# A tibble: 39 × 2
`Test Sample` `%Inhibition`
<chr> <dbl>
1 Leaves 57.0
2 Leaves 64.0
3 Leaves 57.4
4 Leaves 59.7
5 Leaves 45.4
6 Leaves 45.7
7 Leaves 51.6
8 Leaves 40.9
9 Leaves 58.4
10 Rhizomes 33.7
# … with 29 more rows
# ℹ Use `print(n = ...)` to see more rows
Df Sum Sq Mean Sq F value Pr(>F)
`Test Sample` 4 6902 1725.6 21.07 8.2e-09 ***
Residuals 34 2785 81.9
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Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Based on the ANOVA model the p-value is statistically significant (p<0.05), indicate that each group does not have the same average values.
Dunnett's test for comparing several treatments with a control :
95% family-wise confidence level
$Kortezor
diff lwr.ci upr.ci pval
Leaves-Kortezor -26.67793 -41.54715 -11.808715 0.00025 ***
Pericarp-Kortezor -32.29819 -47.16740 -17.428969 1.2e-05 ***
Rhizomes-Kortezor -43.91150 -58.78072 -29.042286 1.4e-08 ***
Seeds-Kortezor -12.49588 -27.36509 2.373339 0.11194
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Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
The Control group (Kortezor) scored significantly higher values compared to Leaves, Pericarp, and Rhizomes with p-values result of 0.00039, 0.000011, and 0.00000001, respectively. Moreover, the difference between Kortezon and Seeds does not differ significantly with a p-value result of 0.1115.