<!-- background-color: #006DAE --> <!-- class: middle center hide-slide-number --> <div class="shade_black" style="width:60%;right:0;bottom:0;padding:10px;border: dashed 4px white;margin: auto;"> <i class="fas fa-exclamation-circle"></i> These slides are viewed best by Chrome and occasionally need to be refreshed if elements did not load properly. See <a href=/>here for PDF <i class="fas fa-file-pdf"></i></a>. </div> <br> .white[Press the **right arrow** to progress to the next slide!] --- background-image: url(images/bg1.jpg) background-size: cover class: hide-slide-number split-70 title-slide count: false .column.shade_black[.content[ <br> # .monash-blue.outline-text[ETC5510: Introduction to Data Analysis] <h2 class="monash-blue2 outline-text" style="font-size: 30pt!important;">Week 11</h2> <br> <h2 style="font-weight:900!important;">About the Practical Exam and Project</h2> .bottom_abs.width100[ Lecturer: *Stuart Lee & Nicholas Tierney* Department of Econometrics and Business Statistics <span><i class="fas fa-envelope faa-float animated "></i></span> June 2020 <br> ] ]] <div class="column transition monash-m-new delay-1s" style="clip-path:url(#swipe__clip-path);"> <div class="background-image" style="background-image:url('images/large.png');background-position: center;background-size:cover;margin-left:3px;"> <svg class="clip-svg absolute"> <defs> <clipPath id="swipe__clip-path" clipPathUnits="objectBoundingBox"> <polygon points="0.5745 0, 0.5 0.33, 0.42 0, 0 0, 0 1, 0.27 1, 0.27 0.59, 0.37 1, 0.634 1, 0.736 0.59, 0.736 1, 1 1, 1 0, 0.5745 0" /> </clipPath> </defs> </svg> </div> </div> --- class: transition # Some notes on the practical exam --- # Practical exam - Practical exam is worth 20% of your final grade - There is another practical exam up on the assessment tab for you to access - Rmd and HTML files have to be submitted on ED, like you would on ED. - Practical exam opens at **6:00pm on Wednesday 3rd June** - Practical exam closes at **6:00pm on Thursday 4th June** --- # Practical Exam: How Marks are allocated - 37 marks total - 7 Marks for submitting an Rmd document that compiles to HTML with full answers - 30 Marks for correctly answering the questions in the Rmd (a mixture of short answer and code) --- # Expectations for independent work COVID19 has meant that we've had to change a lot about how we teach and do the course. We wanted to give you all a fair opportunity to complete the assignment in a timeline that suits you. So we have given you 24 hours to complete the exam. Please make sure that you don't cheat, and be fair. Penalties for cheating will carry the same academic penalty - Open book - Internet access - No discussion on anything related to this exercise with others, the work submitted should reflect entirely your own work. - Clarification questions can be asked between 6-8pm on Wednesday at the lecture zoom chat --- class: transition # The project: What and when do we present? --- # Due dates for the final project Friday 5th June by midnight: - Submit the full storyboard - This should be a zip file that contains everything I would need to re-run the project. Tuesday 9th June by 12pm - Final project video submitted - We are still finalising the best way to submit the final video, but it is looking likely that we will be asking you to submit the video via ED or moodle, More details to come. --- # The Project: More general questions > "Do we need to stick to 10 minutes" - Yes! You can do shorter if you like, but 5 - 10 minutes is a good aim - DO: Keep it 10 minutes or shorter - DO NOT: Have a video less than 5 minutes - DO NOT: Have a video more than 10 minutes. --- # The Project: More general questions > "Do we need to show the data cleaning?" - Yes, I should be able to see the data cleaning that you have done in the final submitted storyboard. - Your data cleaning should be in the final submitted project, and ideally should be visible in the Rmd - DO: Give a brief overview of the data cleaning required for your project in your presentation - DO NOT: Spend 4 minutes talking about data cleaning and 1 minute talking about what you learn from the dataset --- # The Project: More general questions > "Do we need to show the data cleaning?" - DO: Provide the code used to clean your data, potentially in a tab/page in your flexdashboard (but you don't need to walk through all of it) - DO: Provide the cleaning code in your final submission. - DO NOT: only say: "Data was cleaned and tidied for data analysis". --- # The Project: More general questions > "How/what do I reference?" - References should be in APA style, and could come from your favourite reference manager or using the features of Rmarkdown. - The most important items to reference are your data sets, the R packages used and any external publications/blog posts/websites that you accessed. - DO: Provide a tab/page in your dashboard that lists all your references - DO: Cite the R packages you have used, you can generally access these with `citation` function. See also `knitr::write_bib()`. - DO: Cite your data sources. --- # The Project: More general questions > "How many questions should we ask?" - About 3 main questions - roughly one per person in your group. You want to be able to present in ten minutes > "How will the project be marked?" - You will all mark the projects as you watch them, an ED quiz will be uploaded with the presentations. - Peer marks count for 30 marks - Instructor marks for the remaining marks --- # The Project: Sharing your project - You might be interested in sharing your project with others, if you want to share your final project, there's a pretty nifty solution with `netlify` that is free, Nick has made a short video on how to share your project there: https://www.youtube.com/watch?v=mAM7IYLbv30 - With your permission we could also host them on the EBS shiny server.