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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

      Specialized Models: Time Series and Survival Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Jupyter, Data Cleansing, Applied Machine Learning, Data Transformation, Exploratory Data Analysis, Pandas (Python Package)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      134 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      MathWorks

      Predictive Modeling and Machine Learning with MATLAB

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Matlab, Regression Analysis, Predictive Modeling, Classification And Regression Tree (CART), Machine Learning, Predictive Analytics, Feature Engineering, Statistical Modeling, Data Processing, Sampling (Statistics)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      PowerBI for Beginners: Sales Data Exploration

      Skills you'll gain: Power BI, Interactive Data Visualization, Data Visualization, Data Presentation, Dashboard, Trend Analysis, Exploratory Data Analysis, Customer Analysis, Data Visualization Software, Sales, Business Intelligence, Data Analysis, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      29 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Calculus through Data & Modeling: Limits & Derivatives

      Skills you'll gain: Calculus, Applied Mathematics, Data Analysis, Analysis, Mathematical Theory & Analysis, Derivatives, Trend Analysis, Graphing, Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      198 reviews

      Beginner · Course · 1 - 3 Months

    • E

      Edureka

      Introduction to PySpark

      Skills you'll gain: PySpark, Apache Spark, Distributed Computing, Big Data, Apache Hadoop, Data Processing, Data Manipulation, Exploratory Data Analysis, Python Programming

      3.7
      Rating, 3.7 out of 5 stars
      ·
      35 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      O

      O.P. Jindal Global University

      Machine Learning for Marketing

      Skills you'll gain: Marketing Analytics, Anomaly Detection, Digital Marketing, Web Analytics, Digital Advertising, Dimensionality Reduction, Unsupervised Learning, Customer Analysis, Search Engine Marketing, Supervised Learning, Online Advertising, Customer Retention, Text Mining, Predictive Analytics, Google Analytics, Search Engine Optimization, Applied Machine Learning, Data Ethics, Data Mining, Customer Insights

      4
      Rating, 4 out of 5 stars
      ·
      15 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      GRAMMY GO

      Building Your Audience for Music Professionals

      Skills you'll gain: Marketing Budgets, Digital Media Strategy, Professional Networking, Content Strategy, Promotional Strategies, Branding, Marketing Analytics, Brand Strategy, Brand Awareness, Budget Management, Marketing Design, Customer Engagement, Content Marketing, Target Audience, Digital Marketing, Marketing Strategies, Trend Analysis, Social Media Marketing, Resilience, Customer Insights

      4.8
      Rating, 4.8 out of 5 stars
      ·
      15 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      The Improve Phase for the 6 σ Black Belt

      Skills you'll gain: Lean Methodologies, Lean Six Sigma, Six Sigma Methodology, Performance Measurement, Process Improvement, Continuous Improvement Process, Process Analysis, Operational Efficiency, Statistical Methods, Statistical Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      39 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Icahn School of Medicine at Mount Sinai

      Voice Disorders: What Patients and Professionals Need to Know

      Skills you'll gain: Speech Therapy, Speech Language Pathology, Patient Evaluation, Physical Therapy, Respiration, Surgery, Anatomy

      4.9
      Rating, 4.9 out of 5 stars
      ·
      212 reviews

      Intermediate · Course · 1 - 3 Months

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Intro to Acoustics (Part 1)

      Skills you'll gain: Vibrations, Mechanics, Systems Of Measurement, Engineering Analysis, Differential Equations, Engineering Calculations, Physics, Calculus, Applied Mathematics, Mathematical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      141 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      Universidad Nacional de Colombia

      Ciencia de datos energéticos

      Skills you'll gain: Electrical Power, Electric Power Systems, Energy and Utilities, Time Series Analysis and Forecasting, Data Science, Statistical Methods, Data Modeling, Python Programming, Data Processing, Applied Machine Learning, Data Visualization Software, Regression Analysis, Artificial Neural Networks

      5
      Rating, 5 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      L

      L&T EduTech

      AI & ML Applications in Oil and Gas Industry

      Skills you'll gain: Big Data, Data Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Process Engineering, Geostatistics, Anomaly Detection, Image Analysis, Energy and Utilities, Machine Learning, Automation, Physical Science, Natural Resource Management, Simulation and Simulation Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      39 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Specialized Models: Time Series and Survival Analysis: IBM
    • Predictive Modeling and Machine Learning with MATLAB: MathWorks
    • PowerBI for Beginners: Sales Data Exploration: Coursera Project Network
    • Calculus through Data & Modeling: Limits & Derivatives: Johns Hopkins University
    • Introduction to PySpark: Edureka
    • Machine Learning for Marketing: O.P. Jindal Global University
    • Building Your Audience for Music Professionals: GRAMMY GO
    • The Improve Phase for the 6 σ Black Belt: Kennesaw State University
    • Voice Disorders: What Patients and Professionals Need to Know: Icahn School of Medicine at Mount Sinai
    • Intro to Acoustics (Part 1): Korea Advanced Institute of Science and Technology(KAIST)

    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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