Peer review for proposal - Team B

[TraMiu]

Suggestion 1: Our team thinks your questions about the potential underlying reasons for the differences in educational attainment among the youth across coastal and non-coastal towns in English are very intriguing and interesting. One of the reasons we could think of is the distractions such as the number of fleshpots in those coastal areas that could distract the youth from their education. Therefore, we suggest adding external data such as number of fleshpots to your analysis to see if there are any interesting insights.

Suggestion 2: Our team thinks that your description of the dataset is not really clear about the dataset’s size, and number of samples, it would be better if you could add it. Besides that, about the reason you chose this dataset, I think it would be better if you link the dataset’s advantages to benefits brought back by those characteristics ( e.g. rich of sample -> diversity of viewpoints) rather than simply listing what is good about the chosen data.

[tienvu95]

think considering the distractions in coastal region are a good direction to follow, given that their question 2 are very similar to question 1 (in question 1, I can just separate coastal and non coastal with a legend and can understand what led to the differences between these regions. However, fleshpots might not be an appropriate word to describe what distract the students :))

[khointn]

Hi, it's Khoi from team D. Thank you for your insightful comments and suggestions.

Suggestion 1: I think it's a good idea to take a look at external data as an additional source of information for analysis. As Mr. Tien has mentioned, "fleshpots" might not be an appropriate keyword, but we will try to take a look at other external data that could enrich our analysis. We are thinking of some geometric (common locations in coastal areas) or cultural (common habits or lifestyle) reasons. However, we believe that one critical reason for this issue is that big cities (except Liverpool) in England are normally land area rather that coastal, which leads to better education quality.

Suggestion 2: The reason we chose this dataset was because it provides several interesting insights (e.g. the coastal, and non-coastal differences), together with different attributes provided. However, we admit that it was not clearly shown in our proposal. We are going to modify it and make sure that we highlight this point.