Complete Randomized Design (CRD) in R

 

1. Analyses of the Variance model as we have discrete variable

aku<-aov(POD~treatment, data=data_shahzad_4)

anova(aku)

## Analysis of Variance Table

## Response: POD

## Df             SumSq         MeanSq             F value         Pr(>F)

## treatment     3 864         288.00                 0.4092         0.7467

## Residuals     92               64746                 703.76

2. Multiple comparisons test

aov.out<- aov(POD~treatment, data=data_shahzad_4)

LSD.test(aov.out,"treatment", console = TRUE)

Study: aov.out ~ "treatment"

## LSD t Test for POD

## Mean Square Error: 703.758

## treatment, means and individual ( 95 %) CI

##                     POD                         std         r         LCL             UCL             Min             Max

## Compost     258.4262         26.64398     24         247.6714         269.1811     227.15     292.78

## Control         259.8725         22.40901     24         249.1177         270.6273     231.29     288.78

## Hydropriming 261.4633     30.43338     24         250.7085         272.2182     214.31     299.67

## Potassium nitrate 266.3896 26.01492     24         255.6347         277.1444     236.12     292.78

### Alpha: 0.05 ; DF Error: 92

## Critical Value of t: 1.986086

## least Significant Difference: 15.20965

## Treatments with the same letter are not significantly different.

## POD groups

## Potassium nitrate 266.3896 a

## Hydropriming 261.4633 a

## Control 259.8725 a

## Compost 258.4262 a