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    Results for "advanced statistics"

    • S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Business Communication

      Skills you'll gain: Business Writing, Conflict Management, Teamwork, Constructive Feedback, Business Correspondence, Decision Making, Cooperation, Business Communication, Collaboration, Diversity Awareness, Recognizing Others, Mediation, Writing, Organizational Skills, Interpersonal Communications, Concision, Team Motivation, Tactfulness, Performance Review, Employee Performance Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      10K reviews

      Beginner · Specialization · 3 - 6 Months

    • N

      New York Institute of Finance

      Risk Management

      Skills you'll gain: Credit Risk, Operational Risk, Risk Management, Risk Management Framework, Business Risk Management, Risk Modeling, Risk Mitigation, Financial Market, Enterprise Risk Management (ERM), Risk Appetite, Risk Control, Derivatives, Governance, Portfolio Management, Risk Analysis, Capital Markets, Investment Management, Financial Analysis, Market Data, Key Performance Indicators (KPIs)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Google Business Intelligence

      Skills you'll gain: Business Intelligence, Data Modeling, Dashboard, Database Design, Extract, Transform, Load, Data Integration, Stakeholder Engagement, Data Warehousing, Data Presentation, Performance Tuning, Data Pipelines, Data Visualization Software, Business Reporting, Data Integrity, Business Analytics, Real Time Data, Requirements Elicitation, Scalability, Business Process, Data-Driven Decision-Making

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      S

      Stanford University

      Cryptography I

      Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Kinesiology, Injury Prevention, Statistical Machine Learning, Analytics, Data Analysis, Statistical Analysis, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      255 reviews

      Intermediate · Specialization · 3 - 6 Months

    • 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

    • M

      Macquarie University

      Excel Skills for Business: Intermediate I

      Skills you'll gain: Microsoft Excel, Dashboard, Spreadsheet Software, Excel Formulas, Data Analysis Expressions (DAX), Data Visualization, Consolidation, Business Reporting, Data Management, Data Cleansing, Automation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      17K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      U

      University of California, Santa Cruz

      C and Go: Classical and Modern Programming

      Skills you'll gain: Go (Programming Language), Debugging, C (Programming Language), Data Structures, C++ (Programming Language), Object Oriented Design, Object Oriented Programming (OOP), Code Review, Programming Principles, Computer Programming, Unit Testing, Algorithms, Command-Line Interface, Program Development, Integrated Development Environments, Software Testing, Computer Science, Computational Thinking, File Management, Integration Testing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      7.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Business Data Management and Communication

      Skills you'll gain: Data Storytelling, Revenue Recognition, Financial Statements, Data Presentation, Data Visualization, Accrual Accounting, Cash Flows, Financial Accounting, Data Collection, Bookkeeping, Tidyverse (R Package), Income Statement, Data Processing, Data Visualization Software, Business Valuation, Business Analytics, Balance Sheet, Data Quality, Asset Management, Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Hardware Architecture, Systems Architecture, Artificial Intelligence, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    advanced linear models for data science 2: statistical linear models
    1…111213…260

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

    • Algorithms: Stanford University
    • Business Communication: University of Colorado Boulder
    • Risk Management: New York Institute of Finance
    • Google Business Intelligence: Google
    • Cryptography I: Stanford University
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Sports Performance Analytics: University of Michigan
    • Biostatistics in Public Health: Johns Hopkins University
    • Excel Skills for Business: Intermediate I: Macquarie University
    • C and Go: Classical and Modern Programming: University of California, Santa Cruz

    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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