The number of prescriptions issued for antibiotics varied considerably between clinics.
The researchers wanted to find out whether there was a correlation between the number of prescriptions for each of the five antibiotics issued by a clinic and the percentage of urine samples containing resistant E. coli.
Spearman’s rank correlation test was used for this analysis.
The results of this analysis are shown in Table 2.
Table 2
Antibiotic |
Spearman’s rank correlation coefficient (rs) |
cephalosporin |
0.30 |
trimethoprim |
0.62 |
co-amoxiclav |
0.23 |
ampicillin |
0.71 |
quinolone |
0.44 |
Table 3 shows the critical values for rs at five levels of significance for the data collected in this study.
Table 3
 level of significance (p) |
0.20 |
0.10 |
0.05 |
0.02 |
0.01 |
 critical value of rs |
0.240 |
0.306 |
0.362 |
0.425 |
0.467 |
(i)
Suggest why the Spearman’s rank correlation test was used in this study.
[1]
(ii)
State a null hypothesis for the Spearman’s rank correlation test for this study.
[1]
(iii)
Using Table 2 and Table 3, identify which antibiotics showed a statistically significant correlation between the number of prescriptions and the presence of resistant strains of E. coli in urine samples. Give a reason for your answer.
[2]