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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

    • G

      Google Cloud

      Work with Gemini Models in BigQuery

      Skills you'll gain: Generative AI, Predictive Modeling, Applied Machine Learning, Predictive Analytics, Google Cloud Platform, Big Data, Artificial Intelligence and Machine Learning (AI/ML), SQL, Python Programming, Customer Relationship Management

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Data Manipulation with dplyr in R

      Skills you'll gain: Data Manipulation, Tidyverse (R Package), Data Wrangling, R Programming, Exploratory Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • I

      Illinois Tech

      Data Preparation and Analysis

      Skills you'll gain: Machine Learning Algorithms, Statistical Analysis, Data Visualization, Data Analysis, Exploratory Data Analysis, Data Presentation, Data Cleansing, Applied Machine Learning, Analytics, Machine Learning, Data Science, Regression Analysis, Data Manipulation, Data Mining, Statistical Modeling, Python Programming, Feature Engineering, Scikit Learn (Machine Learning Library), Unsupervised Learning, Classification And Regression Tree (CART)

      Build toward a degree

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Analyze Data in Azure ML Studio

      Skills you'll gain: Descriptive Statistics, Jupyter, Microsoft Azure, Matplotlib, Feature Engineering, Scatter Plots, Data Analysis, Statistics, Exploratory Data Analysis, Seaborn, Data Visualization Software, Correlation Analysis, Applied Machine Learning

      Beginner · Guided Project · Less Than 2 Hours

    • J

      Johns Hopkins University

      Data Science Decisions in Time: Using Data Effectively

      Skills you'll gain: Reinforcement Learning, Data-Driven Decision-Making, Strategic Decision-Making, Markov Model, Time Series Analysis and Forecasting, Bayesian Statistics, Predictive Analytics, Anomaly Detection, Probability Distribution, Machine Learning Methods, Statistical Analysis, Sampling (Statistics)

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Launching into Machine Learning em Português Brasileiro

      Skills you'll gain: Exploratory Data Analysis, Data Quality, Applied Machine Learning, Data Cleansing, Machine Learning, MLOps (Machine Learning Operations), Machine Learning Algorithms, Supervised Learning, Google Cloud Platform, Data Processing, Data Analysis, Predictive Modeling, Big Data, Statistical Analysis, Sampling (Statistics), Regression Analysis, Performance Tuning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      32 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Florida

      Agroforestry II: Major Systems of the World

      Skills you'll gain: Land Management, Natural Resource Management, Environment and Resource Management, Systems Thinking, Environment, Cultural Diversity, Spatial Analysis, Environmental Science, Research

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Linear Regression Modeling for Health Data

      Skills you'll gain: Statistical Modeling, Regression Analysis, Statistical Methods, Statistical Inference, Probability & Statistics, Correlation Analysis, Data Analysis, Statistical Analysis, Statistical Hypothesis Testing, Predictive Modeling

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Instructor Network

      The Beginner’s Guide to Business Negotiation

      Skills you'll gain: Negotiation, Contract Negotiation, Influencing, Communication, Relationship Building, Persuasive Communication, Interpersonal Communications, Rapport Building, Verbal Communication Skills, Trustworthiness, Collaboration, Personal Attributes, Active Listening, Goal Setting, Overcoming Obstacles

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      Sungkyunkwan University

      Machine Learning Algorithms

      Skills you'll gain: Machine Learning Algorithms, Decision Tree Learning, Unsupervised Learning, Machine Learning, Supervised Learning, Python Programming, Algorithms, Linear Algebra, Bayesian Statistics, Probability & Statistics

      3.5
      Rating, 3.5 out of 5 stars
      ·
      8 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      M

      MathWorks

      Data Science Companion

      Skills you'll gain: Data Science, Data Processing, Applied Machine Learning, Machine Learning, Supervised Learning, Geographic Information Systems, Big Data, Data Visualization, Data Analysis, Data Integration, Amazon Web Services, Cloud Computing, Matlab, Predictive Modeling, Classification And Regression Tree (CART), Regression Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      13 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      إنشاء صفحة أعمال مجانية باستخدام Blogger

      Skills you'll gain: Blogs, Search Engine Optimization, Brand Marketing, Content Marketing, Keyword Research, Content Creation, Web Analytics, Customer Engagement, Thought Leadership, Customer Relationship Building, Content Management Systems, Business Marketing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17 reviews

      Beginner · Guided Project · Less Than 2 Hours

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    1…139140141…197

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

    • Work with Gemini Models in BigQuery: Google Cloud
    • Data Manipulation with dplyr in R: Coursera Project Network
    • Data Preparation and Analysis: Illinois Tech
    • Analyze Data in Azure ML Studio: Coursera Project Network
    • Data Science Decisions in Time: Using Data Effectively: Johns Hopkins University
    • Launching into Machine Learning em Português Brasileiro: Google Cloud
    • Agroforestry II: Major Systems of the World: University of Florida
    • Linear Regression Modeling for Health Data: University of Michigan
    • The Beginner’s Guide to Business Negotiation : Coursera Instructor Network
    • Machine Learning Algorithms: Sungkyunkwan 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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