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Exploratory Data Analysis (EDA) using Watson Analytics Activities 1. Select from the datasets provided (or ones designated by your instructor).
Exploratory Data Analysis (EDA) using Watson Analytics
Activities
1. Select from the datasets provided (or ones designated by your instructor). Provide a brief description of the dataset to include the number of cases, description of the inputs, description of the variables that could be used to develop predictive models, etc.
2. Examine the dataset and eliminate mistakes, bad records, data entry errors, and outliers.
Using Watson Analytics:
3. Explore the dataset, including:
a) Examine the initial set of questions posed by Watson Analytics. Provide any insights gained from this initial dataset.
b) Develop new specific questions which provide additional insights into and answer specific questions from the dataset. Discuss how these insights could be useful. Did Watson Analytics provide the answers necessary? Discuss how you would improve the relevancy.
c) Experiment with the available filters and visualization options and summarize the results. Create and explain at least one insightful global and one local filter for your dataset.
d) Create and explain at least one insightful calculation. Discuss why this would be useful.
4. Refine the dataset.
a) Which variables have the highest quality score? Which ones have the lowest quality score and why? Discuss how the quality of the dataset could be improved.
b) Utilize the available grouping, filtering and hierarchical functionalities to refine the data. Summarize the approach you took and the outcome. What suggestions or insights are gained?
