PSDA PROJECT 2

            In this report, a case study is carried out on an existing statistics of daily trending YouTube videos. From the pre-preparing process (proposal), to trial-and-error when doing analysis by choosing relevant listed variables, followed by the process of obtaining numerical analysis using R Studio, and finally completing the report and video presentations, I understand that these processes require efforts and time-planning discipline when a research-based study takes place.

               This dataset related to YouTube is chosen because it is indeed a worth-knowing statistics especially when it comes so close to us in daily lives. YouTube, as a world-famous video website with various types of videos available in it, making it a platform for us to be entertained, to be benefited and meanwhile a platform for film-makers or YouTubers to show talents and even earn a livelihood.

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In this project, the popularity of a trending YouTube video is assumed to be determined by its number of likes. Tests on data analysis are carried out, including hypothesis testing of 2 samples with unequal variance, correlation, regression and ANOVA. The interesting findings are when determining one of the variables, number of views, 10 random data in USA and Canada regions are compared and unexpectedly they have the same mean of number of views, where it is predicted that considering other variables such as description of videos, number of dislikes and others, this gives both regions producing well-matched videos ‘a fair competition’ to contribute to the popularity of their videos. To sum up, there is a relationship between number of likes (popularity) of a YouTube video and its category ID (representing video type).

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               As to say what I have learnt, I would say that through this project I have understood the importance of being inquisitive when it comes to a case-study project. Aspect of being neutral is also vital, especially when this is an individual project. For me, ‘neutral’ itself tells not having sure-to-be assumptions towards any hypothesis when analyzing the results, but to figure out “Is it appropriate for me to explain the results in such a way?”. Again, a great thanks to my lecturer, Dr Sharin for her guidance and clear instructions during completing this project.  :D

Here is the simple presentation of results analyzed in Project 2:

A YouTube video presentation URL is attached in the retractable column, "Instructions".