ISSS608 2017-18 T3 Assign Low Zhi Wei Methodology

 Investigating chemical contamination in the Boonsong Lekagul waterways

Background

Methodology

Visualisations

Conclusion

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Approach

The approach to this exercise is captured in the flow below. Unlike in most typical data analysis undertakings, the data provided is relatively clean and requires no further cleaning.

Data Description

To understand the data, high level review was conducted across the data as a whole and on each of the available variables. The table below summarises observations on the data as a whole as well as provided descriptive information on the data.

Variable	Description	Observation / Structure
Id	Identification number for the record (only for bookkeeping)	136824 unique records
Value	Measured value for the chemical or property in this record	Range from 0 to 37959.28 with a mean of 24.02
Location	Name of the location sample was taken from. See the map for geo-location of the sampling site.	10 different locations - Achara, Boonsri, Busarakhan, Chai, Decha, Kannika, Kohsoom, Sakda, Somchair, Tansanee.
Sample Date	Date sample was taken from the location	Range from Jan 1998 to Dec 2016
Measure	Chemicals (e.g., Sodium) or water properties (e.g., Water temperature) measured in the record	Spans across 106 differing chemicals. 9700 records were noted with zero values.
Unit	An additional field acting as reference on the measurement units used for different chemicals listed in the waterway readings	Available in C, mg/l and µg/l. Out of the 106 chemicals, only Water Temperature is available in C, 39 chemicals are provided in mg/l, and 65 chemicals in µg/l. Macrozoobenthos is not listed with any type of measurement.

For the purposes of analysis, only Value, Location, Sample Date, and Measure have been identified as useful.

Data Exploration

A basic distribution view is generated on the 4 key variables identified for analysis.

Value

This field represents the readings of samples collected. An overwhelming majority (99.5%) fall under 347 and below, while the maximum is at 37959.28. While it is noted that the values are represented on different scales according to the 'Unit' variable, normalisation is not recommended to rescale these values as chemicals naturally occur at widely different levels of amount in soil.

Taking the largest unit of mg/l and maximum value of 37959.28, the value translates to roughly 37.9grams per litre; this indicates the absence of abnormal or impossibly high data errors.

Location

From the table below, we see a wide disparity between the total number of readings collected at each location. This is disconcerting as it indicates a lack of consistency in collection of the chemical samples.

Location	No. of records
Achara	2855
Boonsri	31314
Busarakhan	7492
Chai	31245
Decha	2731
Kannika	22152
Kohsoom	7895
Sakda	21429
Somchair	7537
Tansanee	2174

Dates

The dates do not reflect normally in JMP, whereby the year appears to be inflated. However, no further cleaning was performed on this field as it suitably reads and displays accurately in Tableau.

Measure

The distribution of measures show an even more astonishing disparity in readings between chemicals than the locations. As the data set does clearly show a sizeable amount of zero-value readings (9700), we cannot safely assume that the lack of readings for any particular chemical is due to it not being found in the soil samples.

Using a simple colour chart below, a daily view of the collected readings can be shown - at one glance, the records collected for each chemical on a daily basis is highly inconsistent, mostly hovering at just 1, and going as high as 19. This demonstrates a fatal flaw in the collection of the data from a statistical standpoint - insufficient resampling to support any significant observation or hypothesis. It is also not in line with common soil sample collection methodologies.

In addition, we can illustrate the number of records collected across all 10 locations and 19 years. From the chart below, it is clear that there were no records collected at 3 locations Achara, Decha, Tansanee for the years 1998-2008. We further note that Boonsri and Chai have an improportionate number of records collected from 2005-2008. Given these observations, it would be appropriate to only compare 2009-2016 data for consistency.

Tools

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