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    Results for "applied statistics"

    • Coursera Project Network

      Time Series Data Visualization And Analysis Techniques

      Skills you'll gain: Time Series Analysis and Forecasting, Data Visualization Software, Statistical Visualization, Plot (Graphics), Box Plots, Anomaly Detection, Heat Maps, Exploratory Data Analysis, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      17 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free

      DeepLearning.AI

      Introduction to On-Device AI

      Skills you'll gain: Application Deployment, Performance Testing, Android Development, PyTorch (Machine Learning Library), Embedded Software, Deep Learning, Tensorflow, Hardware Architecture, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Real Time Data, Computer Vision

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13 reviews

      Beginner · Project · Less Than 2 Hours

    • 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

    • Coursera Project Network

      Análisis exploratorio de datos con Python y Pandas

      Skills you'll gain: Exploratory Data Analysis, Pandas (Python Package), Seaborn, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, NumPy, Data Cleansing, Descriptive Statistics, Python Programming

      4.3
      Rating, 4.3 out of 5 stars
      ·
      14 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • University of Colorado Boulder

      Association Rules Analysis

      Skills you'll gain: Unsupervised Learning, Anomaly Detection, Machine Learning Methods, Data Mining, Applied Machine Learning, Feature Engineering, Exploratory Data Analysis, Data Processing, Data Analysis, Machine Learning Algorithms, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 3 Months

    • Google Cloud

      Launching into Machine Learning en Français

      Skills you'll gain: Exploratory Data Analysis, Data Analysis, Applied Machine Learning, Data Quality, Data Cleansing, Machine Learning, Supervised Learning, Google Cloud Platform, Regression Analysis, Sampling (Statistics), Performance Tuning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 3 Months

    • SAS

      Distributed Programming in SAS® Viya® for Data Analysts

      Skills you'll gain: SAS (Software), Data Manipulation, Data Validation, Data Analysis, Data Access, Exploratory Data Analysis, Cloud Computing, Distributed Computing, Cloud Services, Data Processing, Data Transformation, Statistical Programming, Data Management, Cloud Computing Architecture, Data Import/Export, Servers, Statistical Software, SQL, Query Languages

      4.9
      Rating, 4.9 out of 5 stars
      ·
      13 reviews

      Beginner · Specialization · 3 - 6 Months

    • University of Colorado Boulder

      Data Understanding and Visualization

      Skills you'll gain: Matplotlib, Seaborn, Data Visualization, Data-Driven Decision-Making, Exploratory Data Analysis, Data Presentation, Plot (Graphics), Data Visualization Software, Descriptive Statistics, Data Storytelling, Pandas (Python Package), Statistical Methods, Data Analysis, Statistics, Statistical Analysis, Data Manipulation, Box Plots, Scatter Plots, Correlation Analysis, Histogram

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Vanderbilt University

      ChatGPT + Zapier: From Email Inbox to Excel Spreadsheet

      Skills you'll gain: Prompt Engineering, Microsoft Power Automate/Flow, ChatGPT, HubSpot CRM, Business Process Automation, Google Sheets, Workflow Management, Automation, Data Integration, JSON, Large Language Modeling, Unstructured Data

      Beginner · Course · 1 - 4 Weeks

    • University of Colorado Boulder

      American History Through Baseball

      Skills you'll gain: Labor Relations, Labor Law, Culture, Social Studies, World History, Cultural Diversity, Economic Development, Socioeconomics, Social Justice, Global Marketing, Anthropology, Business Economics, Demography, Social Sciences, Market Opportunities, Economics, Public Safety and National Security, International Relations, Trend Analysis, Political Sciences

      4.4
      Rating, 4.4 out of 5 stars
      ·
      13 reviews

      Beginner · Specialization · 3 - 6 Months

    • Korea Advanced Institute of Science and Technology(KAIST)

      Differential Equations Part III Systems of Equations

      Skills you'll gain: Differential Equations, Applied Mathematics, Advanced Mathematics, Linear Algebra, Calculus, Engineering Analysis, Mathematical Modeling

      4.1
      Rating, 4.1 out of 5 stars
      ·
      11 reviews

      Intermediate · Course · 1 - 3 Months

    • University of Colorado Boulder

      Modeling and Predicting Climate Anomalies

      Skills you'll gain: Matplotlib, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Applied Machine Learning, Statistical Analysis, Machine Learning, Pandas (Python Package), Regression Analysis, Environmental Policy, Data Science, Data Analysis, Scikit Learn (Machine Learning Library), Supervised Learning, NumPy, Environment, Environmental Issue, International Relations, Policy Analysis, Energy and Utilities

      Intermediate · Specialization · 1 - 3 Months

    Searches related to applied statistics

    applied statistics for data analytics
    statistics and applied data analysis
    1…136137138…197

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

    • Time Series Data Visualization And Analysis Techniques : Coursera Project Network
    • Introduction to On-Device AI: DeepLearning.AI
    • Agroforestry II: Major Systems of the World: University of Florida
    • Análisis exploratorio de datos con Python y Pandas: Coursera Project Network
    • Association Rules Analysis: University of Colorado Boulder
    • Launching into Machine Learning en Français: Google Cloud
    • Distributed Programming in SAS® Viya® for Data Analysts: SAS
    • Data Understanding and Visualization: University of Colorado Boulder
    • ChatGPT + Zapier: From Email Inbox to Excel Spreadsheet: Vanderbilt University
    • American History Through Baseball: University of Colorado Boulder

    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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