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assessment.Rmd
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---
title: "Assessment"
---
```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
library(knitr)
library(tidyverse)
library(kableExtra)
opts_chunk$set(echo = FALSE)
```
```{r create-assessment}
assessment_df <- data.frame(
"assessment_task" = c("Reading Quizzes",
"Lab Exercises",
"Assignment 1",
"Mid-semester in-class exam",
"Assignment 2",
"Data Analysis Practical Exam",
"Project Submission"),
"value" = c("5%",
"5%",
"10%",
"20%",
"10%",
"20%",
"30%"),
"due_date" = c("Weeks 1-8",
"Each class period",
"Week 4 (9th April)",
"Week 6 (29th April)",
"Week 9 (20th May)",
"Week 11 (3rd June)",
"Week 11")
)
names(assessment_df) <- c("Assessment Task",
"Value",
"Due Date")
assessment_df %>%
kable(escape = FALSE,
align = c("l", "c", "l")) %>%
kable_styling(bootstrap_options = "striped",
fixed_thead = T) %>%
column_spec(1, width = "0.5cm") %>%
column_spec(2, width = "1cm") %>%
column_spec(3, width = "3cm")
```
## Assignments
Information to complete the assignments is below:
```{r assignments}
assignment_df <- data.frame(
Assignment = c(1,2),
`Due Date` = c(
"2020/04/09 at 5pm",
"2020/05/20 at 6pm"
),
Instructions = c(
"[here](assignments/assignment-1-instructions.html)",
"[here](assignments/assignment-2-instructions.html)"
),
Zipfile = c(
"[zip](assignments/mida-assignment-1.zip)",
"[zip](assignments/mida-assignment-2.zip)"
)
)
assignment_df %>%
kable(escape = FALSE,
align = c("l", "c", "l", "l")) %>%
kable_styling(bootstrap_options = "striped",
fixed_thead = T) %>%
column_spec(1, width = "0.5cm") %>%
column_spec(2, width = "1cm") %>%
column_spec(3, width = "1.5cm") %>%
column_spec(4, width = "1.5cm")
```
## Project
[Project instructions](project/project-instructions.html) and
[project groups](./groups.html). Please check the project groups
for any discrepancies.
- **Deadline 1 (13th May)**: Find team members, and potential topics to study (List of groups will be posted [here](./groups.html))
- **Deadline 2 (20th May)**: Team members and team name, data description.
- **Deadline 3 (29th May) **: Electronic copy of your data, and a page of data description, and cleaning done, or needing to be done.
- **Deadline 4 (5th June at midnight) **: Final version of story board uploaded.
-
- **Presentation in week 12**
There are several ways to do the storyboard:
- [flexdashboard](https://rmarkdown.rstudio.com/flexdashboard/) package, and there is an [example here](project/electricity-webstory.zip) that contains code for a complete dashboard
- A basic [shiny](https://shiny.rstudio.com/gallery/) app
- slides with the [xaringan](https://bookdown.org/yihui/rmarkdown/xaringan.html) package
- a [learnr](https://rstudio.github.io/learnr/index.html) tutorial, example project [here](project/pisa_au_app.zip).
Past Example projects from ETC1010:
- [Analysing Movie Data](https://ebsmonash.shinyapps.io/Thor/)
- [Instagram analysis](https://ebsmonash.shinyapps.io/Instagram/)
Examples from different web sites:
- [Blue Bikes Sharing in Boston](https://www.r-bloggers.com/blue-bikes-sharing-in-boston/)
- [What birds are observed near Radolfzell? Bird occurrence data in R](https://ropensci.org/blog/2018/08/21/birds-radolfzell/)
- [Who wrote the anti-Trump New York Times op-ed? Using tidytext to find document similarity](https://www.r-bloggers.com/who-wrote-the-anti-trump-new-york-times-op-ed-using-tidytext-to-find-document-similarity/)
- [Hotels vs Airbnb - Barcelona case study (proof of concept)](https://nycdatascience.com/blog/student-works/web-scraping/hotels-vs-airbnb-barcelona-case-study-proof-of-concept/)
- [Don't Worry: Google Only Checks Your Location Every 10 Minutes](http://www.sastibe.de/2018/04/don-t-worry-google-location/)
- [World Income, Inequality and Murder](http://staff.math.su.se/hoehle/blog/2018/07/09/gini.html)
- [Text analysis of Trump's tweets confirms he writes only the (angrier) Android half](http://varianceexplained.org/r/trump-tweets/)
- [What digits should you bet on in Super Bowl squares?](http://varianceexplained.org/r/super-bowl-squares/)
- [Exploring handwritten digit classification: a tidy analysis of the MNIST dataset](http://varianceexplained.org/r/digit-eda/)
- [Facebook advertising case-study: dog food and manhood](https://rickpackblog.wordpress.com/2018/08/20/facebook-advertising-case-study-dog-food-and-manhood/)
- [Analysis of Los Angeles Crime with R](https://datascienceplus.com/analysis-of-los-angeles-crime-with-r/)
- [Looking at Seinfeld dialogues using #tidytext](https://pradeepadhokshaja.wordpress.com/2018/08/06/looking-at-seinfeld-dialogues-using-tidytext/)
- [Twitter Coverage of the useR Conference 2018](https://github.com/neilfws/Twitter/blob/master/user2018/code/R/user2018.md)
## Practical Exam
The exam will be conducted in week 11. These are similar in presentation
to assignments but you have a shorter amount of time to complete them. You
will be given an Rmd file and some data. Inside the Rmd are questions
to help guide you through a data analysis.
You are expected to answer all of the questions inside the Rmd, and then submit
both the Rmd and compiled html file to ED within 24 hours. In previous versions
of the course the exam has taken students about 60 minutes to 90 minutes to complete.
### Practice exam
- [Practical Exam 2020 Semester 2, solution and student copy](exam/practical-exam-2019-s2.zip)
- [Practical Exam 2019 Semester 1 Rmd](exam/practical_exam_2019_S1.Rmd) and [ Practical Exam 2019 Semester 1 HTML](exam/practical_exam_2019_S1.html)
- [Practical Exam 2019 Semester 1 SOLUTION Rmd](exam/practical_exam_2019_S1_solution.Rmd) and rendered at [Practical Exam 2019 Semester 1 SOLUTION HTML](exam/practical_exam_2019_S1_solution.html)
## Midsemester test information
Past test:
- [Midterm 2019](exam/midterm2019.pdf) [(solution)](exam/midterm2019_solution.pdf)