Big Data in Social Sciences & Reproducible Research
13 Questions
2 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What are some examples of new data sources mentioned in the context of big data in social sciences?

  • Historical documents and census data
  • Social media data and GIS data (correct)
  • Television ratings and book sales
  • Weather reports and personal emails
  • Why is it important to use comments in code for reproducible research?

  • They allow for faster computation of results
  • They can help identify bugs automatically
  • They help other programmers understand how the code functions (correct)
  • They improve the performance of the code
  • What is the recommended naming convention for object names in programming mentioned in the content?

  • Pascalcase
  • kebab-case
  • camelCase
  • snake_case (correct)
  • What is an important tip regarding mathematical operators in code?

    <p>Put spaces on either side of most mathematical operators</p> Signup and view all the answers

    What has changed regarding who analyzes data in the modern world?

    <p>More people outside of traditional statistics have begun to analyze data</p> Signup and view all the answers

    What is the primary purpose of setting a working directory in R using the setwd() function?

    <p>To specify where R should look for files and save outputs</p> Signup and view all the answers

    Which statement correctly describes a .RProj file?

    <p>It bundles data and code for reproducible research.</p> Signup and view all the answers

    What is the function of getwd() in R?

    <p>To display the current working directory</p> Signup and view all the answers

    What is Quarto primarily used for in R?

    <p>To create dynamic documents combining code and text</p> Signup and view all the answers

    What does the Tidyverse consist of?

    <p>A collection of R packages focused on data science</p> Signup and view all the answers

    How does using relative paths after setting the working directory benefit R coding?

    <p>It simplifies file operations by avoiding long file paths.</p> Signup and view all the answers

    What type of programming does Quarto utilize?

    <p>Literate programming</p> Signup and view all the answers

    What is a key feature of reproducible research mentioned in the content?

    <p>The research can be replicated using the provided code and data.</p> Signup and view all the answers

    Study Notes

    Big Data in Social Sciences

    • The world is surrounded by data.
    • Social media data, GIS data, economic data, military data, and data from randomized experiments/surveys are new data sources that have increased significantly in recent years.
    • New substantive ideas and data analysis tools are required to work with these new data sources.
    • The shift to new data has led to everyone analyzing data, not just statisticians, due to advancements like the internet and computing revolution.
    • Quantitative reasoning is essential for analyzing, interpreting, describing, and evaluating data to make good decisions in society and at work.

    Writing Code for Reproducible Research

    • Comments should explain why the code does something, not how or what.
    • Comments should be updated when the code changes.
    • Object names must start with a letter and can only contain letters, numbers, underscores, and spaces.
    • Different naming conventions exist: snake_case (recommended by the professor), camelCase, PascalCase, and kebab-case.
    • Place spaces on either side of mathematical operators (except for ^) to improve code readability and conciseness.
    • Section code with comments (e.g., "#load data", "#plot data") as the script grows longer.

    Reproducible Research

    • Reproducible research can be exactly redone given the materials used.
    • Another researcher should be able to reproduce results with the same code, data, and environment.
    • Code, dataset, and environment must be released.
    • Document the workflow to answer questions about the original dataset, data transformations, analysis done, and how the paper was built.

    R Projects

    • An R project bundles work in a portable, self-contained folder containing all relevant data and code.
    • setwd() sets the working directory, which is the folder R reads and saves files from by default.
    • A project is a working directory designated with a .RProj file.
    • When opening a project, the working directory automatically sets to the directory containing the .RProj file.

    Quarto/R Markdown

    • Quarto integrates code and natural language in "literate programming."
    • It is the successor of R Markdown, which allowed including R code chunks.
    • Quarto is a markup language similar to HTML or LaTeX.
    • It creates live documents where code executes and forms part of the document.
    • It allows compilation into HTML, PDFs, but this can take time as the code needs to run.

    Tidyverse

    • The Tidyverse is a collection of R packages designed for data science.

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Related Documents

    Description

    Explore the transformative impact of big data on social sciences and the importance of reproducible research practices. Discover how new data sources and quantitative reasoning are vital for effective analysis. This quiz covers essential coding practices for maintaining reproducibility in research projects.

    More Like This

    IBM's Social Pulse
    23 questions

    IBM's Social Pulse

    LavishConnemara avatar
    LavishConnemara
    Digital Marketing Trends Quiz
    10 questions
    Introduction to Big Data
    16 questions

    Introduction to Big Data

    EnthralledSard7619 avatar
    EnthralledSard7619
    Use Quizgecko on...
    Browser
    Browser