<- linear_reg() |>
m_ht_wt set_engine("lm") |>
fit(Height_in ~ Width_in, data = pp)
08-effective-communication
Effective Communication
Q&A
Q: for the last part of lecture 07, I tried glance(m_ht_wt) but it didn’t work because m_ht_wt doesn’t exist. Is “m_ht_wt” supposed be a model?
A: Yup, this model was the height by weight model:
Q: I was not too sure what was going on when talking about the relationship between painting height and school.
A: I don’t think you were the only one confused! Briefly here (and I’m happy to chat more before/after class and in OH), we were looking to determine/quantify the relationship between the size (height) of a painting and the school from which the painting originated. This was an example of having more than two categories for a categorical (factor) predictor. The important points were undersatnding that each level is compared to the baseline and the linear model that results from multiple categories. Part 4 of the lab gets into this a bit more too. Definitely follow up if you’re unsure after doing that part of the lab!
Q: How do you calculate the linear regression model when you have non-numeric values? For example, on lab 04, when it asks to calculate the linear regression model by gender, the gender appears only as male and female. Suppose male is 1 and female is 0 (interpreted by the function), then male linear regression model is y =ax + 1?
A: Close! the “1” would be plugged in as the value of x (in what you suggested)m not for the intercept. So the function would be \(y=\beta_1*1 + \beta_0\)
Course Announcements
- Lab04 due Friday
- HW02 due Monday
. . .
- Practice Midterms Now Available
- answers posted next week
- Midterm Exam
- will cover material through “Multiple Linear Regression”
- will be released/posted next Friday after lab
- will be due Monday Nov 6th at 11:59 PM
- will be an Rmd document and submitted via GitHub (like everything so far)
- will be completed individually (open Notes; open Internet)
. . .
. . .
Agenda
- Communicating for your audience
- Oral Communication
- Written Communication
- Visual Communication
Suggested Reading
- Bookdown Section 2.6 R Code Chunks & inline R code
- Bookdown Chapter 3: Documents
- Will Chase’s rstudio::conf2020 talk: “The Glamour of Graphics” [slides] [video]
Consider your audience
What does this mean?
❓ What does it mean to “consider your audience?”
. . .
Simply: You do the work so they don’t have to.
. . .
…also the aesthetic-usability effect exists.
What’s the right level?
General Audience
✔ background
🚫 limit technical details
🎉 emphasize take-home
Technical Audience
⬇ limit background
💻 all-the-details
🎉 emphasize take-home
Considerations
- Platform: written? oral?
. . .
- Setting: informal? formal?
. . .
- Timing: never go over your time limit!
Storytelling
- Stories have a beginning, a middle, and an end.
. . .
- Stories do not need every detail of what you’ve tried
. . .
- Reports and presentations should tell a story
- Planning out your report/presentation can help
. . .
- Hold the audience’s attention with what needs to be said; do so effectively
- Tell your audience why they should care; why it matters
- You should explain your choices and the “why”
Choose informative titles
On presentations: Balance b/w short and informative (goal: concise)
. . .
Avoid: “Analyzing NHANES”
Better: “Data from the NHANES study shows that diet is related to overall health”
. . .
On visualizations: emphasize the take-home! (what’s learned or what action to take)
. . .
Avoid: “Boxplot of gender”
Better: “Twice as many females as males included for analysis”
. . .
Avoid: “Tickets vs. Time”
Better: “Staff unable to respond to incoming tickets; need to hire 2 FTEs”
Effective Oral Communication
Brainstorm: Advice You’ve Been Given?
Student responses
Advice you've received |
---|
consider your audience |
speak organizedly and logically |
A narrative format is preferable to an enumeration or a nonlinear presentation such as what would arise from reading off an infographic, for example. |
Be clear and direct! |
Don't say filler words like "uhm" "like". Take a pause instead |
Consciously speak slowly than you normally do (for fast talkers) |
speak confidently and know material well enough to sound natural/not just memorize material |
interact with the audience |
Talk slowly and clearly |
Put yourself in the shoes of your audience |
Speak clearly at a good pace (not too fast or slow), make eye contact and engage with your audience |
Enunciation, proper volume, etc. |
I tend to speak in long sentences which can confuse the audience. |
Talk slower and clearer. Enunciation. Eye contact while talking. Avoid filler words. |
speak clearly, slow down if you need to, don't just read off slides when presenting |
be sure to point out areas of interest on your plots and explain them |
Use simply words if possible |
Speaking slowly at someone |
Don't assume the audience know the same thing (like the research background or the research design) as you do. Another thing is: try to make sentence as simple as possible. |
Take moments to pause in between you sentences if you get lost. |
Speak slowly and clearly |
Keep it engaging, involve audience participation, make eye contact, be confident |
Talk clearly and stick with the theme |
Cater to your audience. Be conscious of what they know and don't know. |
Use appropriate font. |
Speak clearly and slow down when you're picking up a fast pace. |
Presentations are for listening
- Advantage: words to explain out loud what you’re showing
. . .
- You are presenting for the person in the back of the room.
. . .
To accomplish:
don’t read directly off slides
repetition is ok: tell what you’re going to tell them, tell them, tell them what you told them
use animation to build your story (not to distract)
introduce your axes
text/labels larger
watch your speech speed
practice!
For Example: A Happy Ending for (almost) everyone in Little Red Riding Hood
- Red Riding Hood (RRH) has to walk 0.54 mi from Point A (home) to Point B (Grandma’s)
- RRH meets Wolf who (1) runs ahead to Grandma’s, (2) eats her, and (3) dresses in her clothes
- RRH arrives at Grandmas at 2PM, asks her three questions
- Identified problem: after third question, Wolf eats RRH
- Solution: vendor (Woodsman) employs tool (ax)
- Expected outcome: Grandma and RRH alive, wolf is not
Little Red Riding Hood
Effective Written Communication
Brainstorm: Advice You’ve Been Given?
Student responses
Advice you've received |
---|
When sending a status update on a project to people in my team, I often had a habit of over explaining things such as specific terms or what a specific p-value indicates, etc. and it was redundant to my team, who all knew what these terms mean and how they are defined. On the flip side, during a meeting with non-technical people, a lot of my team's work didn't make sense to some people in the meeting and they requested info in "layman terms". My mentor advised me to not over-explain terms in depth to technical people, but keep things simple, clear and concise to those without a technical background. |
NA |
Be as concise as possible while getting your point across |
no need to write full sentences for bullet points |
write in a concise manner, don’t use big words unless it’s relevant |
keep things succinct and write in a neutral tone |
Bold or italicize important ideas/ key words in long writing |
Main idea sentence in the beginning of your text (report, essay, email). |
Refrain from using the first person. Talk in the past-tense |
Use grammarly |
Watch repetition of certain words. Occasionally change the structure of sentences. Know your audience. |
Dont be too repetitive and Don’t have run on long sentences and get caught up in the details too much - I do that a lot :// |
Avoid ambiguity, have someone else proof read to double check what you've written, try not to make your sentences too wordy. |
Write for your audience, avoid overuse of jargon and if necessary be sure to define the terms in a way appropriate for how you’re actually using them. |
Be clear and concise with the points you're trying to make and don't lose them with sentences that run on for too long |
Be concise and use as few words to effectively get point across. Don't go off on tangents. |
Organize using subheadings, highlight main points using bold or colors if appropriate, vary sentence structure |
make your sentences simpler to understand |
When giving a status report to a technical team, no need to over-explain terms. It is a lot of times effective to make a concise bullet point list such as p value= x, correlation coefficinet = y, instead of overexplaining what each value means b/c a technical team probably would know the signifance anyways |
Write in words that the readers will understand, and do not assume that the readers will know what you mean. |
use an outline to help organize the order of your paper. it helps you figure out where to place images, plots, and text |
Organize arguments, don't be overly repetitive |
Benefits of written communciation
Your audience has time to process…but the explanation has to be there!
. . .
Visually: more on a single visualization
. . .
Yes, often there are different visualizations for reports/papers than for presentations/lectures.
When you have time to digest (read)
. . .
❓ What makes this an effective visualization for a written communication?”
Source: Storytelling wtih data by cole nussbaumer knaflic
Written Explanations
- Visualizations should be explained/interpreted
- Models should be explained
- should be clear what question is being answered
- what conclusions is being drawn
- and what numbers were used to draw that conclusion
Data Science Reports in .Rmd
- As concise as possible
- Necessary details (for your audience); nothing more
- Be sure that the knit output contains what you intended (plots displayed; headers etc.)
- …and does NOT display stuff that doesn’t need to be there (messages/warnings suppressed, brainstorming, etc.)
- Typical Sections: Introduction/Background, Setup, Data, Analysis, Conclusion, References
Controlling HTML document settings
- Table of Contents
---
title: "Document Title"
output:
html_document:
toc: true
toc_float: true
---
. . .
- Theme
---
title: "Document Title"
output:
html_document:
theme: united
highlight: tango
---
. . .
- Figure Options
---
title: "Document Title"
output:
html_document:
fig_width: 7
fig_height: 6
fig_caption: true
---
. . .
- Code Folding
---
title: "Document Title"
output:
html_document:
code_folding: hide
---
Controlling code chunk output
- Specified in the curly braces, separated by commas
. . .
eval
: whether to execute the code chunkecho
: whether to include the code in the outputwarning
,message
, anderror
: whether to show warnings, messages, or errors in the knit documentfig.width
andfig.height
: control the width/height of plots
. . .
- Controlling for the whole document:
knitr::opts_chunk$set(fig.width = 8, collapse = TRUE)
Editing & Proofreading
- Did you end up telling a story?
- Things missing?
- Things to delete?
. . .
- Do not fall in love with your words/code/plots
. . .
- Do spell check
- Do read it over before sending/presenting/submitting
Aside: Citing Sources
When are citations needed?
. . .
“We will be doing our analysis using two different data sets created by two different groups: Donohue and Mustard + Lott, or simply Lott”
. . .
“What turned from the idea of carrying firearms to protect oneself from enemies such as the British monarchy and the unknown frontier of North America has now become a nationwide issue.”
. . .
“Right to Carry Laws refer to laws that specify how citizens are allowed to carry concealed handguns when they’re away from home without a permit”
. . .
“In this case study, we are examining the relationship between unemployment rate, poverty rate, police staffing, and violent crime rate.”
. . .
“In the United States, the second amendment permits the right to bear arms, and this law has not been changed since its creation in 1791.”
. . .
“The Right to Carry Laws (RTC) is defined as”a law that specifies if and how citizens are allowed to have a firearm on their person or nearby in public.””
. . .
Reminder: You do NOT get docked points for citing others’ work. You can be at risk of AI Violation if you don’t. When in doubt, give credit.
Footnotes in .Rmd
How to specify a footnote in text:
Here is some body text.[^1]
How to include the footnote’s reference:
[^1]: This footnote will appear at the bottom of the page.
Note: .bib files can be included with BibTeX references using the bibliography
parameter in your YAML
Effective Visual Communication
Brainstorm: Advice You’ve Been Given?
Student Responses
Advice you've received |
---|
Don’t make slides overly colorful |
no borders on plots, graphs.don't write the whole info on one slide. take advantage of white space |
use images to help audience understand |
Highlight important points in visualization. |
don’t write everything on slides, just main points, try to use pictures that model/reflect/support talking points |
use a legend for graphs |
make sure your plot is relevant to the point you are trying to make |
reduce the number of words on the slide |
It should be easy to understand/digest relatively quickly, only put absolutely necessary/relevant things |
Pick a font and size for body+headings and commit to it |
Try to keep the design minimalistic and aesthetic, no cognitive overload that way. |
Title your plots & graphs |
Images/visuals should help strengthen your presentation/story, not distracting from it |
Use lots of pictures! |
It's better to have meaningful and intuitive color selection. |
Specific graphs are more beneficial to a technical audience, while others are better for a non-technical one. My coworkers like graphs such as boxplots, but when presenting to partners, I have found that they prefer more intuitive/popular graphs like histograms or line plots. |
Complementary colors, appropriate graphs for the type of information you have and want to get across, neat and not cluttered |
Concise and clear, use colors and space effectively |
Use color responsibly in graphs/tables, make text large enough for everyone in the room to see, don't overload slides with information |
dont put too much words |
Don’t put too many animations (if any) |
Less is more. Too much can distract and detract from the main point |
good contrast color between background and text |
make clear visual guide, don’t make it too complicated |
Avoid neon colors |
Keep accessibility in mind when presenting visuals. (e.g. using texture instead of color, image descriptions, etc.) |
Make presentations look cleaner. Seems like you know what youre talking about. |
The Glamour of Graphics
- builds on top of the grammar (components) of a graphic
- considerations for the design of a graphic
- color, typography, layout
- going from accurate to 😍effective
These ideas and slides are all modified from Will Chase’s rstudio::conf2020 slides/talk
Left-align titles at top-left
😬 Accurate
ggplot(penguins, aes(x = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1))
😍 Effective
ggplot(penguins, aes(x = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1),
plot.title.position = "plot")
Avoid head-tilting
😬 Accurate
ggplot(penguins, aes(x = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1),
plot.title.position = "plot")
😍 Effective
ggplot(penguins, aes(y = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme(plot.title.position = "plot")
Borders & Backgrounds: 👎
😬 Accurate
ggplot(penguins, aes(y = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_bw() +
theme(plot.title.position = "plot")
😍 Effective
ggplot(penguins, aes(y = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_minimal() +
theme(plot.title.position = "plot")
Organize & Remove/Lighten as much as possible
😬 Accurate
ggplot(penguins, aes(y = species, fill = species)) +
geom_bar() +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_minimal() +
theme(plot.title.position = "plot")
😍 Effective
ggplot(penguins, aes(y = fct_rev(fct_infreq(species)), fill = species)) +
geom_bar() +
geom_text(stat='count', aes(label=..count..), hjust = 1.5, color = "white", size = 6) +
scale_x_continuous(expand = c(0, 0)) +
scale_fill_manual(values = c("#454545", rep("#adadad", 2))) +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_minimal(base_size = 18) +
theme(axis.text.x = element_blank(),
plot.title.position = "plot",
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
axis.title = element_blank())
Legends suck
😬 Accurate
ggplot(penguins, aes(y = fct_rev(fct_infreq(species)), fill = species)) +
geom_bar() +
geom_text(stat='count', aes(label=..count..), hjust = 1.5, color = "white", size = 6) +
scale_x_continuous(expand = c(0, 0)) +
scale_fill_manual(values = c("#454545", rep("#adadad", 2))) +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_minimal(base_size = 18) +
theme(axis.text.x = element_blank(),
plot.title.position = "plot",
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
axis.title = element_blank())
😍 Effective
ggplot(penguins, aes(y = fct_rev(fct_infreq(species)), fill = species)) +
geom_bar() +
geom_text(stat='count', aes(label=..count..), hjust = 1.5, color = "white", size = 7) +
scale_x_continuous(expand = c(0, 0)) +
scale_fill_manual(values = c("#454545", rep("#adadad", 2))) +
labs(title = "Adelie Penguins are the most common in Antarctica",
subtitle = "Frequency of each penguin species studied near Palmer Station, Antarctica") +
theme_minimal(base_size = 20) +
theme(axis.text.x = element_blank(),
plot.title.position = "plot",
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
axis.title = element_blank(),
legend.position = "none")
Additional Guidance
- White space is like garlic - take the amount you need and triple it
- Fonts Matter
- Use Color Effectively