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    Results for "advanced statistics"

    • Status: New
      New
      M

      Macquarie University

      Excel Skills for Statistics and Data Analysis: Intermediate

      Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Statistical Inference, Microsoft Excel, Correlation Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Regression Analysis, Data Analysis, Sampling (Statistics), Descriptive Statistics, Forecasting

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Spring Framework, Prompt Engineering, Cloud-Native Computing, HTML and CSS, Software Development Life Cycle, Software Architecture, Hibernate (Java), Database Design, Docker (Software), Containerization, Git (Version Control System), GitHub, Software Design, Microservices, Object Oriented Programming (OOP), Spring Boot, Large Language Modeling, Object-Relational Mapping, Java Programming, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Visualization Software, Sampling (Statistics), Data Presentation, Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Professional Networking, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Statistical Machine Learning, Object Oriented Programming (OOP), Data Analysis, Interviewing Skills

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.5K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Python Programming, Data Structures, Web Scraping, Data Manipulation, Programming Principles, Pandas (Python Package), Computer Programming, Object Oriented Programming (OOP), Restful API, NumPy, Application Programming Interface (API), Data Analysis, Data Import/Export, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      41K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Excel Basics for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Visualization Software, Information Privacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Data Visualization, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Data Science, Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      English for Career Development

      Skills you'll gain: English Language, Vocabulary, Business Writing, Interviewing Skills, Language Learning, Verbal Communication Skills, Professional Networking, Professional Development, Business Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      17K reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Statistics & Mathematics for Data Science & Data Analytics

      Skills you'll gain: Descriptive Statistics, Probability & Statistics, Statistical Hypothesis Testing, Statistics, Data Analysis, Statistical Analysis, Regression Analysis, Analytics, Statistical Methods, Probability, Data Science, Statistical Modeling, Data-Driven Decision-Making, Statistical Inference, Probability Distribution, Predictive Analytics, Applied Machine Learning, Correlation Analysis

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rutgers the State University of New Jersey

      Supply Chain Management

      Skills you'll gain: Strategic Sourcing, Lean Six Sigma, Lean Manufacturing, Demand Planning, Procurement, Supplier Relationship Management, Forecasting, Process Improvement, Supplier Management, Operations Management, Customer Demand Planning, Purchasing, Production Process, Supply Management, Operational Efficiency, Warehouse Management, Supply Chain Planning, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Visualization, Data Analysis, Tidyverse (R Package), Data Visualization Software, Statistical Programming, Data Cleansing, Data Manipulation, Programming Principles, Data Transformation, Integrated Development Environments, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Macquarie University

      Excel Skills for Business

      Skills you'll gain: Microsoft Excel, Dashboard, Excel Formulas, Spreadsheet Software, Data Visualization, Excel Macros, Data Validation, Data Analysis Expressions (DAX), Data Cleansing, Data Modeling, Financial Forecasting, Workflow Management, Finance, Data Management, Business Intelligence Software, Consolidation, Data Integrity, Data Entry, Business Reporting, Productivity Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      62K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1234…270

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

    • Excel Skills for Statistics and Data Analysis: Intermediate: Macquarie University
    • IBM Java Developer: IBM
    • Google Advanced Data Analytics: Google
    • Business Statistics and Analysis: Rice University
    • Python for Data Science, AI & Development: IBM
    • Excel Basics for Data Analysis: IBM
    • Data Science: Statistics and Machine Learning: Johns Hopkins University
    • English for Career Development: University of Pennsylvania
    • Statistics & Mathematics for Data Science & Data Analytics: Packt
    • Supply Chain Management: Rutgers the State University of New Jersey

    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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