Some writing tips for the final report

[joelostblom]

As you are finishing up your projects, I want to share a few writing tips to help you with the final report. Note that these are tips for how to write, you should not have to redo any analysis based on this, it is just advice on how to put together what you already have. Much of this is a reminder/clarification of what has been discussed in the course already.

Introduction

This usually starts as a general background section, stating what has been done in the field previously. Towards the end of the introduction, it is made clear what gap(s) there are in the previous literature and how these made you curious to ask the question in your current study and why this is important. This is the rationale/motivation and impact of your study and sets you up for stating you hypothesis in the next section.

Hypothesis

Based on the gap you identified in the literature, you have narrowed down one central question for your work (possibly with side questions, or smaller questions on the way).

Methods

In addition to describing the data (what was measured and how), also describe the model techniques you used for your analysis and how these work. Shorter justification and comparison to other techniques could go here, but is usually put in discussion if it is lengthy.

Results

Create a narrative from your findings. As you might have noticed from your literature readings, this section usually reads like a story to some extend. It should be easy for the reader to follow along, and the end of one paragraph should motivate what you did next and are describing in the next paragraph (e.g. after observing X, we proceed to explore Y to see if this relationship also extended to Z). Don't just describe the figures, describe your findings and use the figures as a visual aid for this narrative.

Discussion

How does your novel findings fit into the current literature and what future work might they motivate? You can also bring up caveats with your analysis methods here, alternate approaches, questions that you did not have time to explore or was outside the scope of this study, etc.

Conclusions

Summarize findings and reiterate impact.

Comment below if something is unclear!

[jeff-a-nguyen]

Hi Joel.

I wanted to have an interactive graph for our final project. But i noticed that when i used ggplotly there's a message on the knitted document saying

We recommend that you use the dev version of ggplot2 with ggplotly()

Install it with: devtools::install_github('hadley/ggplot2')

but when I use that code, R tells me it doesnt understand the devtools. I also used options(warn = -1)
but it didn't work

[lwjohnst86]

You need to install devtools install.packages('devtools'). The :: is telling R to use the install_github function from the devtools package.

[lwjohnst86]

Also, make sure to use output: html_document for your report, not html_notebook.

[jeff-a-nguyen]

Thanks Luke. I was able to get rid of that message, however, my ggplot function seems to also have changed and one of my graphs are producing a very strange image

[lwjohnst86]

hm. What was the image before? and what's the code above to create the plot?

[joelostblom]

It looks like it's making the smoothened lines and confidence intervals between the incorrect data points. Can you post the code from that code chunk?

…

On Dec 11, 2017 4:01 PM, "jeff-a-nguyen" ***@***.***> wrote: Thanks Luke. I was able to get rid of that message, however, my ggplot function seems to also have changed and one of my graphs are producing a very strange image [image: stange1] <https://user-images.githubusercontent.com/32882992/33853615-881556e4-de8c-11e7-9d25-9aacf465dcd7.png> — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#23 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AEWUuVJRcQIuE6ocYTYeT7kdW5Z5hZSlks5s_ZgogaJpZM4Q7I3v> .

[jeff-a-nguyen]

The image was a scatter plot of the log of predator mass vs the log of prey mass.

pred_prey_dataset %>%
ggplot(aes(x = log(Predator_mass), y = log(Prey_mass))) +
geom_point(bins = 50) +
geom_smooth(method = "glm", colour = "Red") +
xlab("Log (Predator Mass)")+
ylab("Log (Prey Mass)")+
jrc_theme()

There use tto be just a single red line for the glm

[jeff-a-nguyen]

i also changed the geom_point(bins = 50) -> geom_point()

[jeff-a-nguyen]

and its still like that strange image