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    Results for "advanced statistics"

    • Status: Free Trial
      Free Trial
      A

      Arizona State University

      Experimental Design Basics

      Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Hypothesis Testing, Design Strategies, Probability & Statistics, Statistical Modeling, Descriptive Statistics, Quality Control, Variance Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      295 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      L

      Ludwig-Maximilians-Universität München (LMU)

      Strategic Organization Design

      Skills you'll gain: Organizational Structure, Organizational Strategy, Organizational Effectiveness, Strategic Thinking, Corporate Strategy, Strategic Leadership, Process Design, Business Strategy, Business Management, Strategic Decision-Making, Strategic Planning, Systems Thinking, Growth Strategies, Decision Making, Innovation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      299 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Presentation, Data Storytelling, Presentations, Data Cleansing, Data Visualization, Rmarkdown, Data-Driven Decision-Making, Data Validation, Data Ethics, Analytical Skills, Dashboard, Spreadsheet Software, Ggplot2, SQL, Data Visualization Software, Data Literacy, Data Collection, Sampling (Statistics), Data Analysis, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      314 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistics and Data Analysis with Excel, Part 2

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Sampling (Statistics), Statistical Methods, Microsoft Excel, Probability & Statistics, Data Analysis, Regression Analysis, Probability Distribution

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Advanced Clinical Data Science

      Skills you'll gain: Clinical Data Management, Clinical Research, Data Quality, Health Informatics, Biostatistics, Time Series Analysis and Forecasting, Data Analysis, Data Modeling, Data Science, Analytics, Statistical Reporting, R Programming, SQL

      4.8
      Rating, 4.8 out of 5 stars
      ·
      23 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Computer Vision Fundamentals with Google Cloud

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Supervised Learning, Google Cloud Platform, Machine Learning Methods, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Small Data, Data Processing, Cloud API

      4.5
      Rating, 4.5 out of 5 stars
      ·
      544 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Logistic Regression in R for Public Health

      Skills you'll gain: Descriptive Statistics, Exploratory Data Analysis, Regression Analysis, R Programming, Statistical Modeling, Predictive Modeling, Statistical Analysis, Biostatistics, Feature Engineering, Statistical Inference, Data Analysis Software, Public Health

      4.8
      Rating, 4.8 out of 5 stars
      ·
      365 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Test and Behavior Driven Development

      Skills you'll gain: Test Driven Development (TDD), Gherkin (Scripting Language), Code Coverage, Behavior-Driven Development, Software Testing, Unit Testing, Test Automation, Test Case, Test Data, Integration Testing, Restful API, Microservices

      4.8
      Rating, 4.8 out of 5 stars
      ·
      231 reviews

      Intermediate · Course · 1 - 3 Months

    • E

      EDHEC Business School

      Building Strategic Foresight Capabilities

      Skills you'll gain: Systems Thinking, Strategic Thinking, Forecasting, Strategic Decision-Making, Stakeholder Engagement, Organizational Strategy, Complex Problem Solving, Business Transformation, Business Strategy, Trend Analysis, Innovation, Emerging Technologies

      4.9
      Rating, 4.9 out of 5 stars
      ·
      226 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      Universidad Nacional Autónoma de México

      Evolución

      Skills you'll gain: Biology, Life Sciences, Human Development, Human Learning, Environment, Anthropology, World History, Social Studies, Deductive Reasoning, Innovation, Molecular, Cellular, and Microbiology, European History, Higher Education, Taxonomy, Mathematical Modeling, Scientific Methods, Probability & Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      358 reviews

      Beginner · Specialization · 1 - 3 Months

    • T

      The University of Sydney

      eHealth: More than just an electronic record

      Skills you'll gain: Health Technology, Health Informatics, Health Care, Electronic Medical Record, Care Coordination, Healthcare Industry Knowledge, Telehealth, Health Information Management, Patient Education and Support, Interoperability, Data Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      327 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      N

      New York Institute of Finance

      Reinforcement Learning for Trading Strategies

      Skills you'll gain: Reinforcement Learning, Financial Trading, Deep Learning, Portfolio Management, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning Software, Applied Machine Learning, Markov Model, Machine Learning, Financial Market, Time Series Analysis and Forecasting

      3.5
      Rating, 3.5 out of 5 stars
      ·
      240 reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…545556…269

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

    • Experimental Design Basics: Arizona State University
    • Strategic Organization Design: Ludwig-Maximilians-Universität München (LMU)
    • Google Data Analytics: Google
    • Statistics and Data Analysis with Excel, Part 2: University of Colorado Boulder
    • Advanced Clinical Data Science: University of Colorado System
    • Computer Vision Fundamentals with Google Cloud: Google Cloud
    • Logistic Regression in R for Public Health: Imperial College London
    • Introduction to Test and Behavior Driven Development: IBM
    • Building Strategic Foresight Capabilities: EDHEC Business School
    • Evolución: Universidad Nacional Autónoma de México

    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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