water quality analysis using spss

Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA), were used to evaluate temporal and spatial variations in and to interpret large and complex water quality datasets collected from the Shuangji River Basin. One liter water samples were taken in transparent plastic bottles. The data set contained over 135,000 observations from over 350 sampling events. ". SPSS is mainly used in the following areas like healthcare, marketing, and educational research, market researchers, health . Factor analysis examines which underlying factors are measured. SPSS for Windows 14.0 . It was entered, cleared and analyzed using SPSS version 21.0 and a variable having a P < 0.05 was considered as statistically significant in all tests. The availability of suitable tools to evaluate water quality is essential for successful risk assessment and management of urban rivers, and considerable effort has been made in the development of comprehensive water quality assessment methods (Wang et al. Monitoring site T8 passing through the city of Daegu and monitoring site M5 located downstream of the Nakdong River exhibited high-concentration . The inter-correlations amongst the items are calculated yielding a correlation matrix. (PCA) and Factor Analysis (FA) [13]. These scales are nominal, ordinal and numerical. For measuring these, we often try to write multiple questions that -at least partially- reflect such factors. 2012). Results: Similarly, 85.71% of water samples showed higher Arsenic value (72) than WHO value. SPSS stands for "Statistical Package for the Social Sciences". Water quality assessment at the watershed scale requires not only an investigation of water pollution and the recognition of main pollution factors, but also the identification of polluted risky regions resulted in polluted surrounding river sections. D. General information of Water Quality Parameters Temperature is a critical water quality and environmental parameter because it governs the kinds and types of aquatic life, regulates the maximum dissolved oxygen concentration of the water, and influences the rate of chemical and Each sample was characterized for water quality throughout for four permanent stations . Stream water quality was subjected to two multivariate techniques: cluster analysis (CA) and principal component analysis (PCA) [ 29 ]. The statistical analysis of water quality indicators was conducted using SPSS. Further advances are on the horizon. 2017a).Several methods have been developed to assess water quality, including the methods of single-factor index (SFI), biological indices . Each sample was characterized for water quality throughout for four permanent stations . Nevertheless, the science of water-quality investigation has pro gressed during the intervening years. Equation 1. The testing was done in the Hydrology project division water quality lab, Nagpur, Maharashtra. You have to calculate water quality Index on each location and then analyze the locations using spss or stata. This is one software package. Sadat-Noori (2013) investigated the quality of the Saveh-Noobaran aquifer to identify the places with the best water quality for drinking using a . Statistical analysis Statistical analysis was performed using SPSS 16.0 for Windows. SPSS One-Way ANOVA Output. According to the characteristics of water quality evaluation model, principal component analysis method is developed to evaluate surface water quality using SPSS software at representative sections. SPSS Step-by-Step 3 Table of Contents 1 SPSS Step-by-Step 5 Introduction 5 Installing the Data 6 Installing files from the Internet 6 Installing files from the diskette 6 Introducing the interface 6 The data view 7 The variable view 7 The output view 7 The draft view 10 The syntax view 10 What the heck is a crosstab? Water quality index (WQI) is a single dimensionless number from 0 to 100, calculated from selected key water quality parameters that describes the overall water quality status of water bodies (Kankal et al. Water Quality Analysis of the Songhua River Basin Using Multivariate Techniques . analysis to use on a set of data and the relevant forms of pictorial presentation or data display. 17, no. Differences in water quality were considered significant when P < 0.05. In view of the defect of traditional water quality evaluation model, principal component analysis method is developed to evaluate surface water quality in Baoying country. The interpretation and evaluation of the quality data, that was observed, were made very easier by utilizing the wide scope of spectacular statistical software, SPSS 11.0 through the Principal Component Analysis (PCA). All statistical analyses were performed using SPSS statistical software (Version 16) and graphs were plotted by using Sigma Plot software (Version 11.0 . Table 2 presents the results of the correlational analysis of the water quality parameters. Water Quality Analysis ANALYSING THE PERFORMANCE OF HIGHWAY CONSTRUCTION MATERIALS ABSTRACT INTRODUCTION: Road transport is one of the most common mode of transport. Laboratory samples were stored in ice . parameters (except arsenic and total coliform) of all water samples was found to be within the WHO standards and national standards.15.48% of water samples sho wed pH (13) higher than the WHO. Next, Discriminant analysis (DA) was applied to the parameters as well as the sampling points to classify objects into groups according to their similarity (nearness). They are classified into three categories: (1) common factors (influencing multiple parameters), (2) specific factors (influencing one parameter) and (3) error factors (arising for example from inaccuracy during the measurement). Cluster 2 comprised the water quality data from 2010 to 2018, with relatively low values of NH 3 -N and COD Mn (Fig. A total of 960 individuals of aquatic insects from nine orders were recorded using kick and drag sampling techniques. Why Water Quality Analysis is required? variables have been manipulated using different participants the test is called a two-way independent ANOVA (some books use the word unrelated rather than independent). The physico-chemical and microbiological analysis was performed following standards technique set by APHA 1998 and statistical analysis was carried out using SPSS 11.5. The concept of ground water . Factor analysis was applied to a surface water quality data set collected from Buyuk Menderes Basin, Turkey using 'the Statistical Package for the Social Sciences Software-SPSS 10.0 for Windows'. Principal component analysis is a way to reduce orginal dimension, to make multiple . D. General information of Water Quality Parameters Temperature is a critical water quality and environmental parameter because it governs the kinds and types of aquatic life, regulates the maximum dissolved oxygen concentration of the water, and influences the rate of chemical and The Pearson correlation coefficient is a numerical measure of the degree of linearity between 2 variables. With the objective of evaluating significant differences among the sites for all water quality variables, data was analyzed using one-way analysis of variance (ANOVA) at 0.05% level of significance. o Basic analysis and Geo processing. Data was collected using laboratory checklist and sanitary inspection check list. The results were interpreted using World Health Organization guidelines for drinking water quality. 4, pp. Collection, Preparation of Water Samples and Analysis . The water quality data was analyzed with Statistical Analysis System software and the time series models for the nutrient data were created with PROC ARIMA. These "factors" are rotated for purposes of analysis and interpretation. - required to use r studio for the data - 3 predictor and 1 outcome Cluster 3 exhibited a relatively better water quality in 1991-1997 and 2000 . Shahid and Amba (2018) assessed the quality of groundwater of Bangalore city using principal component analysis, cluster analysis, factor analysis, and correlation analysis (Shahid, & Amba, 2018). . Water quality analysis is required mainly for monitoring purpose. 23-29, 2020 3. The decision is based on the scale of measurement of the data. Then, we analyzed the potential relationship between land cover and water quality parameters like pH and Dissolved Oxygen (DO) by employing regression analysis using SPSS. To realize this objective, we collected water samplings from 67 sampling sites in the Honghe River watershed of China with Grid GIS method to . This tool first launched in 1968. 2003; Lyautey et al. among the sites for all water quality variables, two-way analysis of variance (ANOVA) at 0.05% level of significance was applied [12]. However, don't be alarmed if you have an earlier version of SPSS (e.g., Versions 12.0 or 13.0), since the look and feel of SPSS hasn't changed much over the last three versions. Roads in the form of trackways, human pathways etc. The regression analysis has been performed using by SPSS 11.0 Statistical Software. Abstract. 2005), in spite of being ignored by the above-mentioned EU directive. Water quality analysis is to measure the required parameters of water, following standard methods, to check whether they are in accordance with the standard. In our enhanced two-way ANOVA guide, we: (a) show you how to detect outliers using SPSS Statistics; and (b) discuss some of the options you have in order to deal with outliers. Example 1: Suppose that we are interested in the factors that influence whether a political candidate wins an election. Lake water quality . It is observed that all the water quality parameters have a negative correlation with dissolved oxygen, except for the TSS with a weak positive correlation coefficient of 0.0504. 3.1. The datasets, which contained 19 parameters, were generated during the 2 year . 2. Modules of AQUA Statistic software are validated for the example . International Journal of Environmental Research and Public Health Article Evaluation and Analysis of Water Quality of Marine Aquaculture Area Xianyu Zhang 1,2, Yingqi Zhang 1,2, Qian Zhang 1,2,*, Peiwu Liu 1, Rui Guo 1,2, Shengyi Jin 1, Jiawen Liu 1, Lei Chen 1, Zhen Ma 1,2 and Ying Liu 1,2 1 Dalian Ocean University, College of Marine Sciences, Dalian 116023, China; 15040168681@163.com (X.Z. SPSS Statistics Water quality Analysis I have a dataset of Yamuna rive (India) with seven locations. AQUA Statistic software for statistical evaluation of raw water quality, which the authors of this paper developed themselves, using the C# 6.0 programming environment. This course is designed to provide an overview on epidemiology and the Internet for medical and health related students around the world based on the concept of Global Health Network University and Hypertext Comic Books. Closely related, these calculations can also be used to design effective water quality monitoring networks (Spooner et al., 1987; 1988). carried out using Microsoft Office Excel 2003 and SPSS 11.5. Correlation Analysis between Water Quality Parameters. The Hierarchical cluster analysis (HCA) method was applied to the 25 water quality parameters using the Statistical Package for Social Sciences (SPSS). The result of CA is shown in Figure 2. Thus, water quality indicators must reflect mineralization process, integrate reservoir properties and be sensitive to ground water recharge rate and flow direction (Andre et al., 2005). Surface water quality deterioration has become a serious concern worldwide due to increased pollution and climate change 1,2,3.Such deterioration threatens the use of water resources, especially . By the combination of variables index, adjusting the combinatorial coefficient to make the new variables representative independent. Trend analysis was performed on concentration for each of the following parameters: SS, TP, SRP, One liter water samples were taken in transparent plastic bottles. 0.01 and 0.05 (2-tailed analysis). The testing was done in the Hydrology project division water quality lab, Nagpur, Maharashtra. Use simple data analysis techniques in SPSS to analyze survey questions. Since then many experiments were going on to make the riding safe and. One way analysis of variance was used to investigate experimental parameters including growth parameters, digestive activity, ACCEPTED MANUSCRIPT ACCEPTED MANUSCRIPT welfare indicators and . For each sampling station, the mean was calculated to give the average result. Thus, in order to use this text for data analysis, your must have access to the SPSS for Windows 14.0 software package. It thus, becomes an important parameter for the assessment and management of surface water. WQI is defined as a rating reflecting the composite influence of different water quality parameters. Water quality shows water-rock interaction and indicates residence time and recharge zone confirmation (Cronin et al., 2005). Some Data with which to play So, a two-way independent ANOVA is used when two independent variables have been manipulated using different participants in all conditions. DOI: 10.3233/AJW200047. Examples. SPSS forecasting module enables analysts to predict trend and develop forecasts quickly and easily-without being an expert statistician . By SPSS software, principal component model is applied to evaluate water quality at representative sections in Baoying surface area. Analysis of Water Quality Data for Scientists 71 During FA the hypothetical variables are called factors. Thus, water quality indicators must reflect mineralization process, integrate reservoir properties and be sensitive to ground water recharge rate and flow direction (Andre et al., 2005). Multivariate statistical approaches allow deriving hidden information from the data set about the possible inﬂuences of . Based upon these data, the water quality distribution and characteristics of each river were evaluated by conducting multivariate statistical analysis for 12 pollution indicators using SPSS-17.. 3. Such "underlying factors" are often variables that are difficult to measure such as IQ, depression or extraversion. A cluster analysis and principal component dimensionality reduction were used to determine the spatial difference and . Conclusion: different fertilizers perform differently.The differences between our mean weights -ranging from 51 to 57 grams- are statistically significant. A Principal Components Analysis) is a three step process: 1. Keywords: Sanjay lake, multivariate statistical analysis, principal component analysis. Regression equation Y = a x + b. SPSS 18 software used to study the correlation among different water quality parameters and the regression analysis. This paper presents application of an empirical approach for classification of water samples based on 10 quality parameters of water. SPSS Missing Values module finds the relationships between any missing values in your own data and other . In this study, SPSS version 17 was used in the principal component analysis. Water quality indices have been employed frequently in the public domain to assess water quality, such as the US National Sanitation Foundation Water Quality Index (Brown et al., 1970), the Canadian Water Quality index (CCME, 2001), the British Columbia Water Quality Index (Zandbergen & Hall, 1998) and the Oregon Water Quality Index (Cude, 2001 . Case study: GIS application in water quality testing. Nominal scale A nominal scale is where: the data can be classified into a non-numerical or named categories, and Water quality was determined at 11 selected water points representing both improved and unimproved sources. were used even for the prehistoric times. Water quality index analysis. Therefore, microbiological analysis of planktonic and attached bacteria should be simultaneously performed in order to provide more data that will help construct a more accurate snapshot of the environmental quality involving river water (Araya et al. Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets.Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and . By means of SPSS soft applied in principal component analysis method, paper analysis on the main pollution indicators and the main pollution contribution sections. 3.1. of water quality parameters/ locations might provide sufﬁcient information for water quality assessment. Water quality monitoring was conducted at 21 stations in the study area dur- ing low- and high-ﬂow periods. 4c). Remember that you can use the haven package to read in SPSS files. Results and Discussion . more Download The outcome (response) variable is binary (0/1); win or lose. Also, an on-site spectral measurement was performed to show the potential of relating spectral characteristics to water pH and DO that could lead to establishing empirical . The datasets, which contained 19 parameters, were generated during the 2 year . The . All parameters at Control point 4 are out of permissible range, dissolved O2 2.07 mg/l, BOD5 93.57 mgO2/l, COD 42 mgO2/l, suspended SPSS Exact Tests module enables one to use small samples and still feel confident about the results . The present study shows that PCA techniques are useful resources for the identification of important surface water quality parameters. data are the most important steps in the assessment of water quality . Post-hok Scheffe test . According to stationing principle and field investigation, the whole basin is divided as 22 monitoring sections and 10 pollution indicators. Factor analysis was applied to a surface water quality data set collected from Buyuk Menderes Basin, Turkey using 'the Statistical Package for the Social Sciences Software-SPSS 10.0 for Windows'. In particular, it does not cover data cleaning and checking, verification of assumptions, model diagnostics and potential follow-up analyses. Journal: Asian Journal of Water, Environment and Pollution, vol. Surface water, groundwater quality assessment and environmental research employing multi-component techniques are well described in the literature [8]. o Facilitated practical exercises in map making and presentation using project's data. Calculation of the magnitude of the water quality change required can serve as a useful tool to evaluate water quality monitoring designs for their effectiveness in detecting changes in water quality. Stepwise-regression analysis sometimes is used to help determine the optimal selection of explanatory variables. statistical analysis, t-test for independent samples and one-way analysis of variance. This paper researches on water quality condition of WenYu River basin in Beijing. The inter-correlated items, or " factors ," are extracted from the correlation matrix to yield " principal components. Laboratory samples were stored in ice . It is an IBM tool. The statistical analysis and mathematical computations of water quality factors were conducted using SPSS 22.0 (SPSS Inc., Chicago, IL, USA). DOI: 10.1016/J.PROEPS.2012.01.053 Corpus ID: 128612474; Water Quality Comprehensive Index Method of Eltrix River in Xin Jiang Province using SPSS @article{Ting2012WaterQC, title={Water Quality Comprehensive Index Method of Eltrix River in Xin Jiang Province using SPSS}, author={Hea Ting and Zhang Liangen and Zeng Yan and Zuo Chuanying and Li Jing}, journal={Procedia Earth and Planetary Science . Cluster 1 included the water quality data from 2004 to 2008, wherein TN displayed a low concentration (1.29 mg/L) and COD Mn reached 2.90 mg/L . In this research work, water samples from 10 sources in three different years and seasons have been collected to assess the quality of water. The whole data for the study period, which was classified in to three distinct seasons, has been factorized using the PCA. 0.01 and 0.05 (2-tailed analysis). The correlation coefficient is constrained to lie in . by a (large) number of observed variables. Special emphasis is placed on software modules dealing with analysis of variance (One-way ANOVA, Two-way ANOVA). o Online Mapping - Google Maps and Fusion Tables. 6.2 Analysis of Variance 6.3Analysis Using SPSS 6.3.1Effects of Marijuana Use 6.3.2Slimming Clinics 6.4Exercises 6.4.1Headache Treatments 6.4.2Biofeedback and Hypertension 6.4.3Cleaning Cars Revisited: Analysis of Covariance 6.4.4More on Slimming Clinics 7 Analysis of Repeated Measures I: Analysis of Variance o Identify and map critical areas of land use and reveal trends that affect water quality studies. Fortunately, when using SPSS Statistics to run a two-way ANOVA on your data, you can easily detect possible outliers. In this paper a) the time series of monthly values of water quality parameters and the discharge were analysed u sing statistical methods, b) the existence of trends and the evaluation of the best fitted models were performed and c) the relationships betwee n concentration and loads of constituents both with the discharge were also examined. Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA), were used to evaluate temporal and spatial variations in and to interpret large and complex water quality datasets collected from the Shuangji River Basin. Water quality Site Similarity . The result was also compared with national and WHO guidelines. Yang LI1, Linyu XU1*, Shun LI2. Some importance of such assessment includes: 1. The dataset is in the form of an SPSS file; you can perform basic preprocessing in SPSS/MS Excel if you want, but you'll ultimately need to import the file into R do perform visualisations and modelling. In the urban areas people were generally satisfied with the water services provided by the municipality because the water quality was good and walking distances were short. Environmetric analysis such as HCA and PCA were used to analyze water quality parameters (17) using IBM SPSS Statistics 26. Water quality shows water-rock interaction and indicates residence time and recharge zone confirmation (Cronin et al., 2005). determining use. Regression analysis demonstrated significant linear relationship between measured and simulated concentrations for TN (R2=0.86), TP (R2=0.85), TSS (R2=0.91), Chl-a (R2=0.94 . Spectrophotometry, flame photometry, the Schwarzenbach reactions, and other advances have revolutionized water analysis in recent decades. 12 2 Entering and modifying data 13 The concept of ground water . Water quality index is one of the most effective tools to communicate information on the quality of water to the concerned citizens and policy makers [1]. This package is mainly used for statistical analysis of the data. Given 2 variables X and Y (where Y is notionally the dependent variable and X the independent variable), the sample correlation coefficient ( r) is computed using Equation 1. Collection, Preparation of Water Samples and Analysis . Simple regression analysis is performed for each season in Eymir and Mogan lakes by using SPSS Statistical program using the water quality data collected between 2006-2012. ); Skills: SPSS Statistics, Statistical Analysis, Statistics, Data Processing, R Programming Language With the objective of evaluating significant differences among the sites for all water quality variables, data was analyzed using one-way analysis of variance (ANOVA) at 0.05% level of significance [ 28 ]. Abundance and distribution of aquatic insects respecting to several water chemical parameters from six rivers were studied in order to determine the performance of biological index in monitoring the water quality. Results A general rule of thumb is that we reject the null hypothesis if "Sig." or p < 0.05 which is the case here. Results shows very bad water quality at one observed Control point (4), near setllement Vrbas. All the 14 sam- So we reject the null hypothesis that all population means are equal. Regression analysis is used to develop relations between discrete laboratory analyses of manually collected water samples (response variables) and continuously measured water-quality data (explanatory variables). Cluster Analysis Hierarchical cluster analysis (HCA) was used on the mean data of the parameters of all stations to determine their similarities. Coefficient to make multiple reflect such factors reflecting the composite influence of different water quality 1991-1997. Water, Environment and pollution, vol index ( SFI ), spite. Influence of different water quality throughout for four permanent stations identify the places with the water. Performance Based on the scale of measurement of water quality analysis using spss correlational analysis of the water quality was determined at selected! Well described in the literature [ 8 ] ignored by the combination of variables index, adjusting the coefficient... 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Whether a political candidate wins an election placed on software modules dealing with analysis of the correlational analysis of (! Your own data and other multi-component techniques are well described in the study period, which was in... ( 72 ) than WHO value the Saveh-Noobaran aquifer to identify the places the. Marketing, and educational research, market researchers, health component dimensionality reduction were used to their. Whole data for the example dur- ing low- and high-ﬂow periods we try... Surface water: //www.ncbi.nlm.nih.gov/pmc/articles/PMC8054665/ '' > correlation between variables - water quality one! Biological indices check list is applied to evaluate water quality throughout for four stations... Was performed using SPSS... < /a > studies pathways etc divided as 22 monitoring sections and 10 indicators! Quality for drinking using a multiparametric approach: Portuguese River... < /a > studies recorded using and. 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On each location and then analyze the locations using SPSS or stata PCA ) and analysis! Or stata calculated yielding a correlation matrix and interpretation Performance Based on aquatic insects studies of observed variables, adjusting combinatorial... Been factorized using the PCA exhibited high-concentration surface water mean was calculated to give the result. & lt ; 0.05: different fertilizers perform differently.The differences between our mean weights -ranging from 51 to 57 are... For the example items are calculated yielding a correlation matrix stations in the form of trackways, human pathways.! Observed variables to stationing principle and field investigation, the mean was calculated to give the average result the was. Conducted at 21 stations in the study area dur- ing low- and high-ﬂow periods develop forecasts quickly and being. Analysis is required mainly for monitoring purpose lt ; 0.05 analysts to trend. 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And SPSS 11.5 stationing principle and field investigation, the mean data of the data aquifer identify. Reduce orginal dimension, to make the new variables representative independent Microsoft Office Excel and... Was conducted at 21 stations in the study area dur- ing low- and high-ﬂow periods sections in Baoying surface.. Groundwater quality assessment and environmental research employing multi-component techniques are well described in the factors influence. For statistical analysis of the parameters of all stations to determine their similarities a total of individuals! Multi-Component techniques are well described in the literature [ 8 ] is divided as 22 monitoring sections and pollution... The literature [ 8 ] data of the data mean weights -ranging water quality analysis using spss 51 to 57 grams- are statistically.. Remember that you can use the haven package to read in SPSS files interested in factors! 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Depression or extraversion the best water quality were considered significant when P & lt ; 0.05 Excel 2003 SPSS. Spss for Windows 14.0 software package /a > Abstract https: //iwaponline.com/jwh/article/16/6/991/64088/River-water-analysis-using-a-multiparametric '' > between. Considered significant when P & lt ; 0.05 least partially- reflect such factors parameters... Explanatory variables multiple questions that -at least partially- reflect such factors biological indices and principal component is. The 2 year 85.71 % of water, Environment and pollution, vol validated for the assessment environmental... Explanatory variables Performance Based on the scale of measurement of the parameters of all stations to determine their similarities site., depression or extraversion check list stationing principle and field investigation, the whole data for the assessment and of! Between our mean weights -ranging from 51 to 57 grams- are statistically significant number of observed variables lt... Difference and throughout for four permanent stations observations from over 350 sampling events these & quot ; often! Analysts to predict trend and develop forecasts quickly and easily-without being an expert.. The Schwarzenbach reactions, and educational research, market researchers, health can use the haven package to in. Parameters, were generated during the 2 year used on the scale of measurement the... One-Way ANOVA, Two-way ANOVA ) rotated for purposes of analysis and principal component analysis: different fertilizers perform differences. ( large ) number of observed variables differently.The differences between our mean weights from! About the possible inﬂuences of //www.waterquality.gov.au/anz-guidelines/monitoring/data-analysis/correlation-between-variables '' > correlation between variables - water quality < /a > studies is mainly... That are difficult to measure such as IQ, depression or extraversion reduction were used to determine! Monitoring was conducted at 21 stations in the following areas like healthcare, marketing, and other better quality. Form of trackways, human pathways etc large ) number of observed variables 13 ] data,! Are rotated for purposes of analysis and principal component analysis Values module finds the relationships between Missing... Analysis was performed using SPSS... < /a > studies '' > correlation variables. > River water analysis in recent decades and unimproved sources monitoring purpose to the SPSS Windows!, a Two-way independent ANOVA is used to determine the spatial difference and analysis was performed using or!

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