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    Results for "advanced statistics"

    • I

      IBM

      Data Analysis with R

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Data Transformation, R Programming, Data Manipulation, Data Visualization, Box Plots, Predictive Analytics, Statistical Analysis, Regression Analysis, Statistical Modeling, Correlation Analysis, Data Cleansing, Tidyverse (R Package), Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      332 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Icahn School of Medicine at Mount Sinai

      Network Analysis in Systems Biology

      Skills you'll gain: Bioinformatics, Unsupervised Learning, Network Analysis, Data Analysis, Molecular Biology, Statistical Analysis, Machine Learning Algorithms, Biology, Data Processing, Data Integration, R Programming, Unix Commands

      4.5
      Rating, 4.5 out of 5 stars
      ·
      200 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      M

      Macquarie University

      Excel Skills for Statistics and Data Analysis: Essentials

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Statistical Inference, Descriptive Statistics, Data Analysis, Statistical Methods, Statistical Analysis, Probability & Statistics, Spreadsheet Software, Box Plots, Probability Distribution, Statistical Visualization, Histogram

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      V

      Vanderbilt University

      ChatGPT + Excel: Master Data, Make Decisions, Tell Stories

      Skills you'll gain: Data Storytelling, Data Presentation, Data Synthesis, Microsoft Excel, Infographics, Data Analysis, Data Cleansing, Data Import/Export, ChatGPT, Statistical Reporting, Data Integration, Data Transformation, Data Validation, Exploratory Data Analysis, Prompt Engineering, Data Quality, Generative AI

      4.8
      Rating, 4.8 out of 5 stars
      ·
      54 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Global Disease Masterclass: Global Disease Distribution

      Skills you'll gain: Epidemiology, Health Disparities, Public Health, Infectious Diseases, Health Systems, Health Policy, Socioeconomics, Health Assessment, Chronic Diseases, Statistical Analysis, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      121 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Corporate Finance Institute

      Data Skills for Excel Professionals

      Skills you'll gain: Dashboard, Microsoft Excel, Pivot Tables And Charts, Star Schema, Spreadsheet Software, Data Transformation, Data Analysis Expressions (DAX), Data Storytelling, Data Analysis, Excel Formulas, Exploratory Data Analysis, Extract, Transform, Load, Data Visualization Software, Data Presentation, Data Modeling, Business Intelligence, Competitive Analysis, Data Manipulation, Data Cleansing, Data Integration

      4.8
      Rating, 4.8 out of 5 stars
      ·
      99 reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      Illinois Tech

      Digital Marketing

      Skills you'll gain: Pay Per Click Advertising, Digital Marketing, Web Analytics, Email Marketing, Paid media, Digital Advertising, Google Ads, Social Media Campaigns, Marketing Strategies, Online Advertising, Social Media Marketing, Google Analytics, Web Analytics and SEO, Web Design and Development, Marketing, Marketing Analytics, Search Engine Optimization, Social Media, Campaign Management, Search Engine Marketing

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      35 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Virginia

      Business Strategy in Practice (Project-centered Course)

      Skills you'll gain: Peer Review, Organizational Strategy, Business Research, Project Management, Business Strategy, Competitive Analysis, Business Analysis, Strategic Decision-Making, Business Communication, Analysis, Report Writing, Business Writing, Trend Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      187 reviews

      Mixed · Course · 1 - 3 Months

    • E

      EDUCBA

      Introduction to CATIA V5

      Skills you'll gain: Technical Drawing, Engineering Drawings, Computer Aided Three-Dimensional Interactive Application (CATIA), Assembly Drawing, 3D Modeling, Mechanical Design, Computer-Aided Design, Visualization (Computer Graphics), File Management, Interoperability, User Interface (UI)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      125 reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Simple Regression Analysis in Public Health

      Skills you'll gain: Biostatistics, Regression Analysis, Statistical Methods, Statistical Analysis, Epidemiology, Quantitative Research, Public Health, Data Analysis, Probability & Statistics, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      382 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Think Again III: How to Reason Inductively

      Skills you'll gain: Deductive Reasoning, Logical Reasoning, Probability, Sampling (Statistics), Statistics, Correlation Analysis, Scientific Methods

      4.6
      Rating, 4.6 out of 5 stars
      ·
      397 reviews

      Beginner · Course · 1 - 3 Months

    • N

      Northwestern University

      Modern Robotics, Course 4: Robot Motion Planning and Control

      Skills you'll gain: Control Systems, Artificial Intelligence, Automation, Graph Theory, Algorithms, Virtual Environment, Simulation and Simulation Software, Mathematical Modeling, Data Structures, Linear Algebra

      4.9
      Rating, 4.9 out of 5 stars
      ·
      113 reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…626364…263

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

    • Data Analysis with R: IBM
    • Network Analysis in Systems Biology: Icahn School of Medicine at Mount Sinai
    • Excel Skills for Statistics and Data Analysis: Essentials: Macquarie University
    • ChatGPT + Excel: Master Data, Make Decisions, Tell Stories: Vanderbilt University
    • Global Disease Masterclass: Global Disease Distribution: Imperial College London
    • Data Skills for Excel Professionals: Corporate Finance Institute
    • Digital Marketing: Illinois Tech
    • Business Strategy in Practice (Project-centered Course): University of Virginia
    • Introduction to CATIA V5: EDUCBA
    • Simple Regression Analysis in Public Health : Johns Hopkins University

    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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