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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

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Minnesota

      Human Resource Management: HR for People Managers

      Skills you'll gain: Performance Management, Performance Appraisal, Performance Review, Employee Performance Management, Compensation Management, Compensation Strategy, Compensation and Benefits, Constructive Feedback, Workforce Planning, Human Resource Strategy, Human Resources, Employee Onboarding, Recruitment, Recruitment Strategies, Human Capital, Compensation Analysis, Talent Acquisition, Human Resources Management and Planning, People Management, Job Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Process Data from Dirty to Clean

      Skills you'll gain: Data Cleansing, Sampling (Statistics), Data Integrity, Data Quality, Data Validation, Sample Size Determination, Data Analysis, Data Manipulation, SQL, Data Transformation, Spreadsheet Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Data Engineering Foundations

      Skills you'll gain: SQL, Web Scraping, Database Design, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Database Management, Data Warehousing, Databases, Stored Procedure, Data Manipulation, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Tableau Software, Relational Databases, Star Schema, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Applied DevOps Engineering

      Skills you'll gain: User Story, CI/CD, Istio, Open Web Application Security Project (OWASP), Continuous Integration, Kubernetes, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Agile Software Development, Code Coverage, Cloud-Native Computing, OpenShift, Cloud Applications, DevOps, Secure Coding, Grafana, System Monitoring, Agile Methodology

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Applied Software Engineering Fundamentals

      Skills you'll gain: Software Development Life Cycle, Software Architecture, Linux Commands, Unit Testing, Bash (Scripting Language), Shell Script, Git (Version Control System), GitHub, Software Design, Version Control, File Management, Jupyter, Scrum (Software Development), Application Deployment, Collaborative Software, Automation, Flask (Web Framework), Web Scraping, Python Programming, Software Testing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      47K reviews

      Beginner · Specialization · 3 - 6 Months

    • U
      I
      I

      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Computer Programming Tools, Automation, Data Analysis Software, Data Collection, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      112K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Python 3 Programming

      Skills you'll gain: Unified Modeling Language, JSON, Object Oriented Programming (OOP), Software Design, Debugging, Object Oriented Design, Data Processing, Web Scraping, Unit Testing, Programming Principles, Data Import/Export, Restful API, Python Programming, Image Analysis, Data Manipulation, Jupyter, Maintainability, Data Structures, Software Engineering, File Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      23K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Macquarie University

      Excel Skills for Business: Essentials

      Skills you'll gain: Microsoft Excel, Data Visualization, Spreadsheet Software, Excel Formulas, Data Management, Data Entry, Productivity Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      50K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Virginia

      Digital Product Management

      Skills you'll gain: Usability Testing, Agile Product Development, New Product Development, Continuous Delivery, Agile Software Development, User Story, Product Management, Agile Methodology, Product Testing, Agile Project Management, Team Performance Management, Team Management, Design Thinking, Team Building, Team Leadership, Product Improvement, Customer Analysis, Innovation, Analytics, Business Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      DevOps, Cloud, and Agile Foundations

      Skills you'll gain: User Story, Cloud Computing Architecture, Agile Software Development, Cloud Services, Agile Methodology, Kanban Principles, DevOps, Backlogs, Cloud Security, Cloud Technologies, Cloud Infrastructure, Sprint Retrospectives, Cloud Platforms, Agile Project Management, Cloud Hosting, Cloud Engineering, Cloud-Native Computing, CI/CD, Test Driven Development (TDD), Scrum (Software Development)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Specialization · 3 - 6 Months

    Applied Statistics learners also search

    R Statistics
    Beginner Statistics
    Statistics Projects
    Advanced Statistics
    Statistics
    Basic Statistics
    Statistics for Data Science
    Statistics With R
    1…678…198

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

    • Natural Language Processing: DeepLearning.AI
    • Human Resource Management: HR for People Managers: University of Minnesota
    • Process Data from Dirty to Clean: Google
    • Data Engineering Foundations: IBM
    • IBM Business Intelligence (BI) Analyst: IBM
    • IBM Applied DevOps Engineering: IBM
    • Applied Software Engineering Fundamentals: IBM
    • Data Science Foundations: University of London
    • Python 3 Programming: University of Michigan
    • Excel Skills for Business: Essentials: Macquarie 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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