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    Results for "advanced statistics"

    • Status: New
      New
      U

      University of Colorado Boulder

      Statistics and Data Analysis with R

      Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Regression Analysis, Statistical Programming, Probability Distribution, Statistical Analysis, R Programming, Data Import/Export, Statistical Modeling, Statistical Methods, Plot (Graphics), Statistics, Data Manipulation, Analysis, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Instructor Network

      Advanced Data Analysis and Collaboration in Qlik Sense

      Skills you'll gain: Data Storytelling, Data Visualization Software, Dashboard, Data Analysis, Advanced Analytics, Interactive Data Visualization, Data Visualization, Analytics, Data Manipulation, Collaborative Software, Data Presentation, Data Sharing

      5
      Rating, 5 out of 5 stars
      ·
      10 reviews

      Advanced · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Pattern Discovery in Data Mining

      Skills you'll gain: Data Mining, Big Data, Anomaly Detection, Text Mining, Unstructured Data, Spatial Analysis, Advanced Analytics, Image Analysis, Algorithms, Information Privacy

      4.3
      Rating, 4.3 out of 5 stars
      ·
      325 reviews

      Mixed · Course · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Bayesian Network, Bayesian Statistics, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      488 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of California, Davis

      Quantitative Research

      Skills you'll gain: Surveys, Survey Creation, Quantitative Research, Statistical Analysis, Marketing Analytics, Market Research, Statistical Methods, Data Analysis, Marketing, Target Market, Sample Size Determination, Quality Control

      4.4
      Rating, 4.4 out of 5 stars
      ·
      335 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Machine Learning With Big Data

      Skills you'll gain: Exploratory Data Analysis, Apache Spark, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Data Transformation, Predictive Modeling, Data Cleansing, Supervised Learning, Decision Tree Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.5K reviews

      Mixed · Course · 1 - 3 Months

    • T

      The Hong Kong University of Science and Technology

      FinTech Foundations and Overview

      Skills you'll gain: FinTech, Financial Services, Banking Services, Banking, Mobile Banking, Analytics, Emerging Technologies, Finance, Payment Systems, Blockchain, Consumer Lending, Business Strategies, Entrepreneurship, Big Data, Digital Assets, Innovation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      528 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IE Business School

      Globalización, Crecimiento Económico y Estabilidad

      Skills you'll gain: Financial Policy, Economics, Policy, and Social Studies, Economics, Public Policies, International Finance, Policy Analysis, International Relations, Economic Development, Tax, Socioeconomics, Trend Analysis, Global Marketing, Business Economics, Political Sciences, Analysis, Fiscal Management, Supply And Demand, Business Risk Management, World History, Policty Analysis, Research, and Development

      4.8
      Rating, 4.8 out of 5 stars
      ·
      693 reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      SAS

      Doing More with SAS Programming

      Skills you'll gain: SAS (Software), Data Manipulation, Consolidation, Data Transformation, Data Processing, Data Analysis, Data Presentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      939 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      V

      Vanderbilt University

      Case Studies in Personalized Medicine

      Skills you'll gain: Precision Medicine, Medical Science and Research, Health Informatics, Biostatistics, Electronic Medical Record, Healthcare Ethics, General Medicine, Clinical Research, Probability & Statistics, Statistical Analysis, Molecular Biology, Pharmacology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      496 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Minnesota

      Introduction to Recommender Systems: Non-Personalized and Content-Based

      Skills you'll gain: Taxonomy, AI Personalization, Spreadsheet Software, Machine Learning, Predictive Analytics, Statistical Methods, Persona Development, Descriptive Statistics, Data Collection, Algorithms, Java Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      647 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      C Programming for Everybody

      Skills you'll gain: C (Programming Language), C++ (Programming Language), Object Oriented Programming (OOP), Data Structures, Programming Principles, Algorithms, Computer Programming, Software Design, Application Security, Other Programming Languages, Python Programming, System Programming, Java, Performance Tuning, Numerical Analysis, Unix, Computer Science, Debugging

      4.5
      Rating, 4.5 out of 5 stars
      ·
      157 reviews

      Intermediate · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…424344…263

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

    • Statistics and Data Analysis with R: University of Colorado Boulder
    • Advanced Data Analysis and Collaboration in Qlik Sense : Coursera Instructor Network
    • Pattern Discovery in Data Mining: University of Illinois Urbana-Champaign
    • Probabilistic Graphical Models 2: Inference: Stanford University
    • Quantitative Research: University of California, Davis
    • Machine Learning With Big Data: University of California San Diego
    • FinTech Foundations and Overview: The Hong Kong University of Science and Technology
    • Globalización, Crecimiento Económico y Estabilidad: IE Business School
    • Doing More with SAS Programming: SAS
    • Case Studies in Personalized Medicine: Vanderbilt 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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