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    Results for "advanced statistics"

    • G

      Georgia Institute of Technology

      Fundamentals of Engineering Exam Review

      Skills you'll gain: Structural Analysis, Probability & Statistics, Structural Engineering, Hydraulics, Statistical Methods, Statistics, Engineering Analysis, Mechanical Engineering, Probability, Engineering, Probability Distribution, Mechanics, Engineering Calculations, Civil Engineering, Applied Mathematics, Algebra, Advanced Mathematics, Calculus, Differential Equations, Geometry

      4.6
      Rating, 4.6 out of 5 stars
      ·
      611 reviews

      Mixed · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Spreadsheets for Beginners using Google Sheets

      Skills you'll gain: Spreadsheet Software, Data Entry, Data Validation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.2K reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      N

      National Taiwan University

      3D CAD Fundamental

      Skills you'll gain: 3D Modeling, SketchUp (3D Modeling Software), Software Installation, Visualization (Computer Graphics), Computer Graphics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      647 reviews

      Beginner · Course · 1 - 3 Months

    • 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

    • R

      Rutgers the State University of New Jersey

      Supply Chain Planning

      Skills you'll gain: Demand Planning, Forecasting, Customer Demand Planning, Supply Chain Planning, Sales Management, Time Series Analysis and Forecasting, Supply Chain Management, Production Planning, Trend Analysis, Decision Making

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Digital Marketing Analytics in Theory

      Skills you'll gain: Marketing Analytics, Web Analytics, Marketing Effectiveness, Digital Marketing, Marketing Strategies, Analytics, Marketing, Consumer Behaviour, Data Analysis, Data Visualization Software, Data Collection, Regulatory Compliance

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Algebra: Elementary to Advanced - Equations & Inequalities

      Skills you'll gain: Algebra, Arithmetic, Mathematical Modeling, Applied Mathematics, Graphing, Probability & Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      583 reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Regression Models

      Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Data Science, Predictive Modeling, Probability & Statistics, Statistical Inference

      4.4
      Rating, 4.4 out of 5 stars
      ·
      3.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • M

      Michigan State University

      Getting Started With Music Theory

      Skills you'll gain: Music Theory, Music, Musical Composition, Classical Music

      4.5
      Rating, 4.5 out of 5 stars
      ·
      754 reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Meta

      Marketing Analytics Foundation

      Skills you'll gain: Data Collection, Marketing, Marketing Analytics, Google Analytics, Digital Marketing, Application Programming Interface (API), Personally Identifiable Information, Web Analytics, Information Privacy, Data Integration, Analytics, Facebook, Data-Driven Decision-Making, Advertising

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • N

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Financial Services

      3.7
      Rating, 3.7 out of 5 stars
      ·
      814 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Modeling Risk and Realities

      Skills you'll gain: Risk Modeling, Probability Distribution, Mathematical Modeling, Statistical Modeling, Risk Management, Data Visualization, Predictive Modeling, Data Modeling, Probability & Statistics, Risk Analysis, Simulation and Simulation Software, Forecasting, Data-Driven Decision-Making, Business Analysis, Process Optimization, Microsoft Excel

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Mixed · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…272829…263

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

    • Fundamentals of Engineering Exam Review: Georgia Institute of Technology
    • Spreadsheets for Beginners using Google Sheets: Coursera Project Network
    • 3D CAD Fundamental: National Taiwan University
    • Statistics and Data Analysis with R: University of Colorado Boulder
    • Supply Chain Planning: Rutgers the State University of New Jersey
    • Digital Marketing Analytics in Theory: University of Illinois Urbana-Champaign
    • Algebra: Elementary to Advanced - Equations & Inequalities: Johns Hopkins University
    • Regression Models: Johns Hopkins University
    • Getting Started With Music Theory: Michigan State University
    • Marketing Analytics Foundation: Meta

    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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