ISBN:9781319339784
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UNIT 1: INTRODUCTION
Chapter 1: Numbers Do Not Speak for Themselves
Case Study: The Challenger space shuttle
- For Discussion: The Challenger memo
Data reporting involves argument
Data-based arguments depend on purpose, audience, and credibility
Numbers can be manipulated — just like words
Data can be qualitative as well as quantitative
Callout: Is the word data singular or plural?
Is this book for me?
Summary
- Exercise 1.1: Reframing statistics
Chapter 2: Telling a Story with Quantitative Data
Data visualizations and words work together to tell a story
- Exercise 2.1: Telling stories about data
Not all stories are equally credible and ethical
- Avoid breaking common conventions for reporting data
- Do not make small differences seem large
- For Discussion: Adjusted y-axis
- Include important context relevant to understanding the data
- Carefully word claims to avoid exaggeration
Summary
- Exercise 2.2: Rating credibility
UNIT 2: WORKING WITH DATA STORIES
Chapter 3: Visualizing Your Data Story: Part I
The most common visualizations (and the stories they support)
- Callout: Chart, graph, figure? What’s the difference?
Bar graphs
- Line graphs
- Pie graphs
- Tables
The case against pie graphs: Why they should be used sparingly
- For Discussion: Pie graphs
Use captions and labels to complete and reinforce your story
- A checklist for figure and table captions
- Exercise 3.1: Analyzing captions
- Exercise 3.2: Examining visualizations in research articles
Generative AI and data visualization
Summary
- Exercise 3.3: Creating visualizations
Chapter 4: Reinforcing Your Visualization’s Story
Sort to emphasize your story
Group data to foreground one story over another
Reduce non-data ink
Minimize eye movement
Use contrast to emphasize your story
Be consistent and credible in how you display numbers
Summary
- Exercise 4.1: Examining visualizations in research articles
- Exercise 4.2: Revising your data visualizations
- Exercise 4.3: Grouping and arranging data in data visualizations
Chapter 5: Using Basic Math to Shape Your Story
Summarize data to concisely communicate a story
- Exercise 5.1: Summarizing and averaging data
Use weighted data to shape your story
- Weighted data are useful in evaluations
- Weighted data are useful for Likert-scale data
Combine data with other sources to give context
- Exercise 5.2: Combining different types of data
- Case Study: Satisfaction with democracy in the United States, 1997 versus 2022
- For Discussion: Raw numbers versus percentages
- For Discussion: Shaping the story with calculations
Summary
- Exercise 5.3: Turning complex data into a clear story
Chapter 6: Working with Qualitative Data
- Callout: Qualitative and quantitative are not mutually exclusive
Use qualitative data to describe
- For Discussion: Quotations as “data”
Use qualitative data to categorize
Use qualitative data to evaluate
- For Discussion: Qualitative data across disciplines
Report qualitative data ethically
- Exercise 6.1: Ethical interpretation of quotes
Summary
- Exercise 6.2: Analyze a report with qualitative data
UNIT 3: WRITING THE FORMAL DATA REPORT
Chapter 7: Writing a Formal Data Report (IMRD)
IMRD stands for Introduction, Method, Results, and Discussion
IMRD reports have an abstract or executive summary
IMRD sections aid readers by being highly predictable
- Exercise 7.1: Identifying IMRD information
IMRD reports support non-linear reading
- Exercise 7.2: How do you read an IMRD report?
IMRD organization can vary
- Exercise 7.3: Analyze IMRD sections in a sample report
Summary
- Exercise 7.4: Research Posters
- Exercise 7.5: Analysis of good and bad reports
Chapter 8: Writing the Results Section
Write your data story in paragraphs
- For Discussion: How does the paragraph change your understanding?
- Callout: For the mathematically minded...
- Exercise 8.1: Interpreting data
Weave multiple data stories together
Use subheadings to organize into skimmable chunks
A sample Results section: improving instructor ethos through document design
Summary
- Exercise 8.2: Annotating results
Chapter 9: Writing about Methods
Methods readers lie at two extremes of care in reading
Methods are typically organized with subheadings
Methods sections justify choices
- For Discussion: Justifying methodological choices
Methods sections favor past tense and passive voice
- Exercise 9.1: Choosing active or passive voice
Methods themselves are sometimes a major research contribution
Summary
- Exercise 9.2: Comparing methods sections
Chapter 10: Introducing Research Studies
Introductions convey the context and value of your work
Researchers follow a “formula” for introducing research
- Exercise 10.1: Annotating introductions
Introductions can be short and sweet
- For Discussion: Short and sweet introductions
Introductions can be long and encompass multiple sections
Summary
- Exercise 10.2: Annotating Introductions
Chapter 11: Discussions, Conclusions, and Recommendations
IMRD reports conclude by moving from specific to general
- Exercise 11.1: Annotating Discussion sections
What goes in the Results versus the Discussion sections?
- Callout: The combined Results and Discussion
- Exercise 11.2: Choosing Results or Discussion
What goes in the Discussion versus the Conclusion?
A Recommendations section often concludes business and professional reports
Summary
- Exercise 11.3: Annotating concluding sections
Chapter 12: Front Matter: Titles, Abstracts, and Executive Summaries
Titles should clearly and precisely state the main focus
Abstracts and executive summaries are reports in miniature
- Callout: A note of caution
The traditional academic abstract is a single paragraph
The structured academic abstract has labeled sections
An IMRD executive summary is typically one page
The recommendations-first executive summary
Avoid common problems with executive summaries
Summary
- Exercise 12.1: Rating abstracts
APPENDICES
Appendix A: Two Sample IMRD Reports
Version 1: Effect of Verbal Commands in Instructions for Assembly of a Lego Vehicle
Version 2: Effect of Verbal Commands in Instructions for Assembly of a Lego Vehicle