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    Results for "advanced statistics"

    • Status: Free
      Free
      C

      Coursera Instructor Network

      Microsoft Excel VBA and Macros

      Skills you'll gain: Excel Macros, Microsoft Excel, Data Manipulation, Visual Basic (Programming Language), Data Analysis, Productivity Software, Automation, Strategic Decision-Making

      4.5
      Rating, 4.5 out of 5 stars
      ·
      164 reviews

      Beginner · Course · 1 - 4 Weeks

    • K

      Kennesaw State University

      Six Sigma Green Belt

      Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Process Capability, Team Management, Quality Improvement, Root Cause Analysis, Six Sigma Methodology, Lean Six Sigma, Lean Methodologies, Exploratory Data Analysis, Process Improvement, Quality Control, Probability & Statistics, Operational Excellence, Statistical Analysis, Process Analysis, Process Mapping, Correlation Analysis, Business Process Management, Data Analysis

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

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

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

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      The Business of Health Care

      Skills you'll gain: People Management, Financial Reporting, Health Disparities, Financial Statements, Health Care Administration, Health Systems, Income Statement, Employee Performance Management, Financial Analysis, Leadership and Management, Decision Making, Organizational Change, Organizational Structure, Lean Methodologies, Risk Analysis, Cash Flows, Health Care, Healthcare Industry Knowledge, Operational Efficiency, Health Policy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Programming Principles, Computer Science, Statistical Analysis, Computational Thinking, Big Data, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of Amsterdam

      Data Analytics for Lean Six Sigma

      Skills you'll gain: Lean Six Sigma, Statistical Hypothesis Testing, Minitab, Regression Analysis, Data Visualization Software, Probability Distribution, Descriptive Statistics, Data Analysis, Statistical Analysis, Box Plots, Analytics, Process Improvement, Correlation Analysis, Variance Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · 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, Deep Learning, Data Analysis, Regression Analysis, Statistical Inference, Applied Machine Learning, Machine Learning Algorithms, Data Processing, Machine Learning, Statistical Analysis, Data Access, Anomaly Detection, 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

    • U

      University of Illinois Urbana-Champaign

      Managerial Economics and Business Analysis

      Skills you'll gain: Descriptive Statistics, Supply And Demand, Market Dynamics, Sampling (Statistics), Statistical Inference, Business Analytics, Financial Systems, Financial Policy, Banking, Probability Distribution, Analytics, Statistical Analysis, Statistical Hypothesis Testing, Statistics, Regression Analysis, Microsoft Excel, Economics, Financial Market, Business Economics, Risk Management

      Build toward a degree

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

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • K

      Kennesaw State University

      Six Sigma Black Belt

      Skills you'll gain: Statistical Process Controls, Lean Six Sigma, Six Sigma Methodology, Lean Methodologies, Process Improvement, Team Management, Process Capability, Lean Manufacturing, Data Collection, Knowledge Transfer, Team Building, Statistical Hypothesis Testing, Meeting Facilitation, Quality Improvement, Continuous Improvement Process, Conflict Management, Performance Measurement, Sampling (Statistics), Team Leadership, Organizational Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      709 reviews

      Intermediate · Specialization · 3 - 6 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

    • I

      IBM

      Introduction to Software Engineering

      Skills you'll gain: Software Development Life Cycle, Development Environment, Software Engineering, Software Development Tools, Software Architecture, Software Design, Programming Principles, Unified Modeling Language, Agile Methodology, Software Development, Scrum (Software Development), Cloud Development, Integrated Development Environments, Back-End Web Development, Front-End Web Development, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Beginner · Course · 1 - 3 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…131415…260

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

    • Microsoft Excel VBA and Macros: Coursera Instructor Network
    • Six Sigma Green Belt: Kennesaw State University
    • Reinforcement Learning: University of Alberta
    • The Business of Health Care: University of Pennsylvania
    • Introduction to Genomic Technologies: Johns Hopkins University
    • Data Analytics for Lean Six Sigma: University of Amsterdam
    • IBM Machine Learning: IBM
    • Managerial Economics and Business Analysis: University of Illinois Urbana-Champaign
    • Meta Data Analyst: Meta
    • Six Sigma Black Belt: Kennesaw State 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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