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    Results for "advanced statistics"

    • P

      Packt

      The Complete Quantum Computing Course for Beginners

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Data Structures, Data Manipulation, Computer Programming, Applied Mathematics, Algorithms, Mathematics and Mathematical Modeling, Data Processing, Scripting, Linear Algebra, Probability, Mathematical Modeling, IBM Cloud, Computer Science, Algebra, Software Installation, Probability & Statistics, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      29 reviews

      Beginner · Specialization · 3 - 6 Months

    • K

      Kennesaw State University

      DFSS for the 6 σ Black Belt

      Skills you'll gain: Process Improvement, Six Sigma Methodology, Lean Six Sigma, Knowledge Transfer, Continuous Improvement Process, Lean Manufacturing, Statistical Process Controls, Quality Management, Product Design, Statistical Methods, Design and Product, Probability & Statistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      33 reviews

      Mixed · Course · 1 - 3 Months

    • P

      Pontificia Universidad Católica de Chile

      Python para Ciencia de Datos

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Data Analysis, Data Visualization Software, Predictive Analytics, Business Analytics, Database Management, Data Science, Relational Databases, Data Processing, Trend Analysis, Forecasting, Data Manipulation, Python Programming

      Build toward a degree

      3.8
      Rating, 3.8 out of 5 stars
      ·
      66 reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Alberta Machine Intelligence Institute

      Machine Learning Algorithms: Supervised Learning Tip to Tail

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Jupyter, Machine Learning, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Feature Engineering, Data Processing, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      413 reviews

      Mixed · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Foundations of SHRM Certification

      Skills you'll gain: Human Resource Strategy, Human Resources Management and Planning, Human Resources, Recruitment Strategies, Talent Acquisition, Organizational Development, Organizational Effectiveness, Talent Sourcing, HR Tech, Ethical Standards And Conduct, Leadership, Organizational Structure, Cultural Diversity, Conflict Management, Employee Onboarding, Interviewing Skills

      3.7
      Rating, 3.7 out of 5 stars
      ·
      43 reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Tidyverse Skills for Data Science in R

      Skills you'll gain: Tidyverse (R Package), Ggplot2, Data Wrangling, Statistical Modeling, Exploratory Data Analysis, Plot (Graphics), R Programming, Data Import/Export, Predictive Modeling, Statistical Visualization, Sampling (Statistics), Data Visualization Software, Statistical Hypothesis Testing, Data Analysis, Data Manipulation, Data Modeling, Web Scraping, Data Integration, Data Cleansing, Data Transformation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      104 reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      Illinois Tech

      Bayesian Computational Statistics

      Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Inference, Regression Analysis, Statistical Methods, Statistical Analysis, Statistical Modeling, Statistical Programming, Statistical Software, R Programming, Markov Model, Probability, Simulations, Probability Distribution

      Build toward a degree

      Intermediate · Course · 1 - 3 Months

    • S

      SkillUp EdTech

      Working as a Scrum Master

      Skills you'll gain: Sprint Retrospectives, Sprint Planning, Agile Project Management, Team Building, Agile Methodology, Team Management, Meeting Facilitation, Organizational Change, Team Leadership, User Story, Employee Coaching, Stakeholder Management, Change Management, Conflict Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      70 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Alberta

      Science Literacy

      Skills you'll gain: Scientific Methods, General Science and Research, Research Methodologies, Research, Research Design, Peer Review, Experimentation, Statistical Methods, Media and Communications, Correlation Analysis, Probability & Statistics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      261 reviews

      Beginner · Course · 1 - 3 Months

    • P

      Packt

      Data Analysis with Pandas and Python

      Skills you'll gain: Pandas (Python Package), Data Import/Export, Matplotlib, Pivot Tables And Charts, Jupyter, Data Visualization Software, Microsoft Excel, Data Analysis, Text Mining, Data Manipulation, Data Cleansing, NumPy, Data Analysis Software, Data Integration, Data Wrangling, Time Series Analysis and Forecasting, Data Transformation, Python Programming, Data Structures, Integrated Development Environments

      4.7
      Rating, 4.7 out of 5 stars
      ·
      18 reviews

      Intermediate · Specialization · 3 - 6 Months

    • E

      EDHEC Business School

      Economics and Policies of Climate Change

      Skills you'll gain: Environmental Policy, Economics, Environmental Issue, Behavioral Economics, Cost Benefit Analysis, Policy Analysis, Environmental Regulations, Market Analysis, Tax, Financial Trading, Mathematical Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      65 reviews

      Beginner · Course · 1 - 3 Months

    • L

      L&T EduTech

      Mastering Geospatial Analysis with QGIS

      Skills you'll gain: Spatial Analysis, GIS Software, Spatial Data Analysis, Geospatial Mapping, Geographic Information Systems, Building Information Modeling, Data Manipulation, Global Positioning Systems, Network Analysis, Image Analysis, Data Import/Export, Unsupervised Learning, Software Installation, Supervised Learning, UI Components

      4
      Rating, 4 out of 5 stars
      ·
      20 reviews

      Advanced · 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…828384…263

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

    • The Complete Quantum Computing Course for Beginners: Packt
    • DFSS for the 6 σ Black Belt: Kennesaw State University
    • Python para Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Machine Learning Algorithms: Supervised Learning Tip to Tail: Alberta Machine Intelligence Institute
    • Foundations of SHRM Certification: Board Infinity
    • Tidyverse Skills for Data Science in R: Johns Hopkins University
    • Bayesian Computational Statistics: Illinois Tech
    • Working as a Scrum Master: SkillUp EdTech
    • Science Literacy : University of Alberta
    • Data Analysis with Pandas and Python: Packt

    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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