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    2865 results for "statistics"

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      Stanford University

      Introduction to Statistics

      Skills you'll gain: Data Science, General Statistics, Probability & Statistics, Statistical Tests, Estimation, Basic Descriptive Statistics, Correlation And Dependence, Probability Distribution, Regression, Bayesian Statistics, Data Analysis, Data Visualization, Econometrics, Experiment, Machine Learning, Markov Model, Plot (Graphics), Statistical Analysis, Statistical Visualization

      4.5

      (1.9k reviews)

      Beginner · Course · 1-3 Months

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      University of Michigan

      Statistics with Python

      Skills you'll gain: Probability & Statistics, General Statistics, Statistical Programming, Python Programming, Data Science, Business Analysis, Regression, Computer Programming, Data Analysis, Statistical Analysis, Statistical Tests, Experiment, Econometrics, Machine Learning, Machine Learning Algorithms, Data Visualization, Statistical Visualization, Bayesian Statistics, Correlation And Dependence, Data Analysis Software, Estimation, Basic Descriptive Statistics, Mathematics, Plot (Graphics), Programming Principles

      4.6

      (3k reviews)

      Beginner · Specialization · 1-3 Months

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      Johns Hopkins University

      Advanced Statistics for Data Science

      Skills you'll gain: Probability & Statistics, General Statistics, Mathematics, Probability Distribution, Regression, Linear Algebra, Bayesian Statistics, Experiment, Econometrics, Machine Learning, Basic Descriptive Statistics, Biostatistics, Calculus, Statistical Tests, Algebra, Artificial Neural Networks, Dimensionality Reduction, Machine Learning Algorithms, Statistical Machine Learning, Communication, Correlation And Dependence, Data Analysis, Estimation, Exploratory Data Analysis, Statistical Analysis

      4.4

      (688 reviews)

      Advanced · Specialization · 3-6 Months

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      University of Amsterdam

      Methods and Statistics in Social Sciences

      Skills you'll gain: General Statistics, Probability & Statistics, Statistical Tests, R Programming, Statistical Programming, Correlation And Dependence, Probability Distribution, Regression, Basic Descriptive Statistics, Experiment, Algebra, Exploratory Data Analysis, Machine Learning, Scientific Visualization, Research and Design, Data Analysis, Statistical Visualization, Linear Algebra, Plot (Graphics), Statistical Analysis, Business Analysis, Estimation

      4.6

      (7.1k reviews)

      Beginner · Specialization · 3-6 Months

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      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Business Analysis, General Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Spreadsheet Software, Microsoft Excel, Statistical Tests, Basic Descriptive Statistics, Regression, Business Intelligence, Data Visualization, Probability Distribution, Statistical Visualization, Experiment, Plot (Graphics), Data Mining, Exploratory Data Analysis, Computer Programming, Correlation And Dependence, Data Analysis Software, Econometrics, Mathematics

      4.7

      (11.7k reviews)

      Beginner · Specialization · 3-6 Months

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      Google

      Google Data Analytics

      Skills you'll gain: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Change Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development

      4.8

      (101.8k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      Duke University

      Data Analysis with R

      Skills you'll gain: Probability & Statistics, General Statistics, Data Analysis, Statistical Analysis, Regression, R Programming, Statistical Programming, Statistical Tests, Bayesian Statistics, Econometrics, Business Analysis, Data Science, Probability Distribution, Mathematics, Correlation And Dependence, Experiment, Exploratory Data Analysis, Machine Learning, Machine Learning Algorithms, Basic Descriptive Statistics, Data Mining, Plot (Graphics), Statistical Visualization, Data Analysis Software, Data Visualization

      4.7

      (6.9k reviews)

      Beginner · Specialization · 3-6 Months

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      University of Amsterdam

      Basic Statistics

      Skills you'll gain: General Statistics, Statistical Tests, Probability & Statistics, Probability Distribution, R Programming, Statistical Programming, Algebra, Basic Descriptive Statistics, Exploratory Data Analysis, Machine Learning, Scientific Visualization, Correlation And Dependence, Regression, Experiment, Statistical Visualization, Data Analysis, Linear Algebra, Plot (Graphics), Statistical Analysis

      4.6

      (4.3k reviews)

      Beginner · Course · 1-3 Months

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      Johns Hopkins University

      Biostatistics in Public Health

      Skills you'll gain: Probability & Statistics, General Statistics, Biostatistics, Regression, Statistical Analysis, Business Analysis, Data Analysis, Statistical Tests, Econometrics, Experiment, Basic Descriptive Statistics, Correlation And Dependence, Estimation, Mobile Development, Probability Distribution, iOS Development, Data Visualization, Exploratory Data Analysis, Feature Engineering, Machine Learning, Plot (Graphics), Statistical Visualization

      4.8

      (2k reviews)

      Beginner · Specialization · 3-6 Months

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      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Probability & Statistics, Bayesian Statistics, General Statistics, Probability Distribution, Data Science, Statistical Programming, R Programming, Regression, Forecasting, Machine Learning, Markov Model, Statistical Machine Learning, Bayesian Network, Basic Descriptive Statistics, Estimation, Experiment, Correlation And Dependence, Data Visualization, Machine Learning Algorithms, Statistical Tests, Statistical Visualization, Advertising, Business Analysis, Communication, Data Analysis, Graph Theory, Marketing, Mathematics, Statistical Analysis

      4.6

      (3.3k reviews)

      Intermediate · Specialization · 3-6 Months

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      Free

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      University of London

      Probability and Statistics: To p or not to p?

      Skills you'll gain: General Statistics, Probability & Statistics, Experiment, Decision Making, Entrepreneurship, Leadership and Management, Probability Distribution, Data Management, Data Structures, Machine Learning, Markov Model, Theoretical Computer Science

      4.6

      (1.4k reviews)

      Beginner · Course · 1-3 Months

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      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Skills you'll gain: R Programming, Statistical Programming, General Statistics, Statistical Analysis, Data Analysis, Machine Learning, Probability & Statistics, Statistical Tests, Data Science, Machine Learning Software, Basic Descriptive Statistics, Bayesian Statistics, Correlation And Dependence, Econometrics, Estimation, Linear Algebra, Regression, Exploratory Data Analysis, Theoretical Computer Science, Data Visualization, Interactive Data Visualization, Natural Language Processing, Probability Distribution, Plot (Graphics), Machine Learning Algorithms, Algorithms, Applied Machine Learning, Business Analysis

      4.4

      (7k reviews)

      Intermediate · Specialization · 3-6 Months

    Searches related to statistics

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

    • Introduction to Statistics: Stanford University
    • Statistics with Python: University of Michigan
    • Advanced Statistics for Data Science: Johns Hopkins University
    • Methods and Statistics in Social Sciences: University of Amsterdam
    • Business Statistics and Analysis: Rice University
    • Google Data Analytics: Google
    • Data Analysis with R: Duke University
    • Basic Statistics: University of Amsterdam
    • Biostatistics in Public Health: Johns Hopkins University
    • Bayesian Statistics: University of California, Santa Cruz

    Frequently Asked Questions about 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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