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    Results for "advanced statistics"

    • R

      Rutgers the State University of New Jersey

      Supply Market Analysis

      Skills you'll gain: Market Analysis, Supply Management, Supplier Management, Competitive Analysis, Strategic Sourcing, Financial Analysis, Procurement, Market Dynamics, Supply Chain Management, Risk Analysis, Competitive Intelligence, Trend Analysis, Business Strategy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      145 reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Arizona State University

      Response Surfaces, Mixtures, and Model Building

      Skills you'll gain: Regression Analysis, Experimentation, Statistical Methods, Statistical Analysis, Statistical Modeling, Research Design, Mathematical Modeling, Data Analysis Software

      4.7
      Rating, 4.7 out of 5 stars
      ·
      67 reviews

      Intermediate · Course · 1 - 4 Weeks

    • S

      SAS

      Machine Learning Using SAS Viya

      Skills you'll gain: Supervised Learning, Decision Tree Learning, Applied Machine Learning, Data Processing, Predictive Modeling, Feature Engineering, SAS (Software), Machine Learning, Data Analysis, Artificial Neural Networks, Performance Tuning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      101 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Imperial College London

      Global Disease Masterclass: Communicable Diseases Epidemiology, Intervention and Prevention

      Skills you'll gain: Infectious Diseases, Epidemiology, Public Health and Disease Prevention, Public Health, Microbiology, Community Health, Chronic Diseases, Preventative Care, Health Care, Health Policy, Biostatistics, Data Analysis, Policy Analysis, Trend Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      182 reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      Duke University

      ART of the MOOC: Public Art and Pedagogy

      Skills you'll gain: Peer Review, Pedagogy, Art History, Social Sciences, International Relations, Blended Learning, Social Justice, Creativity, Culture, Higher Education, Community Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      126 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Irvine

      Advanced Grammar & Punctuation Project

      Skills you'll gain: Video Production, Grammar, Peer Review, Writing, Editing, Proofreading, English Language, Creativity

      4.8
      Rating, 4.8 out of 5 stars
      ·
      133 reviews

      Advanced · Course · 1 - 3 Months

    • M

      Meta

      Working with Data in Android

      Skills you'll gain: Restful API, Android Development, Kotlin, Android Studio, Application Programming Interface (API), Mobile Development, Database Management, Databases, JSON, Web Applications, SQL, Data Access

      4.7
      Rating, 4.7 out of 5 stars
      ·
      57 reviews

      Intermediate · Course · 1 - 3 Months

    • Y

      Yonsei University

      Big Data Emerging Technologies

      Skills you'll gain: Apache Spark, Big Data, SPSS, Analytics, Real Time Data, Apache Hadoop, Data Processing, Business Analytics, Statistical Analysis, Data Analysis Software, Business Strategy, Market Share, Scalability, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      299 reviews

      Beginner · Course · 1 - 3 Months

    • E

      ESSEC Business School

      Case studies in business analytics with ACCENTURE

      Skills you'll gain: Digital Transformation, Advanced Analytics, Business Analytics, Analytics, Business Analysis, Data Analysis, Value Propositions, Business Consulting, Business Transformation, Data-Driven Decision-Making, Big Data

      3.7
      Rating, 3.7 out of 5 stars
      ·
      205 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Renewable Energy Futures

      Skills you'll gain: Energy and Utilities, Electrical Power, Electrical Systems, Electric Power Systems, Market Dynamics, Emerging Technologies, Market Trend, Trend Analysis, Market Opportunities, Environmental Issue, Forecasting, Mathematical Modeling, Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      232 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      D

      Duke University

      Programming for Python Data Science: Principles to Practice

      Skills you'll gain: Matplotlib, Pandas (Python Package), NumPy, Computational Thinking, Predictive Modeling, Data Cleansing, Data Structures, Data Visualization Software, Visualization (Computer Graphics), Debugging, Data Analysis, Object Oriented Programming (OOP), Data Manipulation, Regression Analysis, Python Programming, Data Science, Algorithms, Simulations, Statistical Methods, Program Development

      3.9
      Rating, 3.9 out of 5 stars
      ·
      66 reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      MathWorks

      Data Processing and Feature Engineering with MATLAB

      Skills you'll gain: Feature Engineering, Dimensionality Reduction, Data Integration, Exploratory Data Analysis, Data Visualization, Matlab, Data Processing, Descriptive Statistics, Data Cleansing, Data Manipulation, Histogram, Data Transformation, Text Mining, Predictive Modeling, Unstructured Data, Image Analysis, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      345 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…767778…263

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

    • Supply Market Analysis: Rutgers the State University of New Jersey
    • Response Surfaces, Mixtures, and Model Building: Arizona State University
    • Machine Learning Using SAS Viya: SAS
    • Global Disease Masterclass: Communicable Diseases Epidemiology, Intervention and Prevention: Imperial College London
    • ART of the MOOC: Public Art and Pedagogy: Duke University
    • Advanced Grammar & Punctuation Project: University of California, Irvine
    • Working with Data in Android: Meta
    • Big Data Emerging Technologies: Yonsei University
    • Case studies in business analytics with ACCENTURE: ESSEC Business School
    • Renewable Energy Futures: University of Colorado Boulder

    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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