You are required to work on at least 10 stations of one area, which matches the last digit of your uni id.

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

There are 10 areas (see “area id” on “station list.xlsx”) of Country A. You are required to work on at least 10 stations of one area, which matches the last digit of your uni id. For instance, if your id is 12345678, you should filter out stations in area 8, and work with at least 10 out of them. There are no imposed criteria in selecting specific stations. As a rule of thumb, your selection should utilize the available information (i.e. non-missing data) of more recent periods as much as possible.

1. Use Tableau® to create an interactive dashboard allowing the user to interrogate your data, to address basic questions about the weather conditions of selected stations over 1951-2010.
   (10 marks)
2. Construct a StoryBoard in Tableau® to explain some particular aspect of the data you find interesting, or surprising, or that could be misleading. The first page should be named “cover page”, which includes your uni id, area id, and briefly explain the criteria of selecting the examined stations (which you displayed in the interactive dashboard, not the storyboard).
   (10 Marks)

Note:

1.     There are quite a few missing values (labelled as 32766), especially over the old years. You need to decide which temporal periods should be kept to present “more useful” weather conditions. However, if you only keep recent data, you are facing a risk of not telling a story of the temporal trend of weather conditions.

2.      As there are no geographical information of the stations, aggregating them “blindly” may not be reasonable (recall that Country A has a large land area, which means very different conditions may exist for different locations). However, stations that share more similar weather conditions may suggest that they are geographically closer. Aggregation based on such justification is not “blind”.

3.     There are no units information of the raw data. Hence, you can discard the categorical variable such as wind direction. For quantitative variables, you don’t have to specifically discuss the exact units. Presenting the numbers are sufficient.

4.     Some weather conditions have both extreme and average/normal variables. You need to make a decision whether you need to focus on extreme values only, usual conditions only, or both.

5.     You should consider the differences in seasons and the corresponding calendar months. As a rough classification, for a country in North Hemisphere, Spring, Summer, Autumn and Winder covers months 3-5, 6-8, 9-11, and 12-2, respectively. However, you can use your own justification on this matter.

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