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    Results for "applied statistics"

    • University of California, Davis

      Essential Design Principles for Tableau

      Skills you'll gain: Data Visualization Software, Tableau Software, Exploratory Data Analysis, Data Presentation, Data Analysis, Web Content Accessibility Guidelines, User Interface and User Experience (UI/UX) Design, Usability, Design Elements And Principles, Color Theory, Data Ethics, Human Factors, Aesthetics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2K reviews

      Beginner · Course · 1 - 4 Weeks

    • University of Illinois Urbana-Champaign

      Auditing II: The Practice of Auditing

      Skills you'll gain: Auditing, Internal Controls, Financial Auditing, External Auditing, Generally Accepted Auditing Standards, Audit Planning, Financial Controls, Verification And Validation, Risk Analysis, Business Risk Management, Probability & Statistics

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      269 reviews

      Intermediate · Course · 1 - 3 Months

    • University of California, Davis

      Quantitative Research

      Skills you'll gain: Surveys, Survey Creation, Quantitative Research, Statistical Analysis, Marketing Analytics, Market Research, Statistical Methods, Data Analysis, Marketing, Target Market, Sample Size Determination, Quality Control

      4.4
      Rating, 4.4 out of 5 stars
      ·
      333 reviews

      Intermediate · Course · 1 - 4 Weeks

    • École Polytechnique

      Quantum Optics 1 : Single Photons

      Skills you'll gain: Physics, Experimentation, Quantitative Research, Cryptography, Mathematical Modeling, Applied Mathematics, Engineering, Scientific, and Technical Instruments, Emerging Technologies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      331 reviews

      Mixed · Course · 1 - 3 Months

    • SAS

      Data Literacy: Exploring and Visualizing Data

      Skills you'll gain: Exploratory Data Analysis, Data Literacy, Data Storytelling, Data-Driven Decision-Making, Data Presentation, SAS (Software), Trend Analysis, Data Manipulation, Data Analysis, Data Quality, Data Cleansing, Scatter Plots, Interactive Data Visualization, Technical Communication, Time Series Analysis and Forecasting, Data Ethics, Data Visualization, Data Visualization Software, Research, Business Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 1 - 3 Months

    • The State University of New York

      Solar Energy System Design

      Skills you'll gain: Electrical Systems, Electrical Power, Basic Electrical Systems, Equipment Design, Energy and Utilities, Electrical Equipment, Survey Creation, System Requirements, Engineering Calculations, Performance Testing, Physical Science, Spatial Analysis, Estimation, Physics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      450 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free

      McMaster University

      Experimentation for Improvement

      Skills you'll gain: Experimentation, Data Visualization, Predictive Modeling, Process Improvement and Optimization, Regression Analysis, Statistical Software, Mathematical Modeling, R Programming, Data Analysis, Statistical Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      921 reviews

      Intermediate · Course · 1 - 3 Months

    • Duke University

      The Brain and Space

      Skills you'll gain: Spatial Analysis, Neurology, Human Learning, Experimentation, Laboratory Research, Physics, Biology, General Science and Research, Magnetic Resonance Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      652 reviews

      Beginner · Course · 1 - 3 Months

    • California Institute of the Arts

      Character Design for Video Games

      Skills you'll gain: Animation and Game Design, Animations, Game Design, Video Game Development, Design, Technical Design, Conceptual Design, Design Elements And Principles, Creative Design, Storytelling, Creativity

      4.7
      Rating, 4.7 out of 5 stars
      ·
      994 reviews

      Beginner · Course · 1 - 4 Weeks

    • New York University

      Guided Tour of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Financial Services, Finance, Tensorflow, Jupyter, Reinforcement Learning

      3.8
      Rating, 3.8 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Google Cloud

      Launching into Machine Learning

      Skills you'll gain: Data Quality, Exploratory Data Analysis, Machine Learning, MLOps (Machine Learning Operations), Applied Machine Learning, Scikit Learn (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Google Cloud Platform, Machine Learning Algorithms, Data Analysis, Predictive Modeling, Big Data, Classification And Regression Tree (CART), Regression Analysis, Data Processing, Sampling (Statistics), Test Data, Performance Tuning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.3K reviews

      Beginner · Course · 1 - 3 Months

    • LearnQuest

      Developing AI Applications on Azure

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Microsoft Azure, Applied Machine Learning, Python Programming, Machine Learning, Machine Learning Algorithms, Data Science, Image Analysis, Computer Vision, Application Deployment, Natural Language Processing, Application Programming Interface (API)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      976 reviews

      Advanced · Course · 1 - 3 Months

    Searches related to applied statistics

    applied statistics for data analytics
    statistics and applied data analysis
    1…363738…195

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

    • Essential Design Principles for Tableau: University of California, Davis
    • Auditing II: The Practice of Auditing: University of Illinois Urbana-Champaign
    • Quantitative Research: University of California, Davis
    • Quantum Optics 1 : Single Photons: Ã‰cole Polytechnique
    • Data Literacy: Exploring and Visualizing Data: SAS
    • Solar Energy System Design: The State University of New York
    • Experimentation for Improvement: McMaster University
    • The Brain and Space: Duke University
    • Character Design for Video Games: California Institute of the Arts
    • Guided Tour of Machine Learning in Finance: New York University

    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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