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Category: "R"

Courses

  1. DataTrail
    Data Trail

    DataTrail aims to equip individuals with the tools they need to enter the booming field of data science.

  2. Mediation and Moderation Analysis using R
    A Complete Guide to Mediation, Moderation, and Causal Analysis Using R and Real-World Data
    Alexandru Cernat

    This course introduces mediation and moderation analysis using R, covering interaction effects, path analysis, SEM, and causal mediation. Gain the skills to separate mediating vs moderating variables, and state-of-the-art methods such as Structural Equation Modelling and causal mediation.

  3. This course brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this course will lay the foundation for you to begin your journey learning data science.

  4. Introduktion til R
    Introduktion til programmeringssproget R
    Tue Hellstern

    R er et open-source programmeringssprog, det er meget populært blandt statistikere, og andre som arbejder med data-mining. R tilbyder en bred vifte af analyseværktøjer, samt rigtig gode mulighed for grafisk præsentation af dine data.

  5. Dirty Data Dojo: Cleaning Data (Excel & R)
    Learn to Clean Your Dirty Data in Minutes, not Months
    Lee Baker

    Data cleaning is a serious business – you’ll typically spend 80% of your analysis time cleaning data! In this course you’ll learn how to clean your data in a fraction of the time. The steps you’ll learn are very simple to follow, but are extremely effective, so you’ll know that you’re getting the best start possible, saving you weeks of misery!

  6. Introduction to R for Social Researchers
    A Practical Course on Data Preparation, Visualisation, and Statistical Analysis
    Alexandru Cernat

    Learn how to use R confidently for real social research. This hands-on course guides you through data wrangling in R, data visualisation in R, and core statistical methods using practical examples with real-world data. Build a solid R workflow you can apply to your own data right away.