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    Results for "advanced statistics"

    • U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Understanding and Visualizing Data with Python

      Skills you'll gain: Sampling (Statistics), Data Visualization, Statistics, Matplotlib, Statistical Visualization, Probability & Statistics, Jupyter, Statistical Methods, Data Visualization Software, Data Analysis, Statistical Analysis, Exploratory Data Analysis, Descriptive Statistics, Statistical Inference, Data Collection, NumPy, Histogram, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Macquarie University

      Excel Skills for Data Analytics and Visualization

      Skills you'll gain: Pivot Tables And Charts, Data Storytelling, Power BI, Excel Formulas, Data Analysis Expressions (DAX), Data Visualization Software, Interactive Data Visualization, Microsoft Excel, Spreadsheet Software, Dashboard, Data Modeling, Data Cleansing, Data Manipulation, Excel Macros, Infographics, Data Transformation, Data Analysis Software, Data Validation, Data Analysis, Microsoft Power Platform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • R

      Rutgers the State University of New Jersey

      Supply Chain Logistics

      Skills you'll gain: Warehouse Management, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics, Logistics, Transportation Operations, Supply Chain Management, Supply Chain, Customer Service, Operating Cost

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

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Statistical Inference, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, R Programming, Data Ethics, Statistical Methods, Data Analysis, Statistical Analysis, Data Modeling, Predictive Modeling, Probability & Statistics, Advanced Analytics, Correlation Analysis, Forecasting, Data Science, A/B Testing, Machine Learning, Classification And Regression Tree (CART), Linear Algebra

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      52 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of California, Davis

      Geographic Information Systems (GIS)

      Skills you'll gain: ArcGIS, GIS Software, Spatial Data Analysis, Spatial Analysis, Data Storytelling, Geographic Information Systems, Data Presentation, Data Sharing, Geospatial Mapping, Public Health, Land Management, Heat Maps, Metadata Management, Data Quality, Community Health, Data Mapping, Data Visualization Software, File Management, Network Analysis, Data Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Visualization with Python

      Skills you'll gain: Data Visualization Software, Plotly, Data Visualization, Dashboard, Interactive Data Visualization, Matplotlib, Seaborn, Data Presentation, Data Analysis, Geospatial Information and Technology, Pandas (Python Package), Scatter Plots, Histogram, Heat Maps, Box Plots

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization Software, Key Performance Indicators (KPIs), Data Visualization, Dashboard, Interactive Data Visualization, Data Mapping, Tableau Software, Proposal Development, Graphing, Histogram, Scatter Plots, Tree Maps, Exploratory Data Analysis, Statistical Visualization, Storytelling, Performance Metric, Geospatial Mapping, Heat Maps

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Epidemiology in Public Health Practice

      Skills you'll gain: Epidemiology, Public Health, Spatial Data Analysis, Data Presentation, Public Health and Disease Prevention, Geographic Information Systems, Health Policy, Chronic Diseases, Health Systems, Infectious Diseases, Biostatistics, Risk Analysis, Investigation, Community Health, Health Care, Data Analysis, Program Evaluation, Health Information Management, Health Informatics, Continuous Monitoring

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistical Analysis, Applied Mathematics, Advanced Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      187 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Customer Analytics

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Marketing Analytics, Predictive Analytics, Customer Insights, Customer Analysis, Business Analytics, Customer Data Management, Analytics, Marketing, Data Collection, Market Research, Regression Analysis, Consumer Behaviour, Correlation Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      12K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      E

      Erasmus University Rotterdam

      Econometrics: Methods and Applications

      Skills you'll gain: Econometrics, Time Series Analysis and Forecasting, Regression Analysis, Data Analysis, Statistical Analysis, Quantitative Research, Statistical Modeling, Statistics, Predictive Analytics, Probability, Linear Algebra, Peer Review

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Mixed · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…121314…260

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

    • Introduction to Data Science in Python: University of Michigan
    • Understanding and Visualizing Data with Python: University of Michigan
    • Excel Skills for Data Analytics and Visualization: Macquarie University
    • Supply Chain Logistics: Rutgers the State University of New Jersey
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Geographic Information Systems (GIS): University of California, Davis
    • Data Visualization with Python: IBM
    • Data Visualization with Tableau: University of California, Davis
    • Epidemiology in Public Health Practice: Johns Hopkins University
    • Advanced Linear Models for Data Science 1: Least Squares: 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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