bonnyopiyo/Complete-Randomized-Design-using-R

-Simplest design to use. -Design can be used when experimental units are essentially homogeneous. -Because of the homogeneity requirement, it may be difficult to use this design for field experiments. -The CRD is best suited for experiments with a small number of treatments.

Complete-Randomized-Design-using-R

-Simplest design to use. -Design can be used when experimental units are essentially homogeneous. -Because of the homogeneity requirement, it may be difficult to use this design for field experiments. -The CRD is best suited for experiments with a small number of treatments.

Randomization Procedure -Treatments are assigned to experimental units completely at random. -Every experimental unit has the same probability of receiving any treatment. -Randomization is performed using a random number table, computer, program, etc.

R-script

Below is a step by step guide on how to obtain CRD Analysis using R

Importing Data Set to R, the data set is annexed in the files here as CRD.xlsx(check out and download)

library(readxl)

CRD <- read_excel("C:/Users/Boss IT Solutions/OneDrive/CRD.xlsx", col_types = c("text", "numeric"))

View(CRD)

Fitting of linear model

model <-lm(CRD$Yield ~ CRD$Treatment)

Obtains R Square and other statistics of fitted model

summary <-summary(model)

Carryout ANOVA

anova <-anova(model) anova

This is a Simple way of obtaining CRD Analysis