MATH1062 Monday 1pm Semester 2
Assessments
For assessment dates, please stay up to date with EdStem announcments and Canvas announcments. For instructions regarding how assessments work for this unit of study, please refer to the unit of study outline here.
Important Links
Lab Clarifications
Please see the Google Doc here where I will place clarifications when needed on lab content. For example, if I am a bit unsure of what a particular answer is, I may add it to this Google Doc after the lab.
Muddy Cards
Muddy cards are a way for you to to share the topic or concept that you have found to be the most confusing from the last week (i.e. your muddiest point). I encourage you to fill out the optional survey here to provide me with your muddiest point. At the end of the week, I’ll review the most common points of confusion and provide further explanation through a Google Doc or my personal website/blog.
Student as Partners
As part of my commitment to being the best teacher that I can be, I will be conducting an optional mid-semester survey for you to provide feedback on how you are finding the tutorials and any ways I can improve my teaching style to support you.
Weekly Resources
Please check back here at the end of each week. I will upload some of the content that I worked on during the labs (for example, the Rmd files from the tutor coding demonstrations).
| Week | Files | Miscellaneous | Further Learning |
|---|---|---|---|
| 1 | No Lab | - | - |
| 2 | Introduction Week_2_Demo.Rmd | - | - |
| 3 | Worksheet_2.Rmd | - | RMarkdown Cheat Sheet RMarkdown YT Tutorial |
| 4 | Worksheet_3.Rmd | - | - |
| 5 | Normal Curve iPad Notes Worksheet_4.Rmd | - | See here for some normal curve slides I made previously. You may find them helpful, but some of the content goes beyond the requirements of this unit |
| 6 | SD Line Ipad Notes Worksheet_5.Rmd | - | - |
| 7 | iPad Notes Worksheet_6.Rmd | See the “muddy cards” section included above. | - |
| 8 | Box Model Empty Scaffold iPad Notes Worksheet_7.Rmd | - | - |
| 9 | Worksheet_8.Rmd | - | - |
| 10 (Lab Cancelled - Public Holiday) | Find the resources for the week 10 lab here! | - | - |
| 11 | Worksheet_10.Rmd | Please read the lab solutions that are uploaded to Canvas (when they are released)! | - |
| 12 | Worksheet_11.Rmd Whiteboard Hypotheses | - | - |
| 13 | Worksheet_12.Rmd | As promised, here is an app I made which can help you revise the box model! | Additional Revision: Box Model Proportion In-Depth Worked Solution |
Responding to Muddy Card Points
Hi All! Sorry it’s taken so long. I would have liked to have gotten to this earlier, but hopefully you still have some time to look at this before your exams. The uptake for Muddy Cards was quite small - we only had three responses over the four classes. I still am happy that we tried it this semester! Below I’ll respond to the muddiest points raised by your peers:
“Probability and combinations (solving by manually)”
I have made a blog post here that is similar, focusing on proability and permutations.
For more info about combintations, please refer to this Khan Academy lesson.
“Knowing the syntax of particular functions.” and “I dont really know how to code functions :(“
I will give an incredibly brief explanation below. I would suggest that before reading, you read this article here.
Functions are confusing, especially if you have never coded before this unit. Essentially, a function is a construct that allows you to write some code that you will repeatedly use in a project. Rather than having to type out the code over and over again, you can just call the function, and it will run the same code that you previously wrote inside your function.
You give a function a name, such as “popSD”. This identifier will remind you what this function does. To use the function, in your code, you write the identifier name, followed by brackets. For example: popSD().
But hang on! What population SD will we be finding? Currently, although we have allegedly created a function called popSD, this function can’t do anything interesting because we have yet to pass it data to process. Because of this, when defining a function, we can additionally include arguments. Arguments are values that the user will specify when calling a function, and the function will process these argument values. For example, in popSD, we would want to include an argument called data, which will represent that we want the user to pass in some data to the function.
Now, whenever the user wants to use the popSD function, they have to specify the function name, and in brackets, the data they want the popSD function to use. For example, if we had the values 1,2,3,4,5,6,7,8,9,10 and we wanted to find the population sd of these values, we would run, popSD(c(1,2,3,4,5,6,7,8,9,10)). Here, we can see that inside the brackets, we’ve specified what we want our data argument to store.
We’ve explained the high-level idea of our popSD function, but let’s actually define the function now. Below is the code for the popSD function (thanks to ChatGPT for generating it and saving me time):
popSD <- function(data) {
n <- length(data)
sqrt(sum((data - mean(data))^2) / n)
}
To run this function on the values 1,2,3,4,5,6,7,8,9,10 we can write:
our_data = c(1,2,3,4,5,6,7,8,9,10) popSD(our_data)