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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: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Statistical Inference, Statistical Methods, Pandas (Python Package), Probability & Statistics, Risk Analysis, Statistics, Financial Trading, Financial Data, Data Manipulation, Statistical Analysis, Regression Analysis, Financial Analysis, Jupyter, Financial Modeling, Python Programming, Data Import/Export

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.4K reviews

      Intermediate · Course · 1 - 4 Weeks

    • S

      SAS

      Statistical Thinking for Industrial Problem Solving, presented by JMP

      Skills you'll gain: Exploratory Data Analysis, Data Compilation, Correlation Analysis, Data Collection, Statistical Inference, Statistical Process Controls, Statistical Methods, Predictive Modeling, Data Analysis, Statistical Hypothesis Testing, Data-Driven Decision-Making, Regression Analysis, Statistical Analysis, Experimentation, Probability & Statistics, Descriptive Statistics, Interactive Data Visualization

      4.9
      Rating, 4.9 out of 5 stars
      ·
      90 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Amsterdam

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Software, Statistical Analysis, Statistical Methods, Quantitative Research, Sampling (Statistics), Probability & Statistics, Regression Analysis, Probability Distribution

      4.3
      Rating, 4.3 out of 5 stars
      ·
      595 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Michigan

      Survey Data Collection and Analytics

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Survey Creation, Data Collection, Statistical Analysis, Data Analysis Software, Business Research, Interviewing Skills, Data Integration, Data Ethics, Research Design, Stata, R Programming, Data Quality, Data Analysis, Statistical Modeling, Qualitative Research, Statistical Methods, Statistical Programming, Data Cleansing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Statistics and Data Analysis with Excel, Part 1

      Skills you'll gain: Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Probability, Box Plots, Histogram, Probability Distribution, Probability & Statistics, Scatter Plots, Statistics, Descriptive Analytics, Microsoft Excel, Excel Formulas, Data Analysis, Spreadsheet Software, Bayesian Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      T

      The State University of New York

      Practical Time Series Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Statistical Analysis, Data Analysis, Data Visualization, Mathematical Modeling, Statistical Modeling, Predictive Analytics, Predictive Modeling, Correlation Analysis, Probability & Statistics, Descriptive Statistics, Statistical Inference

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Course · 1 - 3 Months

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      Status: Free
      Free
      E

      Erasmus University Rotterdam

      Econometrics: Methods and Applications

      Skills you'll gain: Econometrics, Time Series Analysis and Forecasting, Regression Analysis, Data Analysis, Statistical Analysis, Quantitative Research, Statistical Modeling, Statistics, Forecasting, Probability, Linear Algebra, Peer Review

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Mixed · Course · 1 - 3 Months

    • Placeholder
      D

      Duke University

      Bayesian Statistics

      Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Probability Distribution

      3.8
      Rating, 3.8 out of 5 stars
      ·
      794 reviews

      Intermediate · Course · 1 - 3 Months

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      I

      IIMA - IIM Ahmedabad

      Pre-MBA Statistics

      Skills you'll gain: Sampling (Statistics), Probability, Statistical Hypothesis Testing, Statistics, Probability Distribution, Statistical Methods, Statistical Inference, Estimation, Statistical Analysis, Descriptive Statistics, Sample Size Determination, Data Analysis, Data-Driven Decision-Making

      4.6
      Rating, 4.6 out of 5 stars
      ·
      263 reviews

      Beginner · Course · 1 - 3 Months

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      R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Sample Size Determination, Box Plots, Analytical Skills, Statistical Inference

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

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis, Data Processing, Unstructured Data

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

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

    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS
    • Inferential Statistics: University of Amsterdam
    • Survey Data Collection and Analytics: University of Michigan
    • Statistics and Data Analysis with Excel, Part 1: University of Colorado Boulder
    • Practical Time Series Analysis: The State University of New York
    • Econometrics: Methods and Applications: Erasmus University Rotterdam
    • Bayesian Statistics: Duke University
    • Pre-MBA Statistics: IIMA - IIM Ahmedabad
    • Business Statistics and Analysis: Rice 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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