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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

    • U

      University of Pennsylvania

      Single Variable Calculus

      Skills you'll gain: Calculus, Numerical Analysis, Applied Mathematics, Engineering Calculations, Integral Calculus, Engineering Analysis, Differential Equations, Mathematical Theory & Analysis, Advanced Mathematics, Estimation, Derivatives

      4.6
      Rating, 4.6 out of 5 stars
      ·
      418 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Minnesota

      Recommender Systems

      Skills you'll gain: AI Personalization, Machine Learning Algorithms, Taxonomy, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Data Collection, Performance Measurement, Benchmarking, Usability Testing, Exploratory Data Analysis, A/B Testing, Analysis, Artificial Intelligence and Machine Learning (AI/ML), Technical Design, Algorithms, System Design and Implementation, Predictive Modeling

      4.3
      Rating, 4.3 out of 5 stars
      ·
      818 reviews

      Intermediate · Specialization · 3 - 6 Months

    • T

      Tecnológico de Monterrey

      Cálculo Diferencial e Integral unidos por el Teorema Fundamental del Cálculo

      Skills you'll gain: Calculus, Integral Calculus, Advanced Mathematics, Graphing, Trigonometry, Mathematical Modeling, Mathematical Theory & Analysis, Algebra, Computational Thinking, Applied Mathematics, Mathematical Software, Derivatives

      4.6
      Rating, 4.6 out of 5 stars
      ·
      718 reviews

      Mixed · Course · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Semiconductor Devices

      Skills you'll gain: Semiconductors, Electrical Engineering, Electronic Systems, Power Electronics, Electronic Components, Physics, Electronics, Electrical and Computer Engineering, Electronics Engineering, Scalability, Differential Equations, Applied Mathematics, Mathematical Modeling

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      601 reviews

      Advanced · Specialization · 1 - 3 Months

    • U

      Universitat Autònoma de Barcelona

      Pre-Calculus

      Skills you'll gain: Trigonometry, Integral Calculus, Calculus, Arithmetic, Advanced Mathematics, Algebra, Geometry, Applied Mathematics, Graphing, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      569 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      É

      École Polytechnique Fédérale de Lausanne

      Digital Signal Processing 1: Basic Concepts and Algorithms

      Skills you'll gain: Digital Communications, Electrical and Computer Engineering, Programming Principles, Engineering Analysis, Electronics, Telecommunications, Advanced Mathematics, Algorithms, Linear Algebra, Time Series Analysis and Forecasting, Mathematical Modeling, Computational Logic, Applied Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      623 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      State Estimation and Localization for Self-Driving Cars

      Skills you'll gain: Global Positioning Systems, Estimation, Machine Learning Methods, Computer Vision, Spatial Data Analysis, Mathematical Modeling, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      835 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      F

      Fractal Analytics

      Fractal Data Science

      Skills you'll gain: Data Storytelling, Decision Making, Critical Thinking, Database Design, Data Manipulation, Data Presentation, Power BI, Data Visualization, Exploratory Data Analysis, Feature Engineering, Interactive Data Visualization, Data Analysis Expressions (DAX), Human Centered Design, Storyboarding, SQL, Applied Machine Learning, Problem Solving, Data Modeling, Machine Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      345 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      Universidad de los Andes

      Contenido de las matemáticas de primaria

      Skills you'll gain: Mathematics Education, Arithmetic, Geometry, Systems Of Measurement, Applied Mathematics, Algebra, Graphing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 3 Months

    • N

      Nanjing University

      用Python玩转数据 Data Processing Using Python

      Skills you'll gain: Web Scraping, Exploratory Data Analysis, Data Structures, Object Oriented Programming (OOP), Data Processing, Data Mining, Data Analysis, Pandas (Python Package), NumPy, Statistical Analysis, Data Manipulation, User Interface (UI), Financial Data, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.6K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University at Buffalo

      Computer Vision Basics

      Skills you'll gain: Computer Vision, Image Analysis, Computer Graphics, Visualization (Computer Graphics), Data Processing, Digital Design, Artificial Intelligence, Matlab, Linear Algebra, Algorithms, Calculus, Probability & Statistics

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      Unilever

      Unilever Digital Marketing Analyst

      Skills you'll gain: Data Storytelling, Marketing Automation, Web Analytics, Marketing Effectiveness, Marketing Analytics, Customer Insights, Digital Marketing, Social Media Campaigns, Market Analysis, Google Analytics, Social Media Marketing, Customer Analysis, Search Engine Marketing, Marketing Strategies, Social Media Strategy, Customer experience strategy (CX), Performance Reporting, Search Engine Optimization, Predictive Analytics, MarTech

      4.7
      Rating, 4.7 out of 5 stars
      ·
      253 reviews

      Beginner · Professional Certificate · 3 - 6 Months

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    1…333435…200

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

    • Single Variable Calculus: University of Pennsylvania
    • Recommender Systems: University of Minnesota
    • Cálculo Diferencial e Integral unidos por el Teorema Fundamental del Cálculo: Tecnológico de Monterrey
    • Semiconductor Devices: University of Colorado Boulder
    • Pre-Calculus: Universitat Autònoma de Barcelona
    • Digital Signal Processing 1: Basic Concepts and Algorithms: École Polytechnique Fédérale de Lausanne
    • State Estimation and Localization for Self-Driving Cars: University of Toronto
    • Fractal Data Science: Fractal Analytics
    • Contenido de las matemáticas de primaria: Universidad de los Andes
    • 用Python玩转数据 Data Processing Using Python: Nanjing 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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