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    • Statistics

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    2940 results for "statistics"

    • Free

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      Eindhoven University of Technology

      Improving your statistical inferences

      Skills you'll gain: Probability & Statistics, Statistical Tests, General Statistics, R Programming, Statistical Programming, Bayesian Statistics, Data Analysis, Probability Distribution, Statistical Analysis, Bayesian Network, Business Analysis, Experiment, Machine Learning

      4.9

      (751 reviews)

      Intermediate · Course · 1-3 Months

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      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Probability & Statistics, General Statistics, Regression, Experiment, Business Analysis, Data Analysis, Statistical Analysis, Mathematics, Statistical Tests, Econometrics, Machine Learning, Machine Learning Algorithms, Calculus, Communication, Linear Algebra, Marketing, R Programming, SQL

      4.1

      (31 reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Colorado Boulder

      Data Science Foundations: Statistical Inference

      Skills you'll gain: General Statistics, Probability & Statistics, Probability Distribution, Statistical Tests, Calculus, Estimation, Mathematics, Business Analysis, Differential Equations, Econometrics, Spreadsheet Software

      4.4

      (138 reviews)

      Intermediate · Specialization · 3-6 Months

    • Free

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      Duke University

      Data Science Math Skills

      Skills you'll gain: Mathematics, Probability & Statistics, General Statistics, Algebra, Bayesian Statistics, Computational Logic, Data Visualization, Graph Theory, Mathematical Theory & Analysis, Plot (Graphics), Probability Distribution, Theoretical Computer Science

      4.5

      (11k reviews)

      Beginner · Course · 1-3 Months

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      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Mathematics, Algebra, Linear Algebra, Mathematical Theory & Analysis, Algorithms, Calculus, Machine Learning, Theoretical Computer Science, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Probability & Statistics, Regression, Computer Programming, Differential Equations, Econometrics, General Statistics, Python Programming, Statistical Machine Learning, Statistical Programming, Statistical Analysis

      4.5

      (241 reviews)

      Beginner · Specialization · 1-3 Months

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      Johns Hopkins University

      Precalculus through Data and Modelling

      Skills you'll gain: Mathematics, Algebra, Data Management, Probability & Statistics, Calculus, Data Model, Data Analysis, Geometry, Applied Mathematics, Data Analysis Software, Regression, Linear Algebra, Mathematical Theory & Analysis

      4.7

      (208 reviews)

      Beginner · Specialization · 3-6 Months

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      Imperial College London

      Statistical Analysis with R for Public Health

      Skills you'll gain: Probability & Statistics, General Statistics, Regression, Business Analysis, Statistical Analysis, Data Analysis, Machine Learning, Machine Learning Algorithms, Statistical Programming, Mathematics, Statistical Tests, R Programming, Probability Distribution, Basic Descriptive Statistics, Correlation And Dependence, Econometrics, Estimation, Bayesian Statistics, Exploratory Data Analysis, Critical Thinking, Data Analysis Software, Forecasting

      4.7

      (1.7k reviews)

      Beginner · Specialization · 3-6 Months

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      University of Colorado Boulder

      Expressway to Data Science: Essential Math

      Skills you'll gain: Mathematics, Algebra, Calculus, Linear Algebra, Mathematical Theory & Analysis, Differential Equations, Theoretical Computer Science, Probability & Statistics, Algorithms, Entrepreneurship, Graph Theory, Leadership and Management, Probability Distribution, Problem Solving, Research and Design, Computer Graphic Techniques, Computer Graphics, General Statistics, Accounting, Big Data, Computer Programming, Corporate Accouting, Data Analysis, Data Management, Data Mining, Data Model, Data Structures, Design and Product, Finance, Investment Management, Product Design, Programming Principles, Software Architecture, Software Engineering

      4.5

      (210 reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Zurich

      An Intuitive Introduction to Probability

      Skills you'll gain: Probability & Statistics, Probability Distribution, General Statistics, Basic Descriptive Statistics, Bayesian Network, Bayesian Statistics, Data Analysis, Machine Learning

      4.8

      (1.5k reviews)

      Beginner · Course · 1-3 Months

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      University of Colorado Boulder

      Generalized Linear Models and Nonparametric Regression

      Skills you'll gain: Mathematics, Probability & Statistics, Regression, General Statistics, Business Analysis, Data Analysis, Machine Learning, Machine Learning Algorithms, Statistical Analysis, Calculus, Communication, Linear Algebra, Marketing

      4.1

      (9 reviews)

      Intermediate · Course · 1-4 Weeks

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      University of Colorado Boulder

      ANOVA and Experimental Design

      Skills you'll gain: Probability & Statistics, Experiment, General Statistics, Business Analysis, Data Analysis, Statistical Analysis, Statistical Tests, Econometrics, Regression, Calculus, Linear Algebra

      4.1

      (8 reviews)

      Intermediate · Course · 1-4 Weeks

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      University of Colorado System

      Data Warehousing for Business Intelligence

      Skills you'll gain: SQL, Databases, Data Management, Statistical Programming, Database Design, Leadership and Management, Communication, Data Model, Data Warehousing, Database Administration, Business Analysis, Business Intelligence, Data Science, Extract, Transform, Load, Database Application, Entrepreneurship, Problem Solving, Research and Design, Basic Descriptive Statistics, Big Data, Data Architecture, Data Analysis, Data Structures, PostgreSQL, Theoretical Computer Science, Accounting, Computational Logic, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Visualization, Data Visualization Software, Decision Making, Interactive Data Visualization, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Programming Principles, Scientific Visualization, Spreadsheet Software

      4.5

      (3.8k reviews)

      Advanced · Specialization · 3-6 Months

    Searches related to statistics

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

    • Improving your statistical inferences: Eindhoven University of Technology
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Data Science Foundations: Statistical Inference: University of Colorado Boulder
    • Data Science Math Skills: Duke University
    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • Precalculus through Data and Modelling: Johns Hopkins University
    • Statistical Analysis with R for Public Health: Imperial College London
    • Expressway to Data Science: Essential Math: University of Colorado Boulder
    • An Intuitive Introduction to Probability: University of Zurich
    • Generalized Linear Models and Nonparametric Regression: University of Colorado Boulder

    Frequently Asked Questions about Statistics

    • If you're interested in learning about statistics for free, check out some of Coursera's options. The Stanford Statistics course and the Probability and Statistics course provide excellent overviews and introductions to the topic. For a deeper dive, consider the Statistical Inferences and Introduction to Probability classes. Finally, the Python Statistics and Financial Analysis class provides a unique perspective on the topic.‎

    • If you are looking for the best beginners statistics courses, Basic Statistics is a great starting point. For a better understanding of data and how to use them, Data: What It Is and What We Can Do With It can help. To learn about inferential statistics, Inferential Statistics Intro, also through Coursera, is a great option. For those wanting to understand how to apply statistics to public health, An Introduction to Statistics and Data Analysis in Public Health is available. Lastly, those looking to explore statistical thinking can find lots of resources in the Statistical Thinking for Data Science and Analytics course.‎

    • The best advanced statistics courses are Linear Models, Introduction to Machine Learning in Production, Probabilistic Graphical Models, Statistical Inferences, and SAS Statistics. These courses provide in-depth, comprehensive coverage of the fundamental concepts, models and techniques associated with advanced statistics.‎

    • Statistics is the science of organizing, analyzing, and interpreting large numerical datasets, with a variety of goals. Descriptive statistics such as mean, median, mode and standard deviation summarize the characteristics of a dataset; statistical inference seeks to determine the characteristics of a large population from a representative sample through statistical hypothesis testing; and statistical regression techniques establish the correlations between an dependent variable and one or more independent variables.

      A familiarity with statistics is critically important for describing and understanding our world. From stock market volatility to political polling to the three-point percentage of your favorite basketball player, statistics help to make the complexity of the world comprehensible - and tell us what to expect. The era of big data has made the use of statistics even more necessary, and data science software like Python and R programming have made data analysis techniques more powerful and more accessible than ever.‎

    • Just as statistics have become more important for making sense of our world, an ability to understand and use statistics has become increasingly essential for a variety of careers. Whether you are working in business, government, or academia, it is increasingly expected that assertions and decisions are backed up by data. Thus, you’ll need a familiarity with statistics whether you’re an operations manager preparing a presentation on process improvements for a CEO or a policy analyst writing a research paper on criminal justice reform for a legislator.

      If you have a passion for building Markov chain models or debating the relative merits of frequentist and Bayesian statistics, you can pursue a career as a full-time statistician. According to the Bureau of Labor Statistics, statisticians earned a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the demand for keen statistical analysis across all fields. Statisticians typically have at least a bachelor’s degree in mathematics, computer science, or other quantitative fields, and many positions require a master’s degree in statistics.‎

    • Yes, with absolute certainty. Coursera offers individual courses as well as Specializations in statistics, as well as courses focused on related topics such as programming in Python and R as well as the applied use of business statistics. These courses and Specializations are offered by top-ranked universities such as the University of Michigan, Duke University, and Johns Hopkins University, ensuring that you won’t sacrifice educational rigor to learn online. You can also learn about statistics through Coursera’s hands-on Guided Projects, which allow you to build skills with step-by-step tutorials from experienced instructors to help you learn with confidence.‎

    • Before starting to learn statistics, you should already have basic math skills and be able to do simple calculations. You also could take math courses in algebra or calculus to prepare for learning statistics, but many people are able to successfully complete basic statistics courses without experience using advanced math. Other skills that may be useful include analytical, problem-solving, and inferential skills. Experience working with computer programming languages can be helpful if you want to take a course to learn how to use a specific language like Python to analyze data sets.‎

    • The kind of people best suited for roles in statistics enjoy working with data and sharing their findings with others. They tend to be analytical thinkers who look for trends and patterns in the data they collect and spend time asking and answering the questions the data prompts. They're able to work with a variety of people, including team members who help them collect and analyze data and the business executives and researchers relying on the information derived from the data. People who have roles in statistics may also have strong communication and presentation skills.‎

    • If you are an analytical thinker who likes collecting, analyzing, and interpreting data, learning statistics may be right for you. Learning statistics can be a logical choice if you like to make predictions or solve problems. You may be able to use the information you learn in a statistics course as preparation for additional studies in fields like mathematics, data science, or marketing. Learning statistics may be for you if you want to work in a field where you’ll use data regularly, such as business administration, marketing, public policy, finance, or insurance. Feeling comfortable organizing information, analyzing data, and viewing it from multiple perspectives can give you an edge over your competition.‎

    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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