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Calling Bullshit DCS 105 Bates College RByte Worksheets

Author(s): Carrie Diaz Eaton1, Sadie Kriegler

Unity College

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Description

Objective:

RBYTE worksheets are designed to enhance your students understanding and skills in various aspects of data analysis using R through CoLab. These worksheets were designed to formalize in-class coding activities and provides students a reference to look back on for future projects and research. Each worksheet focuses on a specific topic, aiming to deepen your students knowledge through practical exercises and reflections.

Structure:

  1. Objective:

    • Clear goals are set for each worksheet to guide your learning process.
  2. Directions:

    • Review:
      • Study the provided code snippets and explanations related to the topic.
    • Execute:
      • Run the code in your R environment and observe the outcomes.
    • Exercises:
      • Complete the exercises to apply what you've learned.
    • Play and Explore:
      • Engage with additional questions to challenge yourself further.
  3. Reflect:

    • Reflect on observations and learning from the exercises and exploration. Consider the implications and applications of the concepts in real-world scenarios.
  4. Move On:

    • Apply the skills acquired to more complex case studies or projects. Each worksheet typically links to a relevant case study for practical application.

Key Learning Areas:

  • Distributions:

    • Understand different statistical distributions and their properties.
  • Sampling:

    • Learn about sampling techniques and the importance of sample size.
  • Summary Statistics:

    • Calculate and interpret key summary statistics to describe datasets.
  • Data Visualization:

    • Create and interpret various types of data visualizations.
  • Modeling:

    • Build and evaluate statistical models to make predictions and inferences.
  • Random Number Generation:

    • Master techniques for generating random numbers and understand their use in simulations and modeling.

Activities:

  • Code Review:

    • Analyze and run provided code snippets to understand the practical implementation of concepts.
  • Exercises:

    • Engage in hands-on activities to apply concepts and solidify understanding.
  • Play and Explore:

    • Tackle additional questions to challenge knowledge and explore deeper insights.
  • Reflection:

    • Document your learnings and consider how these concepts apply to real-world data analysis.

RBYTE worksheets are crafted to provide a comprehensive and practical learning experience in R through CoLab. By following the structured activities and reflecting on learnings, students will build a strong foundation in data analysis, preparing them to tackle complex data projects with confidence.

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