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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Coding for Everyone: C and C++

      Skills you'll gain: C++ (Programming Language), Debugging, C (Programming Language), Object Oriented Programming (OOP), Software Design Patterns, Code Review, Data Structures, Computer Programming, Algorithms, Command-Line Interface, Programming Principles, Program Development, Computer Science, Computational Thinking, Integrated Development Environments, Graph Theory, Artificial Intelligence, Software Technical Review, File Systems, Game Design

      4.5
      Rating, 4.5 out of 5 stars
      ·
      9.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Y

      Yale University

      Introduction to Negotiation: A Strategic Playbook for Becoming a Principled and Persuasive Negotiator

      Skills you'll gain: Negotiation, Contract Negotiation, Conflict Management, Mediation, Leadership, Communication, Persuasive Communication, Influencing, Relationship Building, Game Theory, Strategic Decision-Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.1K reviews

      Mixed · Course · 1 - 3 Months

    • S

      Stanford University

      Game Theory

      Skills you'll gain: Game Theory, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Behavioral Economics, Probability, Economics, Markov Model, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Excel

      Skills you'll gain: Excel Macros, Prompt Engineering, Microsoft Excel, Data Cleansing, Excel Formulas, Pivot Tables And Charts, Microsoft Copilot, Dashboard, Forecasting, Data Presentation, Data Storytelling, Data Processing, Data Visualization Software, Data Manipulation, Data Visualization, Predictive Modeling, Data Quality, Statistical Analysis, Data Transformation, Data Analysis

      4.1
      Rating, 4.1 out of 5 stars
      ·
      93 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
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      I

      IBM

      IBM Systems Analyst

      Skills you'll gain: Data Storytelling, Business Analysis, Systems Development Life Cycle, Business Process Modeling, Process Optimization, Requirements Management, Business Requirements, Stakeholder Management, Stakeholder Engagement, Systems Analysis, Risk Analysis, Requirements Analysis, Data Visualization Software, Information Technology, Dashboard, Business Systems Analysis, IBM Cognos Analytics, Computer Hardware, Cloud Computing, Network Troubleshooting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • K

      Knowledge Accelerators

      From Excel to Power BI

      Skills you'll gain: Power BI, Dashboard, Data Presentation, Data Visualization Software, Interactive Data Visualization, Data Import/Export, Business Intelligence, Microsoft Excel, Data Analysis, Data-Driven Decision-Making, Data Sharing, Data Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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

    • 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, Business Analytics, Financial Modeling, Data-Driven Decision-Making, Loans, Cash Flows

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      60 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…101112…267

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

    • Coding for Everyone: C and C++: University of California, Santa Cruz
    • Natural Language Processing: DeepLearning.AI
    • Introduction to Negotiation: A Strategic Playbook for Becoming a Principled and Persuasive Negotiator: Yale University
    • Game Theory: Stanford University
    • Algorithms: Stanford University
    • Microsoft Excel: Microsoft
    • Introduction to Data Science in Python: University of Michigan
    • IBM Systems Analyst: IBM
    • From Excel to Power BI: Knowledge Accelerators
    • Fundamentals of Quantitative Modeling: University of Pennsylvania

    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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