Effect of Mouthwash on E-Coli Bacteria

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Interpreting and Evaluating

Mann-Whitney U test

I have decided that I would like to use the Mann-Whitney U test to interpret and evaluate my data. This is because I would like to compare data sets to see whether the medians from the different brands of mouthwash I investigated were significantly different from one another as I have unmatched data and this would help me to demonstrate their differences clearly.

Effect of Mouthwash on E-Coli Bacteria

Results For E-Coli

Average Results

Ranking the Data

1) Mouthwash C

2) Mouthwash B

3) Mouthwash A

4) Mouthwash D

Σ R1 (Mouthwash C) = 55.02

Σ R2 (Mouthwash B) = 39.07

Σ R3 (Mouthwash A) = 24.23

Σ R4 (Mouthwash D) = 19.16

Comparison of Mouthwash A against B:

U1 = ( n    x n     ) + (0.5n   ) (n   + 1) - Σ R

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U1 = (10  x 10) + (0.5[10]) (10 + 1) – 24.23 = 130.77

U2 = ( n    x n     ) + (0.5n   ) (n   + 1) - Σ R

U1 = (10  x 10) + (0.5[10]) (10 + 1) – 39.07 = 115.93

Smaller Value = 115.93

Critical Value for U  = 23

115.93 > 23

Comparison of Mouthwash A against C:

U1 = ( n    x n     ) + (0.5n   ) (n   + 1) - Σ R

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Statistical test only** A worked example of the Mann-Whitney U test that has been calculated well but has not been interpreted at all by the candidate. The statistic has been used correctly and calculated using the formulae for large sample size. A faster method is available for the small sample size used. To improve- The real point of carrying out statistical tests is to see if there is true significance in the data collected and then interpret and evaluate the experiment accordingly. This candidate has unfortunately not discussed the meaning of the statistic at all. If the U value is equal to or less than that in the U value table the null hypothesis can be rejected. The difference in these samples is significant at the 2% level.