Programa de cursos integrados Statistics with R

Inicia em Oct 17

Programa de cursos integrados Statistics with R

Master Statistics with R. Statistical mastery of data analysis including inference, modeling, and Bayesian approaches.

Sobre esse Programa de cursos integrados

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.

Desenvolvido por:

courses
5 courses

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projects
Projetos

Projetado para ajudar a praticar e aplicar as habilidades que aprendeu.

certificates
Certificados

Dê destaque às suas novas habilidades em seu currículo ou no seu perfil do LinkedIn.

Cursos
Beginner Specialization.
No prior experience required.
  1. CURSO 1

    Introduction to Probability and Data

    Compromisso
    5 weeks of study, 5-7 hours/week
    Legendas
    English, Korean

    Sobre o curso

    This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of explorato
  2. CURSO 2

    Inferential Statistics

    Compromisso
    5 weeks of study, 5-7 hours/week
    Legendas
    English

    Sobre o curso

    This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpreta
  3. CURSO 3

    Linear Regression and Modeling

    Compromisso
    4 semanas de estudo, 5-7 horas/semana
    Legendas
    English

    Sobre o curso

    This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractivene
  4. CURSO 4

    Bayesian Statistics

    Compromisso
    5 weeks of study, 5-7 hours/week
    Legendas
    English

    Sobre o curso

    This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced
  5. CURSO 5

    Statistics with R Capstone

    Próxima sessão: Dec 3
    Compromisso
    5-10 hours/week
    Legendas
    English

    Sobre o Trabalho de Conclusão

    The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. A large and complex dataset will be provided to learners and the analysis will require the application of a

Desenvolvedores

  • Duke University

    Duke University is consistently ranked as a top research institution, with graduate and professional schools among the leaders in their fields.

    Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.

  • Mine Çetinkaya-Rundel

    Mine Çetinkaya-Rundel

    Associate Professor of the Practice
  • David Banks

    David Banks

    Professor of the Practice
  • Colin Rundel

    Colin Rundel

    Assistant Professor of the Practice
  • Merlise A Clyde

    Merlise A Clyde

    Professor

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