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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

    • T

      The Hong Kong University of Science and Technology

      Mastering Statics

      Skills you'll gain: Structural Analysis, Mechanics, Engineering Calculations, Mechanical Engineering, Civil Engineering, Engineering Analysis, Engineering Drawings, Geometry, Algebra, Applied Mathematics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      226 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Alberta

      Science Literacy

      Skills you'll gain: Scientific Methods, General Science and Research, Research Methodologies, Research, Research Design, Peer Review, Experimentation, Statistical Methods, Media and Communications, Correlation Analysis, Probability & Statistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      263 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Relational Database Administration (DBA)

      Skills you'll gain: Database Management, Database Architecture and Administration, Relational Databases, Operational Databases, Database Systems, IBM DB2, MySQL, Performance Tuning, PostgreSQL, Disaster Recovery, Data Storage Technologies, Database Design, System Monitoring, Role-Based Access Control (RBAC), User Accounts, Encryption

      4.4
      Rating, 4.4 out of 5 stars
      ·
      237 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Genome Sequencing (Bioinformatics II)

      Skills you'll gain: Bioinformatics, Graph Theory, Molecular Biology, Microbiology, Pharmacology, Infectious Diseases, Computational Thinking, Applied Mathematics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      318 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of London

      Mathematics for Computer Science

      Skills you'll gain: Graphing, Computational Thinking, Arithmetic, Applied Mathematics, Mathematical Modeling, General Mathematics, Computer Science, Computer Graphics, Systems Of Measurement, Cryptography

      4.1
      Rating, 4.1 out of 5 stars
      ·
      238 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Docker (Software), Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      320 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate 日本語版

      Skills you'll gain: Dataflow, Google Cloud Platform, Data Pipelines, Data Lakes, MLOps (Machine Learning Operations), Data Warehousing, Real Time Data, Data Management, Data Infrastructure, Cloud Engineering, Data Processing, Unstructured Data, Cloud Storage, Applied Machine Learning, Tensorflow, Big Data, Data Visualization, Extract, Transform, Load, Dashboard, Data Architecture

      4.4
      Rating, 4.4 out of 5 stars
      ·
      296 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Data Analytics in the Public Sector with R

      Skills you'll gain: Exploratory Data Analysis, Data Visualization, Plot (Graphics), Statistical Analysis, Data Presentation, Ggplot2, Program Evaluation, Policy Analysis, Surveys, Data Ethics, Data Analysis, Tidyverse (R Package), Statistical Visualization, R Programming, Statistical Methods, Data Visualization Software, Statistical Hypothesis Testing, Demography, Political Sciences, Public Policies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      76 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Splunk Inc.

      Splunk Search Expert

      Skills you'll gain: Splunk, Correlation Analysis, Data Transformation, Data Manipulation, Data Visualization Software, Data Wrangling, Performance Tuning, Statistical Methods, Dashboard, Data Analysis Expressions (DAX), Statistical Analysis, Data Processing, Security Information and Event Management (SIEM), Data Analysis, Data Synthesis, Data Modeling, Ad Hoc Reporting, Time Series Analysis and Forecasting, Exploratory Data Analysis, Transaction Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      259 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Recommendation Systems on Google Cloud

      Skills you'll gain: Reinforcement Learning, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Deep Learning, Applied Machine Learning, Unsupervised Learning, Artificial Neural Networks, Feature Engineering, Predictive Modeling, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      478 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Foundations of Sports Analytics: Data, Representation, and Models in Sports

      Skills you'll gain: Statistical Methods, Regression Analysis, Data Cleansing, Statistical Hypothesis Testing, Correlation Analysis, Matplotlib, Data Manipulation, Data Visualization, Statistical Analysis, Scatter Plots, Probability & Statistics, R Programming, Data Analysis, Descriptive Statistics, Pandas (Python Package), Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      188 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Data Engineering, Big Data and ML on Google Cloud 日本語版

      Skills you'll gain: Dataflow, Google Cloud Platform, Data Pipelines, Data Lakes, Data Warehousing, Real Time Data, Data Management, Data Infrastructure, Cloud Engineering, Unstructured Data, Cloud Storage, MLOps (Machine Learning Operations), Applied Machine Learning, Tensorflow, Big Data, Data Visualization, Extract, Transform, Load, Dashboard, Data Architecture, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      289 reviews

      Intermediate · Specialization · 3 - 6 Months

    Applied Statistics learners also search

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    1…495051…198

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

    • Mastering Statics: The Hong Kong University of Science and Technology
    • Science Literacy : University of Alberta
    • Relational Database Administration (DBA): IBM
    • Genome Sequencing (Bioinformatics II): University of California San Diego
    • Mathematics for Computer Science: University of London
    • IBM AI Enterprise Workflow: IBM
    • Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate 日本語版: Google Cloud
    • Data Analytics in the Public Sector with R: University of Michigan
    • Splunk Search Expert: Splunk Inc.
    • Recommendation Systems on Google Cloud: Google Cloud

    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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