• Anytime
    Application Deadline
  • 7 months
    Duration
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Overview

The programme

In this Statistics with R offered by Coursera in partnership with Duke University, 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.

Detailed Programme Facts

Programme Structure

Courses include:

  • Introduction to Probability and Data
  • Inferential Statistics
  • Linear Regression and Modeling
  • Bayesian Statistics
  • Statistics with R Capstone

English Language Requirements

This programme may require students to demonstrate proficiency in English.

General Requirements

Beginner Level

Tuition Fee

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Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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