Investigating the effect of pollution of River Hun on Human health.

Investigating the effect of pollution of River Hun on Human health.

Title: Investigating the effect of pollution of River Hun on Human health.

 

Contents

Introduction. 3

The results. 3

Descriptive analysis. 3

Conclusion of the study. 6

 

 

 

 

Introduction

In this project, the study will be interested with the chronic effect of the pollutant in the river on the chronic effect on the human health. The study was interested in investigating if there was significant difference in the mean level of pollutant at different location of the river Hun. The study also investigated among the location of sampling which of the sampling points was the level of pollution the highest. The study used the one way analysis of variance to investigate if there was significant difference in the mean level of pollutant in the river location. The study also used the regression to investigate If there was significant relation between the location with highest pollution and the other sampling locations. In this project, the exploratory analysis that was conducted was normality test of the data since one of the assumption for conducting One way analysis of variance and the regression analysis was that the data must be normally distributed. Methodology and analysis

The data was collected from different sampling point in the rivers. The sampling points included; H1, H2, H5, H6, D, and X. A control sample was also collected at a different point in river Hun. The analysis to determine if there was significant mean difference in the mean pollutant in the river at different sampling location was conducted using the one way analysis of variance ( ANOVA). The analysis to determine if there was significant influence of the pollution. To investigate the relationship between the highest pollution location with the of ther locations, a regression analysis was noducted.

The results

Descriptive analysis

The analysis indicated that the mean pollution was 4.856 with the minimum pollution was 2.268 while the maximum pollution was 7.765

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  2.268   3.252   4.721   4.856   6.570   7.765 

The result of one way ANOVA

In this section, we are interested in examining the significance of pollution in different river Hun sites. The report investigated the significant of the location H1, H2, H5, H6 and D on the X . the report will use both the ANOVA and the regression analysis. In one way analysis of variance, the data need to follow normal distribution.

The One way analysis of variance

The hypothesis

The null hypothesis: There is no significant mean difference on the level of pollutant in all the locations in River Hun

The alternative hypothesis: There is significant mean difference on the level of pollutant in all the locations in River Hun

             Df Sum Sq Mean Sq F value Pr(>F)
LOCATION      6    0.5  0.0789   0.028      1
Residuals   392 1107.6  2.8254               

 

From one way analysis of variance, it can be observed that the f- value was 0.028 with a p- value = 1 which was greater than 0.05 significant level. This means that there was no significant mean difference in the chronic effect due to the pollutant in the River Hun for different location.

Further analysis indicate that location X was the one with highest level of pollution while D had the least level of pollutions

The regression analysis

The section investigate the relationship between the high location of pollution to other location. From the analysis, it was observed that the H6 sampling location and D location significantly relate to the highest level of pollution the X location. The analysis also indicate that there was no significant relationship between the pollution level at location H1, H2, and H3 and the first sampling replication.

lm(formula = X_rep1 ~ Control_rep1 + H1_rep1 + H2_rep1 + H5_rep1 +

    H6_rep1 + D_rep1, data = data)

 

Residuals:

     Min       1Q   Median       3Q      Max

-0.86582 -0.11516 -0.00023  0.11993  0.79976

 

Coefficients:

             Estimate Std. Error t value Pr(>|t|)   

(Intercept)   0.07031    0.01652   4.256 2.28e-05 ***

Control_rep1  0.21792    0.01646  13.242  < 2e-16 ***

H1_rep1       0.03179    0.04195   0.758    0.449   

H2_rep1      -0.04121    0.03670  -1.123    0.262   

H5_rep1       0.04962    0.04295   1.155    0.248   

H6_rep1       0.40174    0.04621   8.694  < 2e-16 ***

D_rep1        0.33299    0.03276  10.166  < 2e-16 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

 

Residual standard error: 0.1971 on 993 degrees of freedom

Multiple R-squared:  0.9942,  Adjusted R-squared:  0.9942

F-statistic: 2.851e+04 on 6 and 993 DF,  p-value: < 2.2e-16

 

From general analysis of the regression in the sampling one, it was observed that the p- value was 0.0000022 which was less than 0.05 significant level. This implies that the relation was significant and that the pollution at H6 location and D influences the pollution at Location X

The results 2

This section of report investigate the relationship between the pollution of highest location X and the other sampling location and the second sample replication. From the analysis, it was observed that the location H2, H5. H6 and D as well as the control location has a p- value less than 0.05 significant level. This means that the pollution at location H2, H5, H6 and D significantly influence the pollution at the location X in the river Hun

lm(formula = X_rep2 ~ Control_rep2 + H1_rep2 + H2_rep2 + H5_rep2 + 
    H6_rep2 + D_rep2, data = data)

 
Residuals:
     Min       1Q   Median       3Q      Max 
-0.61613 -0.08444 -0.00522  0.08447  0.62664 

 
Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -0.04476    0.01263  -3.543 0.000413 ***
Control_rep2  0.17248    0.01308  13.190  < 2e-16 ***
H1_rep2      -0.02189    0.03200  -0.684 0.494078    
H2_rep2       0.07019    0.01282   5.475 5.53e-08 ***
H5_rep2       0.20875    0.03582   5.828 7.59e-09 ***
H6_rep2       0.46886    0.02979  15.737  < 2e-16 ***
D_rep2        0.11013    0.02787   3.951 8.33e-05 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

 
Residual standard error: 0.1513 on 993 degrees of freedom
Multiple R-squared:  0.9967,  Adjusted R-squared:  0.9967 
F-statistic: 5.045e+04 on 6 and 993 DF,  p-value: < 2.2e-16

 

From general analysis of the regression in the sampling two, it was observed that the p- value was 0.0000000 which was less than 0.05 significant level. This implies that the relation was significant and that the pollution at locations H2, H5, H6 and D influences the pollution at Location X.  The analysis indicated at sampling point 2, the coefficient of determination was 0.99567 which was significantly higher than in sampling point 1.

The results 3

This section of report investigate the relationship between the pollution of highest location X and the other sampling location and the third sample replication. From the analysis, it was observed that the location H2, H5. H6 and D as well as the control location has a p- value less than 0.05 significant level. This means that the pollution at location H1, H2, H5, H6 and D significantly influence the pollution at the location X in the river Hun

lm(formula = X_rep3 ~ Control_rep3 + H1_rep3 + H2_rep3 + H5_rep3 + 
    H6_rep3 + D_rep3, data = data)

 
Residuals:
     Min       1Q   Median       3Q      Max 
-1.58819 -0.17567 -0.00448  0.15654  1.68163 

 
Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)   0.10564    0.02878   3.670 0.000255 ***
Control_rep3  0.09328    0.03072   3.036 0.002457 ** 
H1_rep3      -0.56271    0.06490  -8.670  < 2e-16 ***
H2_rep3       0.76557    0.08696   8.804  < 2e-16 ***
H5_rep3      -0.35181    0.07561  -4.653 3.72e-06 ***
H6_rep3       0.47280    0.07480   6.321 3.92e-10 ***
D_rep3        0.56646    0.07935   7.139 1.82e-12 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

 
Residual standard error: 0.3503 on 993 degrees of freedom
Multiple R-squared:  0.9819,  Adjusted R-squared:  0.9818 
F-statistic:  8992 on 6 and 993 DF,  p-value: < 2.2e-16

From general analysis of the regression in the sampling three, it was observed that the p- value was 0.00000 which was less than 0.05 significant level. This implies that the relation was significant and that the pollution at locations H2, H5, H6 and D influences the pollution at Location X.  The analysis indicated at sampling point 3, the coefficient of determination was 0.9819 which was significantly lower than in sampling point 1 and 2

Conclusion of the study

The study concluded that the location of the river Hun where the sample were collected indicated that there is significant evidence that the pollution in the river affect chronic on human health. The analysis also concluded that there location X had the highest level of pollutants in the river. From the results, it was observed that there was no significant mean pollution difference among the difference location in river Hun. The results also indicated that the location with the highest pollution was X and the location with the least pollution was D.  The results also indicate that there was significant relationship between the location X with the highest amount of pollution and the other locations. The limitation of this project was that the data could not help to significantly determine that location had the highest chronic effect of human health. The data could only give the location that had the highest mean of pollution.

 

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