doebioresearch (version 0.1.0)

crd: Analysis of Completely Randomized Design

Description

The function gives ANOVA, R-square of the model, normality testing of residuals, SEm (standard error of mean), SEd (standard error of difference), interpretation of ANOVA results and multiple comparison test for means

Usage

crd(data, trt.vector, MultipleComparisonTest)

Arguments

data

dependent variables

trt.vector

vector containing treatments

MultipleComparisonTest

0 for no test, 1 for LSD test, 2 for Duncan test and 3 for HSD test

Value

ANOVA, interpretation of ANOVA, R-square, normality test result, SEm, SEd and multiple comparison test result

Examples

# NOT RUN {
data<-data.frame(Treatments=c("T1","T2","T3","T4","T5","T6","T7","T1","T2","T3","T4","T5","T6",
"T7","T1","T2","T3","T4","T5","T6","T7"),
yield=c(25,21,21,18,25,28,24,25,24,24,16,21,20,17,16,19,14,15,13,11,25),
height=c(130,120,125,135,139,140,145,136,129,135,150,152,140,148,130,135,145,160,145,130,160))
#CRD analysis with LSD test for yield only
crd(data[2],data$Treatments,1)
#CRD analysis with LSD test for both yield and height
crd(data[2:3],data$Treatments,1)
# }