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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Black Belt

      Skills you'll gain: Statistical Process Controls, Lean Six Sigma, Six Sigma Methodology, Lean Methodologies, Process Improvement, Team Management, Process Capability, Lean Manufacturing, Data Collection, Quality Improvement, Knowledge Transfer, Team Building, Statistical Hypothesis Testing, Meeting Facilitation, Continuous Improvement Process, Performance Measurement, Conflict Management, Sampling (Statistics), Process Development, Team Leadership

      4.6
      Rating, 4.6 out of 5 stars
      ·
      716 reviews

      Intermediate · Specialization · 3 - 6 Months

    • 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
      ·
      755 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      Stanford University

      Social and Economic Networks: Models and Analysis

      Skills you'll gain: Network Analysis, Network Model, Social Sciences, Sociology, Economics, Policy, and Social Studies, Game Theory, Behavioral Economics, Graph Theory, Mathematical Modeling, Markov Model, Probability & Statistics, Probability Distribution, Bayesian Statistics, Simulations

      4.8
      Rating, 4.8 out of 5 stars
      ·
      754 reviews

      Advanced · Course · 1 - 3 Months

    • 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

    • Status: New
      New
      Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Python Development

      Skills you'll gain: Web Scraping, Data Structures, Git (Version Control System), Generative AI, Version Control, Matplotlib, Plotly, DevOps, Agile Methodology, Web Development, Data Ethics, Flask (Web Framework), Scripting, GitHub, Debugging, Data Cleansing, Data Manipulation, Restful API, Docker (Software), Test Driven Development (TDD)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      218 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      Universidad Nacional Autónoma de México

      Estadística y probabilidad

      Skills you'll gain: Descriptive Statistics, Data Analysis, Correlation Analysis, Statistical Analysis, Data Presentation, Statistical Visualization, Probability, Histogram, Data-Driven Decision-Making, Regression Analysis, Probability Distribution, Box Plots, Graphing, Scatter Plots

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Tools for Analyze

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Process Analysis, Probability Distribution, Process Capability, Statistical Process Controls, Lean Methodologies, Probability & Statistics, Process Improvement, Quality Improvement, Process Mapping, Statistical Analysis, Systems Of Measurement, Risk Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Advanced Writing

      Skills you'll gain: Writing, Grammar, Editing, Proofreading, Peer Review

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Computer Networks and Network Security

      Skills you'll gain: Networking Hardware, TCP/IP, Network Security, Network Protocols, Endpoint Detection and Response, Network Routing, Cybersecurity, Local Area Networks, Dynamic Host Configuration Protocol (DHCP), Firewall, General Networking, Information Systems Security, Intrusion Detection and Prevention, Endpoint Security, Network Infrastructure, Network Planning And Design, Wireless Networks, Security Information and Event Management (SIEM), Network Analysis, Data Loss Prevention

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.4K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Business Analytics

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

      Build toward a degree

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Probabilistic Graphical Models 1: Representation

      Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Applied Machine Learning, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.4K reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing with Attention Models

      Skills you'll gain: Natural Language Processing, PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Tensorflow, Machine Learning Methods, Artificial Intelligence, Artificial Neural Networks, Text Mining, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…242526…268

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

    • Six Sigma Black Belt: Kennesaw State University
    • Getting Started With Music Theory: Michigan State University
    • Social and Economic Networks: Models and Analysis: Stanford University
    • Meditation: A way to achieve your goals in your life: Korea Advanced Institute of Science and Technology(KAIST)
    • Microsoft Python Development: Microsoft
    • Estadística y probabilidad: Universidad Nacional Autónoma de México
    • Six Sigma Tools for Analyze: Kennesaw State University
    • Advanced Writing: University of California, Irvine
    • Computer Networks and Network Security: IBM
    • 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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