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    Results for "advanced statistics"

    • 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 Michigan

      Fitting Statistical Models to Data with Python

      Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Probability Distribution

      4.4
      Rating, 4.4 out of 5 stars
      ·
      699 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      ISC2

      Security Principles

      Skills you'll gain: Security Controls, Information Assurance, Cybersecurity, Risk Management Framework, Security Awareness, Cyber Governance, Security Management, Cyber Risk, Security Strategy, Personally Identifiable Information, Data Ethics, Data Integrity

      4.7
      Rating, 4.7 out of 5 stars
      ·
      543 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      The Brain and Space

      Skills you'll gain: Spatial Analysis, Neurology, Human Learning, Experimentation, Laboratory Research, Physics, Biology, General Science and Research, Magnetic Resonance Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      652 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Research Proposal: Initiating Research

      Skills you'll gain: Market Research, Proposal Writing, Research Methodologies, Market Analysis, Business Research, Data Collection, Quantitative Research, Business Writing, Sampling (Statistics), Survey Creation, Qualitative Research, Request for Proposal, Client Services, Professional Networking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      918 reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Build Better Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Data Ethics, Deep Learning, Machine Learning, Image Analysis, Artificial Neural Networks, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Deep Learning with Keras and Tensorflow

      Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Unsupervised Learning, Deep Learning, Tensorflow, Generative AI, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Image Analysis, Time Series Analysis and Forecasting, Natural Language Processing, Performance Tuning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      935 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Starweaver

      Certified Business Analysis Professional™ (CBAP®)

      Skills you'll gain: Process Analysis, Requirements Elicitation, Business Analysis, Risk Analysis, Backlogs, Requirements Management, Stakeholder Engagement, Business Process, User Requirements Documents, User Story, Business Requirements, Requirements Analysis, Business Modeling, Business Process Improvement, Business Intelligence, Business Risk Management, Business Strategies, Financial Analysis, Performance Measurement, Business Planning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      237 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Free
      Free
      J

      Johns Hopkins University

      Advanced Business Analytics: Excel Optimization & Simulation

      Skills you'll gain: Operations Research, Resource Allocation, Simulation and Simulation Software, Microsoft Excel, Business Analytics, Data-Driven Decision-Making, Business Risk Management, Transportation Operations, Risk Analysis, Process Optimization, Statistical Methods, Business Modeling, Logistics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      18 reviews

      Mixed · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data Science in Real Life

      Skills you'll gain: Data Quality, Data Management, Technical Communication, Data Analysis, Data-Driven Decision-Making, Statistical Analysis, Data Science, Statistical Machine Learning, Statistical Inference, A/B Testing, Statistical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Advanced Algorithms and Complexity

      Skills you'll gain: Algorithms, Network Routing, Network Model, Graph Theory, Operations Research, Theoretical Computer Science, Network Analysis, Data Structures, Computational Thinking, Linear Algebra, Computer Science, Big Data, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      694 reviews

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      E

      Edureka

      Applied Data Analytics

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Visualization, Exploratory Data Analysis, Matplotlib, Data Visualization Software, Web Scraping, Probability Distribution, Predictive Modeling, Seaborn, Statistical Visualization, SQL, Plotly, Interactive Data Visualization, Statistical Inference, Pandas (Python Package), Database Management, Data Analysis, Data Presentation, Databases

      3.9
      Rating, 3.9 out of 5 stars
      ·
      7 reviews

      Intermediate · Specialization · 3 - 6 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
    advanced linear models for data science 2: statistical linear models
    1…323334…262

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

    • Data Literacy: Exploring and Visualizing Data: SAS
    • Fitting Statistical Models to Data with Python: University of Michigan
    • Security Principles: ISC2
    • The Brain and Space: Duke University
    • Research Proposal: Initiating Research: University of California, Davis
    • Build Better Generative Adversarial Networks (GANs): DeepLearning.AI
    • Deep Learning with Keras and Tensorflow: IBM
    • Certified Business Analysis Professionalâ„¢ (CBAP®): Starweaver
    • Advanced Business Analytics: Excel Optimization & Simulation: Johns Hopkins University
    • Data Science in Real Life: 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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