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Data Mining 2015/16 spring

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HW04 (06.03) - Descriptive statistics

1. Watch the video presentation by Tamara Munzner: Keynote on Visualization Principles, and slides - http://www.cs.ubc.ca/~tmm/talks/vizbi11/vizbi11.pdf Summarize the key take-home messages from her presentation.

2. Fetch the UK child height/weight measurements data from here. (File). (Local copy)

Study a sufficiently large subset of measurements - plot dotplots comparing age, height, weight, BMI;

Experiment with color - highlighting gender, BMI clinical score, or age, by different markers, color or color scales.

(hint: you may want to develop ideas first with smaller subsets of data).

3. Derive new features to plot: height*weight ; height/weight; Body Surface Area ; Plot them against each other; and against BMI, height, or weight. Try to identify interesting meaningful trends or examples, provide some interpretation.

4. Normalise height and weight based on the gender and age, repeat some of the plots from above.

5. Draw approximate growth curves over age. Calculate and plot growth curves of the different deciles (0%-10%, 10%-20%, 20%-30%, ...90%-100%) of obesity categories both by BMI and by weight, for both genders.

6. Bonus 3p Attend the Tartu city open data event in the Garage48 hub on Saturday (March 5th, 2pm). Participate in some working group. Write a report about the ideas, problem statement, envision the goals of the project and main steps that need to be executed in order to achieve the stated goals. Event registration on Facebook: https://www.facebook.com/events/969937356395544/

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