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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: New
      New
      Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistics and Data Analysis with R

      Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Regression Analysis, Statistical Programming, Probability Distribution, Statistical Analysis, R Programming, Data Import/Export, Statistical Modeling, Statistical Methods, Plot (Graphics), Statistics, Data Manipulation, Analysis, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Using probability distributions for real world problems in R

      Skills you'll gain: Statistical Inference, Probability Distribution, R Programming, Statistical Visualization, Statistics, Statistical Analysis, Statistical Hypothesis Testing, Data Analysis, Data Science, Probability

      4.8
      Rating, 4.8 out of 5 stars
      ·
      30 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      UX Research at Scale: Surveys, Analytics, Online Testing

      Skills you'll gain: Surveys, UI/UX Research, User Research, Survey Creation, Sampling (Statistics), A/B Testing, Qualitative Research, Usability Testing, Research Methodologies, Web Analytics and SEO, Data Collection, Research Design, Sample Size Determination, Analytics, Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      206 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Survival Analysis in R for Public Health

      Skills you'll gain: Biostatistics, Statistical Analysis, R Programming, Regression Analysis, Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Analysis, Data Import/Export, Statistical Hypothesis Testing, Descriptive Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      324 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      Universidad Austral

      Estadística aplicada a los negocios

      Skills you'll gain: Regression Analysis, Statistical Inference, Descriptive Statistics, Business Risk Management, Risk Analysis, Business Analytics, Statistics, Sampling (Statistics), Microsoft Excel, Data Analysis, Probability, Statistical Analysis, Data-Driven Decision-Making, Probability Distribution, Statistical Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      756 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      N

      New York University

      Fundamentals of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Machine Learning, Predictive Modeling, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks, Jupyter

      3.7
      Rating, 3.7 out of 5 stars
      ·
      338 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      T

      Tecnológico de Monterrey

      Analíticas de Marketing Digital

      Skills you'll gain: Web Analytics, Google Analytics, Web Analytics and SEO, Social Media, Search Engine Marketing, Social Media Marketing, Marketing Analytics, Market Research, Digital Marketing, Search Engine Optimization, Marketing Effectiveness, Content Performance Analysis, Analytical Skills, Online Advertising, Social Media Strategy, Email Marketing, Analytics, Business Metrics, Key Performance Indicators (KPIs), Facebook

      4.7
      Rating, 4.7 out of 5 stars
      ·
      218 reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rutgers the State University of New Jersey

      Business Intelligence and Competitive Analysis

      Skills you'll gain: Competitive Intelligence, Competitive Analysis, Market Intelligence, Management Consulting, Business Consulting, Consulting, Business Strategy, Data Analysis Software, Business Intelligence, Company, Product, and Service Knowledge, Business Analytics, Analytics, Market Analysis, Benchmarking, Analysis, Performance Analysis, Trend Analysis, Business Metrics, Key Performance Indicators (KPIs), Financial Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      236 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Instructor Network

      Strategic HRM: Talent, Performance, Compensation Design

      Skills you'll gain: Performance Appraisal, Human Resource Strategy, Human Resources, Compensation Strategy, Talent Management, Compensation Management, Performance Management, Organizational Development, Employee Engagement, Workforce Development, Talent Acquisition, Employee Retention

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92 reviews

      Beginner · Course · 1 - 4 Weeks

    • É

      École Polytechnique

      Aléatoire : une introduction aux probabilités - Partie 1

      Skills you'll gain: Probability, Probability Distribution, Simulations, Probability & Statistics, Statistical Methods, Mathematical Modeling, Mathematical Theory & Analysis, Applied Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      105 reviews

      Mixed · Course · 1 - 3 Months

    • P

      Peking University

      Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

      Skills you'll gain: Bioinformatics, Markov Model, Molecular Biology, Computational Thinking, Biology, Database Software, Data Analysis, Algorithms, Machine Learning Algorithms, Probability & Statistics, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      279 reviews

      Mixed · Course · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Data Mining Foundations and Practice

      Skills you'll gain: Data Mining, Unsupervised Learning, Data Warehousing, Data Pipelines, Data Processing, Data Integration, Data Modeling, Data Science, Data Cleansing, Big Data, Supervised Learning, Data Transformation, Machine Learning Methods, Text Mining, Data Quality, Classification And Regression Tree (CART), Unstructured Data, Data Analysis, Data Presentation, Analytical Skills

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      134 reviews

      Intermediate · Specialization · 1 - 3 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…555657…198

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

    • Statistics and Data Analysis with R: University of Colorado Boulder
    • Using probability distributions for real world problems in R: Coursera Project Network
    • UX Research at Scale: Surveys, Analytics, Online Testing: University of Michigan
    • Survival Analysis in R for Public Health: Imperial College London
    • Estadística aplicada a los negocios: Universidad Austral
    • Fundamentals of Machine Learning in Finance: New York University
    • Analíticas de Marketing Digital: Tecnológico de Monterrey
    • Business Intelligence and Competitive Analysis: Rutgers the State University of New Jersey
    • Strategic HRM: Talent, Performance, Compensation Design: Coursera Instructor Network
    • Aléatoire : une introduction aux probabilités - Partie 1: École Polytechnique

    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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