Here is my Midterm Report for MTH 231!
The MidtermReportCode.R file is the code used to produce the graphs shown in the report, while the pdf file shows the result of the same code processed through the console. Therefore, the pdf has information that’s not in the report or the .R file, such as the structure of video.data and of various variables.
Thank you for reading!
Midterm Report Code
There wasn’t an actual class session this week. Instead, there was a recorded lesson about hypothesis testing.
I began experimenting with the UC Berkeley Video Game Survey data and have found some interesting observations. There are less than 100 observations with most of them not liking or playing video games, causing some of the observations to have a value of 99 in some of the variables, meaning that no data was collected on that variable from the observation. In the additional data, the value NA is used instead and I need to figure out how to combine those two datasets together.
I have also experimented with making graphs with Exploratory Data Analysis through R. While I have made some graphs, I’m not sure yet how helpful some of them will be. Formatting is also an issue where it’s difficult to combine certain graphs sometimes. The value 99 is also a problem because I’m not sure if it should be removed or not.
For this and next week, I’ll continue to experiment with the dataset and learn how to use ggplot2 to make better plots in R.
Thank you for reading!
Finally finishing all the required readings for the first half of the semester, I now need to think about a possible dataset to use for the other half.
I’m fascinated by Psychology and would love to work on any dataset involving it if so. I was also exploring into the UC Berkeley STAT LABS: Data website (https://www.stat.berkeley.edu/users/statlabs/labs.html) and found that the Video Game Survey data to be interesting in that there are several variables involved, which could raise a multitude of questions and many possible associations to be found. However, I haven’t looked too much into the dataset or other resources, so that will be the task for this week.
Wish me luck and thank you for reading!
For this week, I’ll be reading Chapter 7 of the “Exploratory Data Analysis with R” book. This will complete the 5th and final item on the First Half Semester checklist.
Again, I haven’t put much thought into finding a dataset because I wanted to focus on reading the recommended parts of the book first. I might read more of the book in the future if I need more information for data analysis and have time to do so.
Reading is power!
For this week, I’ll be reading Chapter 6 of the “Exploratory Data Analysis with R” book. This will complete the 4th item on the First Half Semester checklist.
I have not put too much thought into the dataset I want to use for the rest of the semester, but I want the dataset to be simple enough to understand, but complex enough to pose a challenge.
Thank you for reading!
This week, I’ll be reading Chapter 5 of the “Exploratory Data Analysis with R” book. This will complete the 3rd item on the First Half Semester checklist.
I’ve been thinking about what data I want to explore throughout the semester. Although I haven’t researched potential datasets yet, I know I want to do one involving psychology. I will look into datasets later on this or next month.
Thanks for reading!
Due to COVID-19, the class structure has changed. Since the class is unable to find data provided by the school such that everyone can experiment on it as a class, the first half of the semester is about reading the required textbook in order to properly learn how to analyze data with R.
For this week, I’ll read Chapters 1 through 4 of “Exploratory Data Analysis with R”, which completes 2 of the 5 sections of reading required.
Thanks for reading and I’ll post again soon!
School just started on September 2nd and I’m excited for what this class will teach me!!!
Today’s class was about getting set up and prepared for the course, which involved going over the syllabus and how to navigate Mr. Davis’s website.
This week, I’ll download Roger Peng’s “Exploratory Data Analysis with R“, which is available on leanpub.com for free, create this beautiful website with this blog post published, and download R and RStudio.
I have little experience in R, so I’m fascinated by the prospect of learning more!
Thanks for reading and I will post again next week!