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    Results for "advanced statistics"

    • N

      New York Institute of Finance

      Operational Risk Management: Frameworks & Strategies

      Skills you'll gain: Operational Risk, Risk Management Framework, Risk Management, Business Risk Management, Enterprise Risk Management (ERM), Risk Appetite, Risk Control, Governance, Risk Analysis, Key Performance Indicators (KPIs), Business Process, Regulatory Requirements, Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      352 reviews

      Beginner · Course · 1 - 3 Months

    • S

      SAS

      Data Literacy: Exploring and Visualizing Data

      Skills you'll gain: Exploratory Data Analysis, Data Literacy, Data Storytelling, Data-Driven Decision-Making, Data Presentation, SAS (Software), Trend Analysis, Data Manipulation, Data Analysis, Data Quality, Data Cleansing, Scatter Plots, Interactive Data Visualization, Technical Communication, Time Series Analysis and Forecasting, Data Ethics, Data Visualization, Data Visualization Software, Research, Business Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 1 - 3 Months

    • U

      University of Pennsylvania

      Statistics for Data Science Essentials

      Skills you'll gain: Probability, Probability & Statistics, Sampling (Statistics), Probability Distribution, Statistics, Data Science, Statistical Inference, Descriptive Statistics, Statistical Analysis, General Mathematics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Supervised Machine Learning: Classification

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
      ·
      408 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      M

      McMaster University

      Experimentation for Improvement

      Skills you'll gain: Experimentation, Data Visualization, Predictive Modeling, Process Improvement and Optimization, Regression Analysis, Statistical Software, Mathematical Modeling, R Programming, Data Analysis, Statistical Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      921 reviews

      Intermediate · Course · 1 - 3 Months

    • R

      Rice University

      Introduction to Biology: Ecology, Evolution, & Biodiversity

      Skills you'll gain: Biology, Environment, Microbiology, Life Sciences, Environmental Science, Environmental Issue, Environment and Resource Management, Demography, Natural Resource Management, Anatomy, Molecular Biology, Taxonomy, Estimation, Scientific Methods, Research, Experimentation, Data Collection, Research Methodologies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      200 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of Lausanne

      Accounting 1

      Skills you'll gain: Balance Sheet, Income Statement, Cash Flows, Financial Accounting, Financial Statements, Accounting, Bookkeeping, Working Capital, General Accounting, Accrual Accounting, Financial Reporting, Financial Analysis, Ledgers (Accounting), Profit and Loss (P&L) Management, Accounts Payable and Receivable, Reconciliation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      161 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Washington

      Practical Predictive Analytics: Models and Methods

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Big Data

      4.1
      Rating, 4.1 out of 5 stars
      ·
      320 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California, Davis

      Quantitative Research

      Skills you'll gain: Surveys, Survey Creation, Quantitative Research, Statistical Analysis, Marketing Analytics, Market Research, Statistical Methods, Data Analysis, Marketing, Target Market, Sample Size Determination, Quality Control

      4.4
      Rating, 4.4 out of 5 stars
      ·
      335 reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Linear Algebra from Elementary to Advanced

      Skills you'll gain: Linear Algebra, Algebra, Applied Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Advanced Mathematics, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Graph Theory, Applied Machine Learning, Markov Model, Probability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      169 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      Technion - Israel Institute of Technology

      Nanotechnology and Nanosensors, Part1

      Skills you'll gain: Engineering, Scientific, and Technical Instruments, Semiconductors, Innovation, Chemical and Biomedical Engineering, Emerging Technologies, Chemistry, Electronics, Medical Equipment and Technology, Laboratory Research, Chemical Engineering, Creative Design, Biochemistry

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

      Mixed · Course · 1 - 3 Months

    • T

      The State University of New York

      Solar Energy System Design

      Skills you'll gain: Electrical Systems, Electrical Power, Basic Electrical Systems, Equipment Design, Energy and Utilities, Electrical Equipment, Survey Creation, System Requirements, Engineering Calculations, Performance Testing, Physical Science, Spatial Analysis, Estimation, Physics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      450 reviews

      Intermediate · Course · 1 - 3 Months

    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
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…363738…263

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

    • Operational Risk Management: Frameworks & Strategies: New York Institute of Finance
    • Data Literacy: Exploring and Visualizing Data: SAS
    • Statistics for Data Science Essentials: University of Pennsylvania
    • Supervised Machine Learning: Classification: IBM
    • Experimentation for Improvement: McMaster University
    • Introduction to Biology: Ecology, Evolution, & Biodiversity: Rice University
    • Accounting 1: University of Lausanne
    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Quantitative Research: University of California, Davis
    • Linear Algebra from Elementary to Advanced: 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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