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    Results for "advanced statistics"

    • L

      LearnQuest

      Fundamentals of Data Analysis

      Skills you'll gain: Data Analysis, Analytics, Statistical Analysis, Data Mining, Spreadsheet Software, Exploratory Data Analysis, Descriptive Analytics, Quantitative Research, Data Cleansing, Data Processing, Data Collection, Advanced Analytics, Statistics, Predictive Analytics, Data Presentation, Regression Analysis, Data Visualization, SQL

      3.6
      Rating, 3.6 out of 5 stars
      ·
      31 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Accounting for Mergers and Acquisitions: Advanced Topics

      Skills you'll gain: Mergers & Acquisitions, Financial Statement Analysis, Corporate Accounting, Specialized Accounting, Private Equity, Financial Analysis, Corporate Tax, Financial Modeling, Financial Accounting, Accounting, Corporate Finance, Tax, Equities

      4.7
      Rating, 4.7 out of 5 stars
      ·
      21 reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Genentech

      Data Sciences in Pharma - Patient Centered Outcomes Research

      Skills you'll gain: Clinical Trials, Clinical Research, Pharmaceuticals, Patient Evaluation, Quantitative Research, Patient Safety, Medical Science and Research, Data Analysis, Statistical Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      18 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Packt

      Foundations and Core Concepts of PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Artificial Neural Networks, Python Programming, Regression Analysis, Performance Tuning, System Configuration, Development Environment, Software Installation

      4.3
      Rating, 4.3 out of 5 stars
      ·
      23 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      N

      National Taiwan University

      頑想學概率:機率一 (Probability (1))

      Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Data Literacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      360 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Toronto

      Build Your Own iOS App

      Skills you'll gain: Apple iOS, Swift Programming, Mobile Development, Animations, Application Development, Computer Vision, Image Analysis, User Interface (UI) Design

      3.2
      Rating, 3.2 out of 5 stars
      ·
      70 reviews

      Mixed · Course · 1 - 3 Months

    • U

      Universidad Nacional Autónoma de México

      Python: de cero a analista de datos

      Skills you'll gain: Exploratory Data Analysis, Matplotlib, Pandas (Python Package), Extract, Transform, Load, Data Analysis, NumPy, Package and Software Management, Time Series Analysis and Forecasting, Data Visualization Software, Data Science, Python Programming, Jupyter, Graphing, Data Import/Export, Data Manipulation, Scripting, Software Installation, Computational Thinking, Development Environment, Mac OS

      4.2
      Rating, 4.2 out of 5 stars
      ·
      39 reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Data Transformation in the Cloud

      Skills you'll gain: Data Pipelines, Data Cleansing, Data Governance, Data Transformation, Cloud Security, Data Visualization, Extract, Transform, Load, Data Integration, Data Processing, Data Management, Data Migration, Data Collection, Cloud Computing, Cloud Storage, Data Analysis, SQL

      4.5
      Rating, 4.5 out of 5 stars
      ·
      22 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Packt

      The STATA OMNIBUS: Regression and Modelling with STATA

      Skills you'll gain: Stata, Regression Analysis, Statistical Modeling, Statistical Analysis, Advanced Analytics, Correlation Analysis, Statistical Visualization, Data Manipulation, Sampling (Statistics), Statistical Hypothesis Testing, Descriptive Statistics

      Beginner · Course · 3 - 6 Months

    • N

      Novartis

      Preclinical Safety

      Skills you'll gain: Patient Safety, Pharmacology, Clinical Research, Clinical Trials, Pharmaceuticals, Laboratory Testing, Risk Analysis, Regulatory Compliance

      5
      Rating, 5 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Politecnico di Milano

      New paradigms in wastewater management

      Skills you'll gain: Water Resources, Environmental Engineering, Civil Engineering, Energy and Utilities, Environment and Resource Management, Pollution Prevention, Environmental Science, Chemical Engineering, Environmental Regulations, Microbiology

      4.7
      Rating, 4.7 out of 5 stars
      ·
      50 reviews

      Beginner · Course · 1 - 4 Weeks

    • L

      LearnKartS

      Complete Git

      Skills you'll gain: Git (Version Control System), Bitbucket, GitHub, GitLab, Version Control, Software Configuration Management, Collaborative Software, Software Versioning, Continuous Integration, Integrated Development Environments, IntelliJ IDEA, Eclipse (Software), Software Development, User Accounts, Release Management, File Management, Code Review, Remote Access Systems, Development Environment, Command-Line Interface

      4.3
      Rating, 4.3 out of 5 stars
      ·
      18 reviews

      Beginner · Specialization · 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…969798…264

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

    • Fundamentals of Data Analysis: LearnQuest
    • Accounting for Mergers and Acquisitions: Advanced Topics: University of Illinois Urbana-Champaign
    • Data Sciences in Pharma - Patient Centered Outcomes Research: Genentech
    • Foundations and Core Concepts of PyTorch: Packt
    • 頑想學概率:機率一 (Probability (1)): National Taiwan University
    • Build Your Own iOS App: University of Toronto
    • Python: de cero a analista de datos: Universidad Nacional Autónoma de México
    • Data Transformation in the Cloud: Google Cloud
    • The STATA OMNIBUS: Regression and Modelling with STATA: Packt
    • Preclinical Safety: Novartis

    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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