Calling Bullshit DCS 105 Bates College RByte Worksheets
Author(s): Carrie Diaz Eaton1, Sadie Kriegler
Unity College
276 total view(s), 241 download(s)
- DCS 105 RBYTE COVID Cases In Maine .docx(DOCX | 8 KB)
- DCS 105 RBYTE Intermediate R Skills 6W.docx(DOCX | 7 KB)
- DCS 105 RBYTE Pennies to the Moon 2W.docx(DOCX | 35 KB)
- DCS 105 RBYTE Pennies to the Moon 3M.docx(DOCX | 8 KB)
- DCS 105 RBYTE Pennies to the Moon 7M.docx(DOCX | 8 KB)
- DCS 105 RBYTE Random Number Generation Skills 8W.docx(DOCX | 8 KB)
- DCS 105 RBYTE COVID Cases In Maine CoLab Worksheet
- DCS 105 RBYTE Pennies to the Moon 2 CoLab Worksheet
- DCS 105 RBYTE Intermediate R Skills CoLab Worksheet
- DCS 105 RBYTE Random Number Generation CoLab Worksheet
- License terms
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:
-
Objective:
- Clear goals are set for each worksheet to guide your learning process.
-
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.
- Review:
-
Reflect:
- Reflect on observations and learning from the exercises and exploration. Consider the implications and applications of the concepts in real-world scenarios.
-
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.
Cite this work
Researchers should cite this work as follows:
- Diaz Eaton, C., Kriegler, S. (2024). Calling Bullshit DCS 105 Bates College RByte Worksheets. Calling Bull - a resource sharing and teaching community, QUBES Educational Resources. doi:10.25334/C7B6-2G08