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    Results for "advanced statistics"

    • R

      Rice University

      Business Finance and Data Analysis Fundamentals

      Skills you'll gain: Capital Budgeting, Cash Flows, Financial Statements, Microsoft Excel, Descriptive Statistics, Financial Accounting, Business Analytics, Box Plots, Probability Distribution, Financial Analysis, Finance, Data Visualization, Probability, Statistics, Business Valuation, Financial Statement Analysis, Business Mathematics, Accounting, Return On Investment, General Accounting

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      Convolutional Neural Networks in TensorFlow

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Computer Vision, Image Analysis, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Supervised Learning, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      E

      Erasmus University Rotterdam

      Econometrics: Methods and Applications

      Skills you'll gain: Econometrics, Time Series Analysis and Forecasting, Regression Analysis, Data Analysis, Statistical Analysis, Quantitative Research, Statistical Modeling, Statistics, Predictive Analytics, Probability, Linear Algebra, Peer Review

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

      Mixed · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Mathematical Biostatistics Boot Camp 2

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Statistical Methods, Probability & Statistics, Statistical Inference, Biostatistics, Sampling (Statistics), Data Analysis, Sample Size Determination, Risk Analysis, Probability Distribution

      4.3
      Rating, 4.3 out of 5 stars
      ·
      133 reviews

      Mixed · Course · 1 - 4 Weeks

    • M

      Macquarie University

      Excel Skills for Business: Intermediate II

      Skills you'll gain: Excel Formulas, Microsoft Excel, Excel Macros, Data Validation, Spreadsheet Software, Data Modeling, Financial Forecasting, Workflow Management, Data Integrity, Business Modeling, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      8.3K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Data Visualization and Dashboards with Excel and Cognos

      Skills you'll gain: Data Storytelling, Data Visualization Software, Dashboard, IBM Cognos Analytics, Tree Maps, Scatter Plots, Pivot Tables And Charts, Microsoft Excel, Histogram

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      Make the Sale: Build, Launch, and Manage E-commerce Stores

      Skills you'll gain: Order Fulfillment, E-Commerce, Order Processing, Campaign Management, Digital Advertising, Google Ads, Retail Management, Customer Engagement, Marketing Strategies, Market Research, Web Analytics, Trend Analysis, Customer experience strategy (CX), Target Audience

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Supply Chain Management: A Learning Perspective

      Skills you'll gain: New Product Development, Supply Chain Management, Supply Chain Planning, Innovation, Quality Management, Operations Management, Logistics Management, Supplier Management, Transportation, Supply Chain, and Logistics, Inventory Management System, Coordinating, Corporate Sustainability, Value Propositions, Continuous Improvement Process, Consumer Behaviour, Cross-Functional Collaboration, Decision Making, Complex Problem Solving

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Houston

      Math behind Moneyball

      Skills you'll gain: Probability & Statistics, Statistical Methods, Statistics, Microsoft Excel, Predictive Analytics, Game Theory, Spreadsheet Software, Predictive Modeling, Excel Formulas, Pivot Tables And Charts, Regression Analysis, Statistical Analysis, Advanced Analytics, Data-Driven Decision-Making, Data Analysis, Analytics, Data Analysis Software, Business Mathematics, Simulations, Forecasting

      4.5
      Rating, 4.5 out of 5 stars
      ·
      97 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      University of Amsterdam

      Data Analytics for Lean Six Sigma

      Skills you'll gain: Lean Six Sigma, Statistical Hypothesis Testing, Minitab, Regression Analysis, Data Visualization Software, Probability Distribution, Descriptive Statistics, Data Analysis, Statistical Analysis, Box Plots, Analytics, Process Improvement, Correlation Analysis, Variance Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Data Ethics, Applied Machine Learning, Computer Vision, Machine Learning, Unsupervised Learning, Artificial Intelligence, Information Privacy, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…151617…262

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

    • Business Finance and Data Analysis Fundamentals: Rice University
    • Meta Data Analyst: Meta
    • Convolutional Neural Networks in TensorFlow: DeepLearning.AI
    • Econometrics: Methods and Applications: Erasmus University Rotterdam
    • Mathematical Biostatistics Boot Camp 2: Johns Hopkins University
    • Excel Skills for Business: Intermediate II: Macquarie University
    • Data Visualization and Dashboards with Excel and Cognos: IBM
    • Make the Sale: Build, Launch, and Manage E-commerce Stores: Google
    • Supply Chain Management: A Learning Perspective : Korea Advanced Institute of Science and Technology(KAIST)
    • Math behind Moneyball: University of Houston

    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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