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    Results for "advanced statistics"

    • R

      Rutgers the State University of New Jersey

      Supply Chain Logistics

      Skills you'll gain: Warehouse Management, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics, Logistics, Transportation Operations, Supply Chain Management, Supply Chain, Customer Service, Operating Cost

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Data Visualization with Python

      Skills you'll gain: Data Visualization Software, Plotly, Data Visualization, Dashboard, Interactive Data Visualization, Matplotlib, Seaborn, Data Presentation, Data Analysis, Geospatial Information and Technology, Pandas (Python Package), Scatter Plots, Histogram, Heat Maps, Box Plots

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Generative AI, Dimensionality Reduction, Reinforcement Learning, Applied Machine Learning, Deep Learning, Data Analysis, Regression Analysis, Statistical Inference, Data Processing, Machine Learning, Statistical Analysis, Data Access, Statistical Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      C

      Coursera Instructor Network

      Active Listening: Enhancing Communication Skills

      Skills you'll gain: Active Listening, Non-Verbal Communication, Cultural Diversity, Conflict Management, Emotional Intelligence, Empathy, Interpersonal Communications, Leadership, Rapport Building, Collaboration, Communication, Self-Awareness, Adaptability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      433 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

    • I

      Illinois Tech

      A Comprehensive Excel Masterclass

      Skills you'll gain: Capital Budgeting, Data Visualization, Microsoft Excel, Dashboard, Business Intelligence, Interactive Data Visualization, Excel Formulas, Financial Analysis, Data Analysis Expressions (DAX), Pivot Tables And Charts, Key Performance Indicators (KPIs), Google Sheets, Financial Modeling, Data-Driven Decision-Making, Loans, Cash Flows

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      59 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Presentation, Data Analysis, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Ethics, Business Workflow Analysis, Stakeholder Communications, Professional Networking, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Advanced · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistical Analysis, Applied Mathematics, Advanced Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      187 reviews

      Advanced · Course · 1 - 3 Months

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      The University of Sydney

      Introduction to Calculus

      Skills you'll gain: Calculus, Integral Calculus, Algebra, Advanced Mathematics, Geometry, Applied Mathematics, Engineering Calculations, Trigonometry, Arithmetic, Derivatives, Mathematical Modeling, Graphing, Estimation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Executive Data Science

      Skills you'll gain: Data Quality, Exploratory Data Analysis, Employee Onboarding, Data Management, Team Motivation, Technical Communication, Data Analysis, Data Presentation, Project Management, Interviewing Skills, Data Science, Data-Driven Decision-Making, Management Training And Development, Organizational Leadership, Data Strategy, Team Management, Analytical Skills, Project Implementation, Team Building, Project Design

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…121314…262

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

    • Supply Chain Logistics: Rutgers the State University of New Jersey
    • Data Visualization with Python: IBM
    • IBM Machine Learning: IBM
    • Active Listening: Enhancing Communication Skills: Coursera Instructor Network
    • Self-Driving Cars: University of Toronto
    • A Comprehensive Excel Masterclass: Illinois Tech
    • Foundations of Data Science: Google
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
    • Six Sigma Yellow Belt: Kennesaw State University
    • Introduction to Calculus: The University of Sydney

    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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