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    • Advanced Statistics

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    451 results for "advanced statistics"

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      IBM Skills Network

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Analysis, Data Visualization, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Management, Data Analysis Software, Data Science, Plot (Graphics), Big Data, Databases, NoSQL, Python Programming, SQL, Statistical Programming, Data Visualization Software, Statistical Visualization, Basic Descriptive Statistics, Cloud Computing, Data Mining, Data Structures, Data Warehousing, General Statistics, Machine Learning, Mathematics, Probability & Statistics, Accounting, Apache, Computer Programming, Extract, Transform, Load, Interactive Data Visualization, Leadership and Management, Operating Systems, Professional Development, System Programming

      4.7

      (15.1k reviews)

      Beginner · Specialization · 3-6 Months

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      Macquarie University

      Excel Skills for Business

      Skills you'll gain: Business Analysis, Microsoft Excel, Spreadsheet Software, Data Analysis, Plot (Graphics), Data Visualization, Basic Descriptive Statistics, Computational Logic, Computer Architecture, Data Analysis Software, Data Management, Data Mining, Data Visualization Software, Extract, Transform, Load, Interactive Data Visualization, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science

      4.9

      (56.6k reviews)

      Beginner · Specialization · 3-6 Months

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      DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Algebra, Linear Algebra, Mathematics, Mathematical Theory & Analysis, Artificial Neural Networks, Computer Programming, Deep Learning, Econometrics, General Statistics, Machine Learning, Probability & Statistics, Python Programming, Regression, Statistical Programming

      4.4

      (215 reviews)

      Beginner · Course · 1-4 Weeks

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      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Mathematics, Linear Algebra, Algebra, Machine Learning, Python Programming, Probability & Statistics, General Statistics, Calculus, Computer Programming, Mathematical Theory & Analysis, Applied Mathematics, Statistical Programming, Algorithms, Dimensionality Reduction, Regression, Theoretical Computer Science, Basic Descriptive Statistics, Data Analysis, Probability Distribution, Artificial Neural Networks, Computer Graphic Techniques, Computer Graphics, Computer Networking, Deep Learning, Differential Equations, Experiment, Machine Learning Algorithms, Network Model

      4.6

      (13.6k reviews)

      Beginner · Specialization · 3-6 Months

    • Free

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      Duke University

      Data Science Math Skills

      Skills you'll gain: Mathematics, Probability & Statistics, General Statistics, Algebra, Bayesian Statistics, Computational Logic, Data Visualization, Graph Theory, Mathematical Theory & Analysis, Plot (Graphics), Probability Distribution, Theoretical Computer Science

      4.5

      (11k reviews)

      Beginner · Course · 1-3 Months

    • Free

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      Erasmus University Rotterdam

      Econometrics: Methods and Applications

      Skills you'll gain: Advertising, Algebra, Communication, Econometrics, Forecasting, General Statistics, Marketing, Mathematics, Probability & Statistics, Regression

      4.6

      (1.1k reviews)

      Mixed · Course · 1-3 Months

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      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Basic Descriptive Statistics, Python Programming, Data Analysis, Data Structures, Data Mining, Exploratory Data Analysis, Statistical Analysis, Correlation And Dependence, Statistical Tests, Data Architecture, Estimation, General Statistics, Linear Algebra, Regression, Statistical Visualization, Computational Logic, Computer Programming, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Programming Principles, Statistical Programming, Theoretical Computer Science

      4.5

      (26.6k reviews)

      Intermediate · Course · 1-4 Weeks

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      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Probability & Statistics, General Statistics, Regression, Experiment, Business Analysis, Data Analysis, Statistical Analysis, Mathematics, Statistical Tests, Econometrics, Machine Learning, Machine Learning Algorithms, Calculus, Communication, Linear Algebra, Marketing, R Programming, SQL

      4.1

      (31 reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Pennsylvania

      Operations Analytics

      Skills you'll gain: Business Analysis, Correlation And Dependence, Data Analysis, Forecasting, General Statistics, Operational Analysis, Operations Management, Operations Research, Probability & Statistics, Probability Distribution, Research and Design, Spreadsheet Software, Statistical Analysis, Strategy and Operations, Supply Chain and Logistics, Basic Descriptive Statistics, Data Visualization, Microsoft Excel, Plot (Graphics), Statistical Tests, Statistical Visualization, Accounting, Applied Mathematics, Computational Logic, Computer Programming, Computer Programming Tools, Data Analysis Software, Data Management, Data Structures, Decision Making, Entrepreneurship, Leadership and Management, Theoretical Computer Science

      4.7

      (4.9k reviews)

      Mixed · Course · 1-4 Weeks

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      PwC

      Problem Solving with Excel

      Skills you'll gain: Business, Business Analysis, Spreadsheet Software, Microsoft Excel, Data Science, General Statistics, Probability & Statistics, Computer Programming, Data Analysis, Data Analysis Software, Data Mining, Regression, Statistical Analysis

      4.7

      (5.2k reviews)

      Beginner · Course · 1-4 Weeks

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      Tsinghua University

      Learn English

      Skills you'll gain: Communication, Business Psychology, Leadership and Management, Culture, Writing, Marketing, Research and Design, Sales, Business Analysis, Computer Programming, Entrepreneurship, Advertising, Computer Architecture, Computer Networking, E-Commerce, Network Architecture, Visual Design, Application Development, Bioinformatics, Critical Thinking, Human Learning, Other Programming Languages, Probability & Statistics, Resilience, Software Engineering, Strategy and Operations

      4.3

      (776 reviews)

      Beginner · Specialization · 3-6 Months

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      Free

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      University of North Texas

      Math Prep: College & Work Ready

      Skills you'll gain: Mathematics, Algebra, Entrepreneurship, General Statistics, Leadership and Management, Linear Algebra, Probability & Statistics, Problem Solving, Research and Design, Accounting, Financial Accounting, Geometry, Graph Theory

      4.1

      (79 reviews)

      Beginner · Course · 1-4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced linear models for data science 2: statistical linear models
    1…456…38

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

    • Data Analysis and Visualization Foundations: IBM Skills Network
    • Excel Skills for Business: Macquarie University
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
    • Mathematics for Machine Learning: Imperial College London
    • Data Science Math Skills: Duke University
    • Econometrics: Methods and Applications: Erasmus University Rotterdam
    • Introduction to Data Science in Python: University of Michigan
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Operations Analytics: University of Pennsylvania
    • Problem Solving with Excel: PwC

    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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