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    Results for "advanced statistics"

    • U

      University of Illinois Urbana-Champaign

      Cluster Analysis in Data Mining

      Skills you'll gain: Unsupervised Learning, Data Mining, Data Validation, Applied Machine Learning, Machine Learning Algorithms, Data Analysis, Statistical Methods, Exploratory Data Analysis, Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      408 reviews

      Mixed · Course · 1 - 3 Months

    • S

      SkillUp EdTech

      Tableau Data Analyst Certification Preparation

      Skills you'll gain: Dashboard, Data Storytelling, Tableau Software, Peer Review, Data Visualization Software, Presentations, Interactive Data Visualization, Data Visualization, Data Cleansing, Business Intelligence, Real Time Data, Data Manipulation, Data Presentation, Data Analysis Expressions (DAX), Data Quality, Data Transformation, Data Sharing, Data Integration, Pivot Tables And Charts, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      60 reviews

      Advanced · Specialization · 1 - 3 Months

    • W

      Wesleyan University

      Data Analysis Tools

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Statistical Software, Correlation Analysis, SAS (Software), Data Analysis, Statistical Methods, Quantitative Research, Probability & Statistics, Analytical Skills, Regression Analysis, Data Management, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      414 reviews

      Mixed · Course · 1 - 4 Weeks

    • C

      Corporate Finance Institute

      Advanced Tableau

      Skills you'll gain: Star Schema, Data Modeling, Tableau Software, Interactive Data Visualization, Business Intelligence, Extract, Transform, Load, Dashboard, Performance Tuning, Technical Analysis, Database Design, Data Visualization Software, Data Warehousing, Market Data, Data Presentation, Investment Banking, Exploratory Data Analysis, Tree Maps, Data Integration, Market Analysis, Data Storytelling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      14 reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Toronto

      GIS, Mapping, and Spatial Analysis Capstone

      Skills you'll gain: Spatial Analysis, Geographic Information Systems, Geospatial Mapping, ArcGIS, Data Visualization, Data Compilation, Data Mapping, Data Storytelling, Metadata Management, Data Integration, Data Management

      4.9
      Rating, 4.9 out of 5 stars
      ·
      310 reviews

      Beginner · Course · 1 - 3 Months

    • K

      Kennesaw State University

      The Define Phase for the 6 σ Black Belt

      Skills you'll gain: Six Sigma Methodology, Lean Six Sigma, Analysis, Process Improvement, Project Documentation, Quality Improvement, Process Capability, Customer Analysis, Continuous Quality Improvement (CQI), Project Management, Business Process

      4.4
      Rating, 4.4 out of 5 stars
      ·
      95 reviews

      Mixed · Course · 1 - 3 Months

    • D

      Duke University

      Rust Fundamentals

      Skills you'll gain: Rust (Programming Language), Unit Testing, Test Case, Software Testing, Data Structures, Debugging, GitHub, Programming Principles, Package and Software Management, Development Environment

      4.1
      Rating, 4.1 out of 5 stars
      ·
      157 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Learn to Teach Java

      Skills you'll gain: Debugging, Object Oriented Programming (OOP), Java, Programming Principles, Java Programming, Pedagogy, Program Development, Integrated Development Environments, Software Design, Computational Thinking, Computer Programming, Cultural Responsiveness, Test Case, Pseudocode, Algorithms, Data Structures, Computer Science, Technical Communication

      4.7
      Rating, 4.7 out of 5 stars
      ·
      55 reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Scalable Machine Learning on Big Data using Apache Spark

      Skills you'll gain: Apache Spark, PySpark, Applied Machine Learning, Big Data, Machine Learning Methods, Data Storage, Data Pipelines, Machine Learning Algorithms, Distributed Computing, Data Processing, Exploratory Data Analysis, Statistical Analysis

      3.8
      Rating, 3.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Codio

      Cloud Computing Primer for Semi-tech and Business Learners

      Skills you'll gain: Infrastructure As A Service (IaaS), Service Level Agreement, Platform As A Service (PaaS), Software As A Service, Cloud Infrastructure, Cloud Services, Cloud Computing, Cloud Computing Architecture, Cloud Platforms, Public Cloud, Application Development, Application Deployment, Cloud Solutions, Cloud Applications, Private Cloud, Service Level, Business Software, DevOps, Collaborative Software, Agile Methodology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      75 reviews

      Beginner · Specialization · 1 - 3 Months

    • E

      EDUCBA

      IoT Enabled Farming

      Skills you'll gain: Internet Of Things, Big Data, Data Management, Wireless Networks, Predictive Analytics, Emerging Technologies, Data-Driven Decision-Making, Real Time Data, Automation, Environmental Science, Data Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      156 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Minnesota

      Medical Technology and Evaluation

      Skills you'll gain: Payment Systems, Healthcare Industry Knowledge, Medical Equipment and Technology, Cost Benefit Analysis, Clinical Trials, Health Technology, Clinical Data Management, Financial Regulations, Program Evaluation, Pharmaceuticals, Health Policy, Risk Analysis, Health Care Procedure and Regulation, Claims Processing, Regulatory Affairs, Health Care, Quality Assessment, Medicare, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      288 reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…646566…263

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

    • Cluster Analysis in Data Mining: University of Illinois Urbana-Champaign
    • Tableau Data Analyst Certification Preparation: SkillUp EdTech
    • Data Analysis Tools: Wesleyan University
    • Advanced Tableau: Corporate Finance Institute
    • GIS, Mapping, and Spatial Analysis Capstone: University of Toronto
    • The Define Phase for the 6 σ Black Belt: Kennesaw State University
    • Rust Fundamentals: Duke University
    • Learn to Teach Java: University of California San Diego
    • Scalable Machine Learning on Big Data using Apache Spark: IBM
    • Cloud Computing Primer for Semi-tech and Business Learners: Codio

    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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