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Results for "advanced statistics"

  • Status: Free Trial
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    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Statistics, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling

    4.4
    Rating, 4.4 out of 5 stars
    ·
    777 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Statistics with Python

    Skills you'll gain: Sampling (Statistics), Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Data Visualization, Descriptive Statistics, Bayesian Statistics, Data Visualization Software, Jupyter, Histogram, Statistical Software, Probability & Statistics, Matplotlib, Statistical Analysis, Statistics, Data Analysis, Box Plots, Statistical Programming, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.3K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
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    U

    University of Colorado Boulder

    Foundations of Probability and Statistics

    Skills you'll gain: Probability, Markov Model, Estimation, Probability & Statistics, Probability Distribution, Statistical Methods, Statistical Inference, Bayesian Statistics, Sampling (Statistics), Statistical Analysis, Mathematical Modeling, Statistics, Statistical Modeling, Data Analysis, Data Science, Descriptive Statistics, Machine Learning Algorithms, Artificial Intelligence, Generative AI

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    ·
    311 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
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    Free Trial
    I

    Illinois Tech

    Advanced Statistical Techniques for Data Science

    Skills you'll gain: Machine Learning Algorithms, Statistical Analysis, Bayesian Statistics, Data Visualization, Statistical Inference, Data Cleansing, Regression Analysis, Analytics, Data Analysis, Machine Learning, R Programming, Data Science, Statistical Modeling, Data Validation, Data Manipulation, Exploratory Data Analysis, R (Software), Data Mining, Statistical Programming, Predictive Modeling

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    45 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    The Power of Statistics

    Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Statistical Hypothesis Testing, Data Analysis, Probability Distribution, Statistics, Data Science, Statistical Analysis, A/B Testing, Statistical Methods, Probability, Statistical Inference, Statistical Programming, Python Programming, Technical Communication

    4.8
    Rating, 4.8 out of 5 stars
    ·
    843 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    V

    Vanderbilt University

    ChatGPT Advanced Data Analysis

    Skills you'll gain: Prompt Engineering, Data Presentation, ChatGPT, Document Management, Artificial Intelligence, Problem Solving, Data Analysis, Information Management, File Management, Creativity, Data Processing, Automation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    895 reviews

    Beginner · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
    New
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    O

    O.P. Jindal Global University

    Statistical Methods and Data Analysis

    Skills you'll gain: Sampling (Statistics), Statistical Analysis, Probability Distribution, Statistical Hypothesis Testing, Descriptive Statistics, Statistical Methods, Correlation Analysis, Regression Analysis, R (Software), R Programming, Statistical Modeling, Statistical Inference, Probability, Big Data, Decision Tree Learning

    Build toward a degree

    Mixed · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.2K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Amsterdam

    Basic Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistics, Scientific Methods, Quantitative Research, Data Analysis Software

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

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    M

    Microsoft

    Statistical Analysis and Advanced Techniques

    Skills you'll gain: Regression Analysis, Statistical Analysis, Time Series Analysis and Forecasting, R Programming, Statistical Hypothesis Testing, Probability & Statistics, Statistical Modeling, Statistical Methods, Predictive Modeling, Generative AI, Statistical Inference, Forecasting, Descriptive Statistics, Power BI

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    M

    Macquarie University

    Statistics and Data Analysis with Excel

    Skills you'll gain: Pivot Tables And Charts, Sample Size Determination, Data Visualization, Statistical Inference, Data Visualization Software, Statistical Hypothesis Testing, Statistics, Data-Driven Decision-Making, Microsoft Excel, Correlation Analysis, Descriptive Statistics, Data Analysis, Forecasting, Regression Analysis, Business Analytics, Probability & Statistics, Excel Formulas, Statistical Modeling, Statistical Visualization, Data Presentation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    28 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Advanced Data Visualization with Matplotlib Mastery

    Skills you'll gain: Matplotlib, Scientific Visualization, Visualization (Computer Graphics), Plot (Graphics), Statistical Visualization, Data Visualization Software, Scatter Plots, Typography, Python Programming

    Mixed · Course · 1 - 4 Weeks

Searches related to advanced statistics

advanced statistics for data science
advanced quantitative statistics with excel
statistics and data analysis with excel: advanced
1234…349

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

  • Advanced Statistics for Data Science: Johns Hopkins University
  • Statistics with Python: University of Michigan
  • Foundations of Probability and Statistics: University of Colorado Boulder
  • Advanced Statistical Techniques for Data Science: Illinois Tech
  • The Power of Statistics: Google
  • ChatGPT Advanced Data Analysis: Vanderbilt University
  • Statistical Methods and Data Analysis : O.P. Jindal Global University
  • Introduction to Statistics: Stanford University
  • Basic Statistics: University of Amsterdam
  • Statistical Analysis and Advanced Techniques: Microsoft

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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