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    Results for "advanced statistics"

    • E

      EDUCBA

      SIEM Splunk Hands-On Guide

      Skills you'll gain: Splunk, Security Information and Event Management (SIEM), Data Modeling, Role-Based Access Control (RBAC), System Monitoring, Dashboard, Incident Response, Threat Detection, User Accounts, Data Transformation, Cybersecurity, Machine Learning, Performance Tuning, Data Visualization, Event Monitoring, Data Manipulation, Data Analysis, Identity and Access Management, Statistical Analysis, Query Languages

      4.8
      Rating, 4.8 out of 5 stars
      ·
      263 reviews

      Beginner · Specialization · 1 - 3 Months

    • V

      Vanderbilt University

      Microsoft 365 Copilot: Personal Productivity for All

      Skills you'll gain: Microsoft Copilot, Microsoft 365, Target Audience, Microsoft Teams, Productivity Software, Complex Problem Solving, Strategic Communication, Brainstorming, Artificial Intelligence, Communication, Project Management Software, AI Personalization, Generative AI, Project Risk Management, Decision Making

      4.7
      Rating, 4.7 out of 5 stars
      ·
      172 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Introduction to Business Analysis Using Spreadsheets: Basics

      Skills you'll gain: Google Sheets, Spreadsheet Software, Data Presentation, Statistical Visualization, Data Analysis, Data Visualization Software, Business Analytics, Productivity Software, Business Analysis, Data Manipulation, Descriptive Statistics, Analysis, Excel Formulas, Data Cleansing, Mathematical Software

      4.3
      Rating, 4.3 out of 5 stars
      ·
      999 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Colorado Boulder

      Excel/VBA for Creative Problem Solving, Part 2

      Skills you'll gain: Excel Macros, Visual Basic (Programming Language), Data Import/Export, Programming Principles, Spreadsheet Software, UI Components, Automation, Data Structures, Debugging, Data Validation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Vital Skills for Data Science

      Skills you'll gain: Data Ethics, Data Visualization Software, Interactive Data Visualization, Visualization (Computer Graphics), Data Security, Data Presentation, User Centered Design, Statistical Visualization, Cybersecurity, Technical Communication, Usability, Healthcare Ethics, Cyber Attacks, Statistical Reporting, Human Computer Interaction, Authentications, Data Storytelling, Data Science, Ethical Standards And Conduct, User Research

      Build toward a degree

      4.3
      Rating, 4.3 out of 5 stars
      ·
      109 reviews

      Intermediate · Specialization · 3 - 6 Months

    • F

      Fractal Analytics

      Quantum Computing For Everyone - An Introduction

      Skills you'll gain: Computer Science, IBM Cloud, Algorithms, Data Ethics, Computational Thinking, Linear Algebra, Emerging Technologies, Cryptography, Physics, Applied Mathematics

      4
      Rating, 4 out of 5 stars
      ·
      63 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Advanced Data Visualization with R

      Skills you'll gain: Rmarkdown, Tidyverse (R Package), Ggplot2, Spatial Data Analysis, Data Visualization Software, Plot (Graphics), Statistical Visualization, Data Manipulation, Scatter Plots, Plotly, Interactive Data Visualization, R Programming, Data Mapping, Animations

      4.9
      Rating, 4.9 out of 5 stars
      ·
      79 reviews

      Mixed · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      AI and Climate Change

      Skills you'll gain: Image Analysis, Environmental Monitoring, Artificial Intelligence, Deep Learning, Data Processing, Forecasting, Machine Learning, Computer Vision, Environmental Science, Exploratory Data Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Validity and Bias in Epidemiology

      Skills you'll gain: Research Design, Epidemiology, Data Collection, Biostatistics, Research Methodologies, Research, Public Health, Correlation Analysis, Statistical Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      243 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Recommendation Systems on Google Cloud

      Skills you'll gain: Reinforcement Learning, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Deep Learning, Applied Machine Learning, Unsupervised Learning, Artificial Neural Networks, Feature Engineering, Predictive Modeling, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      478 reviews

      Advanced · Course · 1 - 3 Months

    • L

      L&T EduTech

      Building Smarter: BIM in Practice

      Skills you'll gain: Autodesk Revit, Design Reviews, Building Information Modeling, Visualization (Computer Graphics), Construction Management, Augmented and Virtual Reality (AR/VR), Construction, Construction Engineering, Commercial Construction, Engineering Analysis, Construction Estimating, Architectural Engineering, Emerging Technologies, Civil and Architectural Engineering, Structural Engineering, Engineering Documentation, Architectural Design, Collaborative Software, 3D Modeling, Facility Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      67 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Monetary Policy in the Asia Pacific

      Skills you'll gain: Market Liquidity, Analysis, Financial Policy, Economics, International Finance, Financial Systems, Financial Market, Financial Regulation, Market Dynamics, Supply And Demand, Forecasting

      4.8
      Rating, 4.8 out of 5 stars
      ·
      328 reviews

      Intermediate · Course · 1 - 4 Weeks

    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…596061…263

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

    • SIEM Splunk Hands-On Guide: EDUCBA
    • Microsoft 365 Copilot: Personal Productivity for All: Vanderbilt University
    • Introduction to Business Analysis Using Spreadsheets: Basics: Coursera Project Network
    • Excel/VBA for Creative Problem Solving, Part 2: University of Colorado Boulder
    • Vital Skills for Data Science: University of Colorado Boulder
    • Quantum Computing For Everyone - An Introduction : Fractal Analytics
    • Advanced Data Visualization with R: Johns Hopkins University
    • AI and Climate Change: DeepLearning.AI
    • Validity and Bias in Epidemiology: Imperial College London
    • Recommendation Systems on Google Cloud: Google Cloud

    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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