Difference between revisions of "ISSS608 2017-18 T3 Assign Alejandro Llorens Moreno Methodology"

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<br> Pollution in the waters of the reserve is defined by many measures but the data set only provides enough data for a set of measures
 
<br> Pollution in the waters of the reserve is defined by many measures but the data set only provides enough data for a set of measures
 
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<td>[[File:ChemicalsAlex.JPG|50x |center]]</td>
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<td>[[File:Selected chemicals.JPG|50x |center]]</td>
 
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<td><b> 3.Understand the specific changes </b>
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<td><b> 3. Visual interpretation and distribution analysis </b>
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<br>The data provided is all about the chemicals taking the readings and the date and time when the readings were taken (timestamps). This provides valuable information on the paths adopted by different vehicles inside the preserve – where did they go and what time did they go. Thus, one of the core patterns of life analysis will be centered around the paths adopted by different types of visitors identified in 1.
 
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<td><b> 4. Visual interpretation and distribution analysis </b>
 
 
<br>For better user experience I have elaborated a dashboard with a visual representation of each chemical in each location with its specific distribution in a box plot.
 
<br>For better user experience I have elaborated a dashboard with a visual representation of each chemical in each location with its specific distribution in a box plot.
 
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<td><b> 5.Outliers analysis </b>
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<td><b> 4.Outliers analysis </b>
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<br> With a control chart the user can determine easily specific outliers for each chemical selecting 1, 2 or 3 standard deviations from the average.
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<br> With a control chart the user can determine easily specific outliers for each chemical selecting 1, 2 or 3 standard deviations from the average.Upper bound: WINDOW_AVG(SUM([Value])) + ( WINDOW_STDEV( SUM([Value])) * [Standard Deviations] ), Lower bound: WINDOW_AVG(SUM([Value])) - ( WINDOW_STDEV( SUM([Value])) * [Standard Deviations] ). I have also created a measure of Outliers with the following formula: SUM([Value]) < [Lower Bound] OR SUM([Value]) > [Upper Bound]
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<td>[[File:OutliersAlex.JPG|500px|center]]</td>
 
<td>[[File:OutliersAlex.JPG|500px|center]]</td>
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<td><b> 6.Analysis of anomalies and sampling recommendations </b>
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<td><b> 5.Analysis of anomalies and sampling recommendations </b>
 
<br> To understand the sampling strategy in the dataset and suggest improvements I have created a dashboard
 
<br> To understand the sampling strategy in the dataset and suggest improvements I have created a dashboard
 
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Revision as of 09:09, 8 July 2018

Wildlife.jpg VAST Challenge 2018:Like a duck to water

Background

Methodology

Answers

Conclusion

 


Methodology & Design

Methodology

Description Illustration
1.Selecting the right chemicals


Pollution in the waters of the reserve is defined by many measures but the data set only provides enough data for a set of measures

50x
2.Visualizing the overall trend and specific changes


The chemical measures were visualized per quarter and year vs Location. This helps understand the trend for each selected chemical

Trend2.JPG
3. Visual interpretation and distribution analysis


For better user experience I have elaborated a dashboard with a visual representation of each chemical in each location with its specific distribution in a box plot.

Trend3.JPG
4.Outliers analysis


With a control chart the user can determine easily specific outliers for each chemical selecting 1, 2 or 3 standard deviations from the average.Upper bound: WINDOW_AVG(SUM([Value])) + ( WINDOW_STDEV( SUM([Value])) * [Standard Deviations] ), Lower bound: WINDOW_AVG(SUM([Value])) - ( WINDOW_STDEV( SUM([Value])) * [Standard Deviations] ). I have also created a measure of Outliers with the following formula: SUM([Value]) < [Lower Bound] OR SUM([Value]) > [Upper Bound]

OutliersAlex.JPG
5.Analysis of anomalies and sampling recommendations


To understand the sampling strategy in the dataset and suggest improvements I have created a dashboard

Anomalies.JPG
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