PLEASE HAVE A LOOK AT THE QUESTION WHICH IS ATTACHED BELOW:
· Learn how to recognize dataset and attribute types.
· Learn how to generate data analysis questions and transform data in ways that enable you to answer them.
How do you know if you are on the right path? You can easily generate questions out of data, figure out how data needs to be transformed in order to answer the question and, identify what data set type and attribute types your data transformation has generated.
For this exercise we will use the “Aid Data” dataset: World Bank Project-Specific DisbursementsLinks to an external site. (https://www.aiddata.org/data/world-bank-project-specific-disbursements)
Step 1: Read the data set description (from website and dataset itself), carry out data abstraction on the provided data set. (10 points total)
· in a Word document, write down the dataset type. (1 point)
· Write down the number of fields/attributes. (1 point)
· Analyze each field in terms of attribute abstractions: write down a concise description in domain-dependent language of the field’s meaning; decide the attribute type and write that down. (8 points)
Step 2: Analyze the cardinality (10 points total)
Write down the number of total items (1 point), and
· For each attribute, indicate its cardinality. (4 points)
· For categorical attributes, write down the number of unique levels. (2 points)
· For quantitative attributes, specify the range from min to max and note any other characterization that seems potentially useful (cyclic? Anything else?) (2 points)
· For ordered attributes, consider whether it would be more useful to treat them categorical or quantitative, or to preserve them as ordered. (1 point)
Step 3: Write three questions you would like to answer with this data set, from the point of view of an aid worker reporting to the government of a country providing aid. (30 points total, 10 points for each question)
For each question, write the following information:
· Do you need a chart in order to answer this question? (1 point)
· If none of your questions require a chart, try to create a few new ones that might benefit from one.
· Which fields/attributes do you need to use to answer the question? (2 points)
· Do you need to transform the data in order to answer the question? If yes, what transformations are needed? (2 points)
· Do data set type and attribute type change when you need to transform the data? If yes, how do they change? (2 points)
· Do you have all the data you need to answer this question, or would you need additional data fields that are not provided here? (3 points)
Step 4: REFLECT/DISCUSS: What did you learn in this exercise? (5 points) How might this analysis be useful in visualization design? (5 points)