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    Results for "advanced statistics"

    • U

      University of Colorado System

      Computational Thinking with Beginning C Programming

      Skills you'll gain: Computational Thinking, Data Collection, Simulations, Data Analysis, Microsoft Visual Studio, C (Programming Language), Statistical Analysis, Automation, Program Development, Data Structures, Programming Principles, Algorithms, Computer Programming, Development Environment, Descriptive Statistics, Problem Management, File Management, Distributed Computing, Debugging, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      431 reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Macquarie University

      Excel Regression Models for Business Forecasting

      Skills you'll gain: Forecasting, Regression Analysis, Time Series Analysis and Forecasting, Business Mathematics, Microsoft Excel, Statistical Modeling, Trend Analysis, Statistical Analysis, Data Visualization Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      108 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Analyze Website Visitors with Google Analytics Segments

      Skills you'll gain: Google Analytics, Web Analytics, Marketing Analytics, Customer Insights, Analysis, Target Audience

      4.5
      Rating, 4.5 out of 5 stars
      ·
      122 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      P

      Pontificia Universidad Católica del Perú

      Analítica y ciencia de datos para negocios

      Skills you'll gain: Business Analytics, Dimensionality Reduction, Data Processing, Analytics, Data Cleansing, Data Transformation, Anomaly Detection, Business Analysis, Databases, Feature Engineering, R Programming, Data Analysis, Data Quality, Data Science, Exploratory Data Analysis, Statistical Methods, Unsupervised Learning, Supervised Learning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      52 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Maryland, College Park

      Dealing With Missing Data

      Skills you'll gain: Sampling (Statistics), Statistical Programming, Data Cleansing, Data Quality, Data Analysis Software, Statistical Analysis, Statistical Methods, Statistical Modeling, R Programming, Regression Analysis, Statistical Inference

      3.8
      Rating, 3.8 out of 5 stars
      ·
      135 reviews

      Mixed · Course · 1 - 3 Months

    • M

      MathWorks

      Predictive Modeling and Machine Learning with MATLAB

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Matlab, Regression Analysis, Predictive Modeling, Classification And Regression Tree (CART), Machine Learning, Predictive Analytics, Feature Engineering, Statistical Modeling, Data Processing, Sampling (Statistics)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Arizona State University

      Strategic Thinking

      Skills you'll gain: Strategic Thinking, Strategic Decision-Making, Systems Thinking, Strategic Planning, Business Strategy, Complex Problem Solving, Decision Making, Analysis, Trend Analysis, Competitive Analysis, Risk Analysis, Data-Driven Decision-Making, Market Intelligence, Performance Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      46 reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      U

      University of Michigan

      Data-Oriented Python Programming and Debugging

      Skills you'll gain: Debugging, NumPy, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Pandas (Python Package), Data Structures, Probability & Statistics, Statistical Methods, Probability, Statistics, Probability Distribution, Statistical Analysis, Data Analysis, Program Development, Large Language Modeling, Data Manipulation, Programming Principles, Computer Programming, Python Programming

      Intermediate · Specialization · 3 - 6 Months

    • L

      LearnKartS

      CEH (v12) Practice Projects and Exam Simulators

      Skills you'll gain: Penetration Testing, Cyber Security Assessment, Cybersecurity, Cyber Attacks, Vulnerability Assessments, Network Security, Scenario Testing, Malware Protection, Encryption, Test Case

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Corporate Finance Institute

      Fundamentals of Data Analysis in Excel

      Skills you'll gain: Microsoft Excel, Pivot Tables And Charts, Spreadsheet Software, Dashboard, Data Transformation, Data Analysis, Excel Formulas, Exploratory Data Analysis, Data Visualization Software, Data Presentation, Data Manipulation, Data Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      47 reviews

      Beginner · Course · 1 - 3 Months

    • I

      Imperial College London

      Introduction to Android graphics

      Skills you'll gain: Computer Graphics, Visualization (Computer Graphics), Android Development, Computer Graphic Techniques, Animation and Game Design, Virtual Reality, Linear Algebra

      4.1
      Rating, 4.1 out of 5 stars
      ·
      71 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Using Descriptive Statistics to Analyze Data in R

      Skills you'll gain: Descriptive Statistics, R Programming, Statistical Reporting, Data Quality, Data Cleansing, Statistical Methods, Data Manipulation, Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92 reviews

      Beginner · Guided Project · Less Than 2 Hours

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…929394…264

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

    • Computational Thinking with Beginning C Programming: University of Colorado System
    • Excel Regression Models for Business Forecasting: Macquarie University
    • Analyze Website Visitors with Google Analytics Segments: Coursera Project Network
    • Analítica y ciencia de datos para negocios: Pontificia Universidad Católica del Perú
    • Dealing With Missing Data: University of Maryland, College Park
    • Predictive Modeling and Machine Learning with MATLAB: MathWorks
    • Strategic Thinking: Arizona State University
    • Data-Oriented Python Programming and Debugging: University of Michigan
    • CEH (v12) Practice Projects and Exam Simulators: LearnKartS
    • Fundamentals of Data Analysis in Excel: Corporate Finance Institute

    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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