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    Results for "advanced statistics"

    • T

      The University of Edinburgh

      Fundamentals of Music Theory

      Skills you'll gain: Music Theory, Music, Classical Music, Musical Composition

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Go and C++: Programming in Two Successor Languages of C

      Skills you'll gain: C++ (Programming Language), Go (Programming Language), Data Structures, Object Oriented Programming (OOP), Software Design Patterns, Debugging, Object Oriented Design, Programming Principles, Unit Testing, Algorithms, C (Programming Language), Program Development, Integrated Development Environments, Computer Programming, Software Testing, Computer Science, Graph Theory, File Management, Artificial Intelligence, Integration Testing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Data Science Capstone

      Skills you'll gain: Plotly, Exploratory Data Analysis, Predictive Modeling, Data Science, Data-Driven Decision-Making, Data Presentation, Data Analysis, Pandas (Python Package), Web Scraping, Statistical Modeling, Data Wrangling, Machine Learning Methods, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.3K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Introduction to Sustainability

      Skills you'll gain: Environmental Policy, Environment, Water Resources, Demography, Energy and Utilities, Environmental Science, Environmental Resource Management, Socioeconomics, Policy Analysis, Natural Resource Management, Systems Thinking, Social Sciences, Trend Analysis, Economics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.6K reviews

      Mixed · Course · 1 - 3 Months

    • V

      Vanderbilt University

      Data Management for Clinical Research

      Skills you'll gain: Clinical Data Management, Data Capture, Clinical Research, Data Management, Data Collection, Data Sharing, Data Strategy, Data Quality, Sampling (Statistics), Data Integrity, Data Validation, Regulatory Compliance

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Introduction to Data Analysis Using Excel

      Skills you'll gain: Microsoft Excel, Pivot Tables And Charts, Graphing, Spreadsheet Software, Excel Formulas, Data Analysis, Histogram, Scatter Plots, Data Visualization Software, Data Manipulation, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      10K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Machine Learning in Python

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Dimensionality Reduction, Random Forest Algorithm

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      Duke University

      Introduction to Genetics and Evolution

      Skills you'll gain: Life Sciences, Molecular Biology, Biology, Biostatistics, Bioinformatics, Environment, Laboratory Research, Taxonomy, Scientific Methods, Experimentation, Mathematical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • Y

      Yale University

      A Law Student's Toolkit

      Skills you'll gain: Legal Strategy, Legal Research, Legal Writing, Case Law, Civil Procedures, Policy Analysis, Learning Strategies, Economics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Epidemiology in Public Health Practice

      Skills you'll gain: Epidemiology, Public Health, Spatial Data Analysis, Data Presentation, Public Health and Disease Prevention, Geographic Information Systems, Health Policy, Chronic Diseases, Health Systems, Infectious Diseases, Biostatistics, Risk Analysis, Investigation, Community Health, Health Care, Data Analysis, Program Evaluation, Health Information Management, Health Informatics, Continuous Monitoring

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Macquarie University

      Excel Fundamentals for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Spreadsheet Software, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.1K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Biostatistics in Public Health

      Skills you'll gain: Biostatistics, Statistical Hypothesis Testing, Regression Analysis, Sampling (Statistics), Statistical Methods, Statistical Visualization, Statistical Analysis, Epidemiology, Medical Science and Research, Quantitative Research, Descriptive Statistics, Statistical Inference, Data Literacy, Probability Distribution, Scientific Methods, Data Analysis, Public Health, Probability & Statistics, Advanced Analytics, Statistical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.3K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…161718…267

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

    • Fundamentals of Music Theory: The University of Edinburgh
    • Go and C++: Programming in Two Successor Languages of C: University of California, Santa Cruz
    • Applied Data Science Capstone: IBM
    • Introduction to Sustainability: University of Illinois Urbana-Champaign
    • Data Management for Clinical Research: Vanderbilt University
    • Introduction to Data Analysis Using Excel: Rice University
    • Applied Machine Learning in Python: University of Michigan
    • Introduction to Genetics and Evolution: Duke University
    • A Law Student's Toolkit: Yale University
    • Epidemiology in Public Health Practice: Johns Hopkins University

    Frequently Asked Questions about Advanced Statistics

    Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

    These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.‎

    Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

    Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.‎

    Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.‎

    You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.‎

    People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.‎

    If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.‎

    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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