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    Results for "advanced statistics"

    • M

      Macquarie University

      Excel Fundamentals for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Spreadsheet Software, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.1K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      U

      University of Colorado Boulder

      Statistics and Applied Data Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Statistical Programming, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      31 reviews

      Beginner · Specialization · 3 - 6 Months

    • T

      The Hong Kong University of Science and Technology

      Mathematics for Engineers

      Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Calculations, Engineering Analysis, Numerical Analysis, Finite Element Methods, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking, Estimation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Applied Data Science Capstone

      Skills you'll gain: Plotly, Exploratory Data Analysis, Predictive Modeling, Data Science, Data-Driven Decision-Making, Data Presentation, Data Analysis, Pandas (Python Package), Web Scraping, Statistical Modeling, Data Wrangling, Machine Learning Methods, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.3K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Modern Regression Analysis in R

      Skills you'll gain: Statistical Inference, Statistical Modeling, Regression Analysis, Data Ethics, Statistical Methods, Statistical Hypothesis Testing, Data Science, R Programming, Data Modeling, Statistical Analysis, Predictive Modeling, Probability & Statistics, Correlation Analysis, Forecasting, Linear Algebra

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      30 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI for Medical Diagnosis

      Skills you'll gain: Image Analysis, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Applied Machine Learning, Medical Imaging, Machine Learning Algorithms, Computer Vision, Deep Learning, Natural Language Processing, Medical Science and Research, Radiology, Artificial Neural Networks, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • E

      EDHEC Business School

      Investment Management with Python and Machine Learning

      Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Asset Management, Network Analysis, Data Visualization Software, Machine Learning Methods, Financial Data, Unstructured Data, Predictive Modeling, Web Scraping, Machine Learning, Advanced Analytics, Financial Statements, Applied Machine Learning, Financial Market, Financial Analysis, Financial Modeling, Return On Investment, Risk Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Advanced R Programming

      Skills you'll gain: Object Oriented Programming (OOP), R Programming, Debugging, Functional Design, Programming Principles, Data Manipulation, Data Structures, Software Design Patterns, Performance Tuning

      4.2
      Rating, 4.2 out of 5 stars
      ·
      574 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Linear Algebra, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    • I

      Imperial College London

      Mathematics for Machine Learning: PCA

      Skills you'll gain: Dimensionality Reduction, NumPy, Probability & Statistics, Feature Engineering, Jupyter, Data Science, Statistics, Linear Algebra, Python Programming, Advanced Mathematics, Machine Learning, Calculus

      4
      Rating, 4 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • T

      The State University of New York

      Advanced Information Literacy

      Skills you'll gain: Information Management, Research, Literacy, Lifelong Learning, Critical Thinking, Investigation, Intellectual Property, Planning, Journals, Style Guides

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…202122…262

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

    • Excel Fundamentals for Data Analysis: Macquarie University
    • Statistics and Applied Data Analysis: University of Colorado Boulder
    • Mathematics for Engineers: The Hong Kong University of Science and Technology
    • Applied Data Science Capstone: IBM
    • Exploratory Data Analysis for Machine Learning: IBM
    • Modern Regression Analysis in R: University of Colorado Boulder
    • AI for Medical Diagnosis: DeepLearning.AI
    • Investment Management with Python and Machine Learning: EDHEC Business School
    • Advanced R Programming: Johns Hopkins University
    • Machine Learning: Regression: University of Washington

    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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