# 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

ANOVA Comparison

              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                    
---
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 the Comparison of Plant Parts to Kortezor


  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 -41.51016 -11.845709 0.00038 ***
Pericarp-Kortezor -32.29819 -47.13041 -17.465963 1.9e-05 ***
Rhizomes-Kortezor -43.91150 -58.74373 -29.079279 2.0e-08 ***
Seeds-Kortezor    -12.49588 -27.32810   2.336345 0.11160    

---
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.

Correlation

For Leaves


Attaching package: 'dplyr'
The following objects are masked from 'package:stats':

    filter, lag
The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union
# A tibble: 9 × 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

Margin of Error for Leaves % Inhibition


    One Sample t-test

data:  Barrigaleaves$`%Inhibition`
t = 20.467, df = 8, p-value = 3.398e-08
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 47.33289 59.35301
sample estimates:
mean of x 
 53.34295

For Rhizomes

# A tibble: 9 × 2
  `Test Sample` `%Inhibition`
  <chr>                 <dbl>
1 Rhizomes               33.7
2 Rhizomes               44.0
3 Rhizomes               22.8
4 Rhizomes               41.6
5 Rhizomes               35.7
6 Rhizomes               36.1
7 Rhizomes               48.3
8 Rhizomes               38.2
9 Rhizomes               24.6

Margin of Error for Rhizomes % Inhibition


    One Sample t-test

data:  Barrigaleaves$`%Inhibition`
t = 12.969, df = 8, p-value = 1.184e-06
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 29.68861 42.53016
sample estimates:
mean of x 
 36.10938

For Seeds % Inhibition

# A tibble: 9 × 2
  `Test Sample` `%Inhibition`
  <chr>                 <dbl>
1 Seeds                  68.3
2 Seeds                  63.2
3 Seeds                  60.8
4 Seeds                  80.6
5 Seeds                  63.1
6 Seeds                  53.2
7 Seeds                  56.8
8 Seeds                  76.1
9 Seeds                  85.7

Margin of Error for Seeds % Inhibition


    One Sample t-test

data:  Barrigaleaves$`%Inhibition`
t = 18.277, df = 8, p-value = 8.26e-08
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 59.00538 76.04464
sample estimates:
mean of x 
 67.52501

For Pericarp % Inhibition

# A tibble: 9 × 2
  `Test Sample` `%Inhibition`
  <chr>                 <dbl>
1 Pericarp               58.6
2 Pericarp               49.9
3 Pericarp               45.6
4 Pericarp               49.8
5 Pericarp               37.8
6 Pericarp               37.0
7 Pericarp               51.7
8 Pericarp               48.7
9 Pericarp               50.5

Margin of Error for Pericarp % Inhibition


    One Sample t-test

data:  Barrigaleaves$`%Inhibition`
t = 21.032, df = 8, p-value = 2.743e-08
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 42.4902 52.9552
sample estimates:
mean of x 
  47.7227

For Kortezor % Inhibition

# A tibble: 3 × 2
  `Test Sample` `%Inhibition`
  <chr>                 <dbl>
1 Kortezor               94.3
2 Kortezor               79.1
3 Kortezor               66.6

Margin of Error for Pericarp % Inhibition


    One Sample t-test

data:  Barrigaleaves$`%Inhibition`
t = 10, df = 2, p-value = 0.009853
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
  45.59053 114.45125
sample estimates:
mean of x 
 80.02089