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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: Free
      Free
      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, Numerical Analysis, Mathematics Education, Trigonometry, Mathematical Modeling, Mathematical Theory & Analysis, Algebra, Computational Thinking, Applied Mathematics, Derivatives

      4.6
      Rating, 4.6 out of 5 stars
      ·
      716 reviews

      Mixed · Course · 3 - 6 Months

    • W

      Wesleyan University

      Data Management and Visualization

      Skills you'll gain: Descriptive Statistics, Data Manipulation, Data Presentation, Data Management, Data Literacy, Graphing, SAS (Software), Peer Review, Data Analysis, Statistics, Research Reports, Exploratory Data Analysis, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      937 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Text Retrieval and Search Engines

      Skills you'll gain: Text Mining, Natural Language Processing, Data Mining, Unstructured Data, Big Data, Web Analytics and SEO, Machine Learning, Information Architecture, Statistical Methods, Algorithms, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      959 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Increase SEO Traffic with WordPress

      Skills you'll gain: WordPress, Search Engine Optimization, Blogs, Web Analytics, Web Content, Keyword Research, Information Architecture, Content Management

      4.5
      Rating, 4.5 out of 5 stars
      ·
      779 reviews

      Advanced · Guided Project · Less Than 2 Hours

    • G

      Google Cloud

      Smart Analytics, Machine Learning, and AI on Google Cloud

      Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Tensorflow, Unstructured Data, Applied Machine Learning, Data Pipelines, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Machine Learning, Jupyter, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IE Business School

      Globalización, Crecimiento Económico y Estabilidad

      Skills you'll gain: Financial Policy, Economics, Policy, and Social Studies, Economics, Public Policies, International Finance, Policy Analysis, International Relations, Economic Development, Tax, Socioeconomics, Trend Analysis, Global Marketing, Business Economics, Political Sciences, Analysis, Fiscal Management, Supply And Demand, Business Risk Management, World History, Policty Analysis, Research, and Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      692 reviews

      Beginner · Specialization · 3 - 6 Months

    • N

      New York Institute of Finance

      Reinforcement Learning for Trading Strategies

      Skills you'll gain: Reinforcement Learning, Financial Trading, Deep Learning, Portfolio Management, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning Software, Applied Machine Learning, Markov Model, Machine Learning, Financial Market, Time Series Analysis and Forecasting

      3.5
      Rating, 3.5 out of 5 stars
      ·
      239 reviews

      Intermediate · Course · 1 - 4 Weeks

    • E

      ESSEC Business School

      Foundations of marketing analytics

      Skills you'll gain: Marketing Analytics, Customer Analysis, Business Marketing, Advanced Analytics, Marketing Strategies, Business Analytics, Market Research, Customer Insights, R Programming, Data-Driven Decision-Making, Target Market, Data Analysis, Predictive Analytics, Statistical Analysis, Statistical Modeling, Predictive Modeling, Customer Relationship Management, Statistical Methods, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      760 reviews

      Mixed · Course · 1 - 3 Months

    • I

      IBM

      Deep Learning and Reinforcement Learning

      Skills you'll gain: Generative AI, Reinforcement Learning, Deep Learning, Unsupervised Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Keras (Neural Network Library), Machine Learning Algorithms, Tensorflow, Computer Vision, Dimensionality Reduction, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Sampling People, Networks and Records

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Data Collection, Surveys, Quantitative Research, Statistical Methods, Statistical Software, Probability & Statistics, Probability, Research Methodologies, Network Analysis

      4.3
      Rating, 4.3 out of 5 stars
      ·
      104 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Kinematics: Describing the Motions of Spacecraft

      Skills you'll gain: Mechanics, Linear Algebra, Numerical Analysis, Engineering Calculations, Engineering Analysis, Differential Equations, Physics, Mathematical Modeling, Applied Mathematics, Verification And Validation, Advanced Mathematics, Estimation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      332 reviews

      Advanced · Course · 1 - 4 Weeks

    • M

      Macquarie University

      Excel Skills for Business Forecasting

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, Financial Forecasting, Regression Analysis, Microsoft Excel, Demand Planning, Excel Formulas, Trend Analysis, Business Mathematics, Predictive Modeling, Business Metrics, Strategic Thinking, Data Presentation, Statistical Visualization, Graphing, Market Trend, Business Economics, Key Performance Indicators (KPIs), Statistical Modeling, Exploratory Data Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      298 reviews

      Intermediate · Specialization · 3 - 6 Months

    Applied Statistics learners also search

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    1…454647…195

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

    • Cálculo Diferencial e Integral unidos por el Teorema Fundamental del Cálculo: Tecnológico de Monterrey
    • Data Management and Visualization: Wesleyan University
    • Text Retrieval and Search Engines: University of Illinois Urbana-Champaign
    • Increase SEO Traffic with WordPress: Coursera Project Network
    • Smart Analytics, Machine Learning, and AI on Google Cloud: Google Cloud
    • Globalización, Crecimiento Económico y Estabilidad: IE Business School
    • Reinforcement Learning for Trading Strategies: New York Institute of Finance
    • Foundations of marketing analytics: ESSEC Business School
    • Deep Learning and Reinforcement Learning: IBM
    • Sampling People, Networks and Records: University of Michigan

    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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