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    Results for "advanced statistics"

    • E

      Emory University

      Foundations of Marketing Analytics

      Skills you'll gain: Pivot Tables And Charts, Customer Analysis, Probability Distribution, Customer Demand Planning, Marketing Analytics, Forecasting, Descriptive Statistics, Microsoft Excel, Social Media Marketing, Exploratory Data Analysis, Probability, Statistical Analysis, Target Market, Marketing Effectiveness, Social Media, Revenue Forecasting, Time Series Analysis and Forecasting, Predictive Modeling, Statistics, Marketing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      516 reviews

      Intermediate · Specialization · 3 - 6 Months

    • A

      Arizona State University

      Design of Experiments

      Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Design Strategies, Probability & Statistics, Data Analysis, Mathematical Modeling, Data Transformation, Descriptive Statistics, Probability Distribution, Statistical Hypothesis Testing, Variance Analysis, Quality Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      360 reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Mathematical Biostatistics Boot Camp 1

      Skills you'll gain: Sampling (Statistics), Bayesian Statistics, Probability & Statistics, Statistical Inference, Statistical Methods, Probability, Probability Distribution, Statistical Analysis, Biostatistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      514 reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      Applied Data Science with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Shiny (R Package), Data Wrangling, Dashboard, Exploratory Data Analysis, Relational Databases, Data Analysis, Ggplot2, Database Design, Data Presentation, SQL, Plot (Graphics), Leaflet (Software), Data Transformation, Database Management, Data Manipulation, Web Scraping, R Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Differential Equations Part I Basic Theory

      Skills you'll gain: Differential Equations, Mathematical Modeling, Applied Mathematics, Calculus, Linear Algebra, Vibrations, Mechanics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • T

      The Hong Kong University of Science and Technology

      Matrix Algebra for Engineers

      Skills you'll gain: Linear Algebra, Engineering Calculations, Algebra, Engineering Analysis, General Mathematics, Advanced Mathematics, Applied Mathematics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Applied Text Mining in Python

      Skills you'll gain: Text Mining, Natural Language Processing, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data Processing, Feature Engineering, Data Manipulation, Data Cleansing, Unsupervised Learning, Supervised Learning

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Meditation: A way to achieve your goals in your life

      Skills you'll gain: Self-Awareness, Personal Development, Growth Mindedness, Mindfulness, Positivity, Goal Setting, Resilience, Emotional Intelligence, Stress Management, Relationship Building, Cognitive flexibility

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Irvine

      Getting Started with Go

      Skills you'll gain: Go (Programming Language), JSON, Programming Principles, Other Programming Languages, Development Environment, Data Structures, Remote Access Systems, Software Installation, File Management, Program Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Business Analytics

      Skills you'll gain: Data Storytelling, Extract, Transform, Load, Marketing Analytics, Data Presentation, Data Visualization, Regression Analysis, Alteryx, Data Collection, Interactive Data Visualization, Data Quality, Statistical Visualization, Tidyverse (R Package), R Programming, Data Visualization Software, Data Processing, Network Analysis, Business Analytics, Internal Controls, Exploratory Data Analysis, Robotic Process Automation

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • B

      Berklee

      Developing Your Musicianship

      Skills you'll gain: Musical Composition, Music Theory, Peer Review, Music, Music Performance, Instrumental Music, Creativity

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.6K reviews

      Beginner · Specialization · 3 - 6 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

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…262728…263

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

    • Foundations of Marketing Analytics: Emory University
    • Design of Experiments: Arizona State University
    • Mathematical Biostatistics Boot Camp 1: Johns Hopkins University
    • Applied Data Science with R: IBM
    • Differential Equations Part I Basic Theory: Korea Advanced Institute of Science and Technology(KAIST)
    • Matrix Algebra for Engineers: The Hong Kong University of Science and Technology
    • Applied Text Mining in Python: University of Michigan
    • Meditation: A way to achieve your goals in your life: Korea Advanced Institute of Science and Technology(KAIST)
    • Getting Started with Go: University of California, Irvine
    • Business Analytics: University of Illinois Urbana-Champaign

    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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