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    Results for "advanced statistics"

    • 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, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling, Sample Size Determination

      4.4
      Rating, 4.4 out of 5 stars
      ·
      761 reviews

      Advanced · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Probability & Statistics for Machine Learning & Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      554 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      The Power of Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      779 reviews

      Advanced · Course · 1 - 3 Months

    • Unlock Access to 10,000+ courses with a subscription.

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    • U

      University of Michigan

      Statistics with Python

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

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

      Beginner · Specialization · 1 - 3 Months

    • G

      Google

      Google Advanced Data Analytics

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

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    What brings you to Coursera today?

    • Status: Free
      Free
      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, Data Collection, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4K reviews

      Beginner · Course · 1 - 3 Months

    • M

      Meta

      Statistics Foundations

      Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Quantitative Research, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      326 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Jupyter, Advanced Mathematics, Data Science, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Advanced Business Analytics

      Skills you'll gain: Data Storytelling, Data Presentation, Data Governance, Data Visualization, Predictive Analytics, Analytics, Business Analytics, Data Storage, Data Management, Big Data, Risk Analysis, Databases, Data Modeling, Data Visualization Software, Data Analysis, Presentations, Decision Making, Business Intelligence, Data Cleansing, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      E

      Eindhoven University of Technology

      Improving your statistical inferences

      Skills you'll gain: Statistical Inference, Scientific Methods, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Probability & Statistics, Sample Size Determination, Research, Data Collection, R Programming, Data Sharing, Probability Distribution

      4.9
      Rating, 4.9 out of 5 stars
      ·
      793 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Statistical Inference, Statistical Methods, Pandas (Python Package), Probability & Statistics, Risk Analysis, Financial Trading, Financial Data, Data Manipulation, Statistical Analysis, Regression Analysis, Financial Analysis, Jupyter, Financial Modeling

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.5K reviews

      Intermediate · Course · 1 - 4 Weeks

    What brings you to Coursera today?

      Searches related to advanced statistics

      advanced statistics for data science
      advanced quantitative statistics with excel
      advanced statistical analysis and tools
      seaborn: visualizing basics to advanced statistical plots
      advanced probability and statistical methods
      advanced linear models for data science 2: statistical linear models
      1234…262

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

      • Advanced Statistics for Data Science: Johns Hopkins University
      • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
      • The Power of Statistics: Google
      • Statistics with Python: University of Michigan
      • Google Advanced Data Analytics: Google
      • Introduction to Statistics: Stanford University
      • Statistics Foundations: Meta
      • Bayesian Statistics: University of California, Santa Cruz
      • Mathematics for Machine Learning: Imperial College London
      • Advanced Business Analytics: University of Colorado Boulder

      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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