paid media, Advertising, Marketing Analytics, Web Analytics, Generative AI, Marketing Automation

      5
      Rating, 5 out of 5 stars
      ·
      8 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      C

      Coursera Instructor Network

      QA Process Optimization: Agile & Automated Testing

      Skills you'll gain: Software Quality Assurance, Quality Assurance, Test Automation, Test Tools, Acceptance Testing, Agile Software Development, Test Case, Software Testing, Continuous Integration, User Acceptance Testing (UAT), Agile Methodology, User Story

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Simple Regression Analysis in Public Health

      Skills you'll gain: Biostatistics, Regression Analysis, Statistical Methods, Statistical Analysis, Epidemiology, Quantitative Research, Public Health, Data Analysis, Probability & Statistics, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      382 reviews

      Beginner · Course · 1 - 3 Months

    • U

      Universidade de São Paulo

      Marketing Digital

      Skills you'll gain: Search Engine Marketing, Digital Marketing, Email Marketing, Google Ads, Marketing Strategies, Search Engine Optimization, Google Analytics, Online Advertising, A/B Testing, Pay Per Click Advertising, Advertising Campaigns, Web Analytics, Digital Advertising, Facebook, Campaign Management, Marketing Analytics, Return On Investment, Performance Measurement

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.3K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Business Writing

      Skills you'll gain: Business Writing, Business Correspondence, Business Communication, Writing, Organizational Skills, Concision, Writing and Editing, Proofreading, Grammar, Communication, Editing, Organizational Strategy, Persuasive Communication, Verbal Communication Skills, Communication Strategies

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

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Bioinformatics

      Skills you'll gain: Bioinformatics, Molecular Biology, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Data Analysis, Computational Thinking, Graph Theory, Markov Model, Biochemistry, Life Sciences, Microbiology, Statistical Analysis, Medical Science and Research, Precision Medicine, Biology, Pharmacology, Algorithms, Infectious Diseases, Data Mining

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 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, Statistical Modeling, Bayesian Statistics, 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: Free Trial
      Free Trial
      D

      DeepLearning.AI

      AI for Medical Diagnosis

      Skills you'll gain: Image Analysis, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Applied Machine Learning, Medical Imaging, Machine Learning Algorithms, Computer Vision, Deep Learning, Natural Language Processing, Medical Science and Research, Radiology, Artificial Neural Networks, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Programming Principles, Computer Science, Statistical Analysis, Computational Thinking, Big Data, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Amsterdam

      Data Analytics for Lean Six Sigma

      Skills you'll gain: Lean Six Sigma, Statistical Hypothesis Testing, Minitab, Regression Analysis, Data Visualization Software, Probability Distribution, Descriptive Statistics, Data Analysis, Statistical Analysis, Box Plots, Analytics, Process Improvement, Correlation Analysis, Variance Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      AI Product Management

      Skills you'll gain: Deep Learning, MLOps (Machine Learning Operations), Data Ethics, Data Management, Unsupervised Learning, Human Computer Interaction, User Experience Design, Classification And Regression Tree (CART), Data Quality, Human Centered Design, Machine Learning, Human Factors, Regression Analysis, Technical Management, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Artificial Neural Networks, Decision Tree Learning, Data Processing, Personally Identifiable Information

      4.7
      Rating, 4.7 out of 5 stars
      ·
      791 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    Applied Statistics learners also search

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    1…232425…198

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

    • IBM Digital Marketing and Growth Hacking: IBM
    • QA Process Optimization: Agile & Automated Testing: Coursera Instructor Network
    • Simple Regression Analysis in Public Health : Johns Hopkins University
    • Marketing Digital: Universidade de São Paulo
    • Business Writing: University of Colorado Boulder
    • Bioinformatics: University of California San Diego
    • Probabilistic Graphical Models: Stanford University
    • AI for Medical Diagnosis: DeepLearning.AI
    • Introduction to Genomic Technologies: Johns Hopkins University
    • Data Analytics for Lean Six Sigma: University of Amsterdam

    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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