PSDA PROJECT REFLECTION
Reflection PSDA Hazeeq –
It is all started when lecturer gave us the project assessment at the beginning of the semester. The project task need to be done by group and the main objective is kind of a statistic data collection and the way we interpret the data in a better form instead of showing the data collection using Microsoft Excel only which is in a “long black and white table-form” data. I and my group members decided to work on “Evening Activities among UTM students”. But then we change to be more sports-focused as majority agree with this.
Next, things that we got started first is data collection. Nowadays, many people are prefer to fill the questionnaire through online survey. In my opinion, we better use Google Form or any online survey platform because we can save many time by not spending on giving the paper to people and wait them to fill it first. Online survey also can save the use of paper as paper is made from tree. I and my team worked together to create and group the suitable questions according to the topic “Levels of Measurement “and use the appropriate language to make the people feel comfortable and being nice to fill-in our online survey. After making the questionnaire, then we ask the lecturer that our questions suits in our survey or not. What I have learnt is one type of question we can creatively transform it to become other different type of “Level of Measurement” scale. I am interested with the way we manipulate the questions that can produced unique data.
After a few weeks, we got the data in the Google form online survey. I am one of the team member who has made the online survey and I can see the system interpret the data automatically in the “Response” part. But, the data displayed are not customizable and the graph types are not as much as we need such as Box-plot, Steam and Leaf Scatter Plot and many others. So we download the data from Google Form in form of .xlsx files or also known as “Excel”. So then we can import Excel file into R studio that our lecturer recommend for our group to use it as it can produce many styles of graph and the way we interpret the data. For me, the better styles of graph the better conclusion that we can make and people would be easily to understand on what data collection that we are working at to present the statistical data in any kind of purposes.
Next, we move to the process on how to interpret the data using R studio. R studio is a type of free and application and a command-line programming language. Literally, we better learn how to use R studio through tutorial slide that given by our lecturer rather than watching tutorial on YouTube because there are some conflicts such as when on YouTube tutorial it can 100% work to interpret the data but our group can’t. So this is quite frustrating as most of us loves to learn based on visually instead or reading slide-by-slide. So to code the program is such a simple way the only we need is not to forgot the key-word of codes like plot, hist, barplot and many others. We interested that we can also use the color by typing “col= (desired color)” instead of typing the color code in numeric that are way too complicated to interpret the data and make it colorful.
The video making part was very simple as we divide the task into 4 people. I was task with the methodology part as I am the one who can remember the parts-flow in our project and understand the R studio parts. This video making part is happened when we are in quarantined at home. So we talk infront of camera about the task that we have divided for each of us. After that one of our group volunteered to compile the video presentation and to make presentation more attractive.
Lastly, I am so excited experiencing in the making of this statistical project assessment. From this, I have learned so much and make me more matured by the time as we need to be nice in our group members whenever I have a problem or not in a group. Now I am able to make a Google form by myself and making the appropriate question using “measuring scale” that will produce desired data at the end, I also learned to import and interpret data from excel to R studio with colorful and attractive graphs using the useful tools in the application. Hopefully, after this I can use this application if I involve in other statistical work team which are in university or at my job places in the future.