APPLICATIONS OF
STATISTICAL ANALYSES
ON WATER QUALITY
DATA AND ITS RECENT
RESEARCH TRENDS
An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, Statswork
Group www.statswork.com
Email: info@statswork.com
TODAY'S DISCUSSION
Outline
Introduction
Statistical Techniques
Future Scope
INTRODUCTION
Analysing water quality data entails reviewing and
assessing the data to see if any errors were made
during the sampling or analysis of the water quality
sample or data entry.
To detect any issues regarding data, a series of data
checks should be performed.
It includes data checking in the first stage, i.e. data
entry, whether the data is within the range of
parameters, data is within the detection limits, etc.
However, there are different aspects of water quality, and the techniques suitable for
each field are tabulated in the following subsection.
One way to analyse the water quality data is using graphical techniques.
The benefits of graphical representation of data include finding the data trend,
finding outliers in the data, etc.
STATISTICAL
TECHN IQUES
The common statistical analysis or techniques to
handle water quality data is as follows:
Contd...
1.TREND ANALYSIS
It acts as an important factor for water quality analysis since it helps the researcher
understand the data's variability.
Wang et al. (2020) proposed an innovative trend analysis to detect or identify the
annual and seasonal rainfall pattern.
Data collection from different meteorological stations and compare the proposed
method with Theil-Sen trend method Mann-Kendall test.
The result revealed a strong trend associated with flood and drought during extreme
rainfall.
Contd...
These methods' validity showed that the proposed method detects the seasonal
trend accurately than using the other two test methods.
Our Data collection service help in collect clean data and maximize your impact.
Contd...
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2. CORRELATION
Correlation is basically to identify the relationship between two or more variables. It
helps to identify the variables which control the variability in water quality data.
For example, consider a study on water flowing quality on land, i.e. water quality in the
rivers.
One can take different research problem based on the river data.
However, suppose our interest is to find the seasonality of water quality in selected
areas and the land usage.
The correlation matrix will look like the following table 1.
Contd...
Table 1: Sample Correlation Matrix
3. REGRESSION ANALYSIS
Regression analysis helps find the average relationship between the variables and is
useful to predict future outcomes.
Contd...
4. AUTOCORRELATION ANALYSIS
If we want to understand the relationship between two or more similar attributes
measured at different time points, then autocorrelation analysis can be used.
5. TESTING STATISTICAL HYPOTHESIS
6. STATISTICAL MODELLING
It is used to identify the behavior and predict future outcomes through a mathematical
formulation.
Contd...
7. CONTROL CHARTS
It is used to monitor the process and detect the data variability using control limits.
The most popular is the mean chart and range chart.
If any data points are scattered away from the limits, they can be considered defective
and treated as an outlier(s).
However, selecting a suitable statistical analysis or water quality analysis technique
depends on the data and the research question.
The choice of suitable analytical technique is based on detection limits, i.e.
Contd...
range of concentration of the chemical component in the water, how much accuracy
and precision are needed for the research problem.
The most important is the sampling strategy.
Statswork provide suitable online statistical analysis service to get high quality data.
FUTURE SCOPE
There are numerous statistical procedures
techniques to analyse the water quality data.
or
Since water scarcity is increasing due to lack of rainfall
in many regions, finding the water quality for the
recycled water, research related to turning the hard
water to soft water, etc. are considered future research
scope.
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