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CRD and RBD.Rmd

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+---
+title: "CRD and RBD"
+author: "Ian Leboo"
+date: "3/30/2022"
+output: html_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE, message = FALSE,warning = TRUE)
+```
+#1. CRD 
+##Example 1
+The data contains 4 tropical food stuffs A, B, C, and D tried on 20 chicks. Analyze the data at 5% level of significance.
+```{r}
+library(readxl)
+chicks <- read_excel("chics.xlsx")
+```
+
+Set the treatment column into factors
+```{r}
+chicks$Treatment<-as.factor(chics$Treatment)
+```
+
+Performing ANOVA
+##Method 1
+```{r}
+mod1<-aov(Weight~Treatment, data = chics)
+summary(mod1)
+```
+
+##Method 2
+```{r}
+chicksmodel<-lm(Weight~Treatment, data = chics)
+anova(chicksmodel)
+```
+##LSD Test
+```{r}
+library(agricolae)
+LSD.test(chicksmodel,"Treatment", console = TRUE)
+```
+##Example 2
+The data contains the amount of electricity used in KWh in three towns. Test at 5% significance whether the amount of electricity used is the same in the 3 towns.
+The steps are as example 1
+
+```{r}
+library(readxl)
+electricity <- read_excel("electricity.xlsx")
+
+#Set the treatment variable to factor
+electricity$Town<-as.factor(electricity$Town)
+model2<-aov(Electricity_Used~Town, data=electricity)
+summary(model2)
+```
+
+#2. RBD
+
+In this data, there are 4 blocks and 6 treatments.
+we are required to test whether treatments and blocks differ significantly at 5% significance level
+```{r}
+library(readxl)
+RBD <- read_excel("RBD.xlsx")
+```
+
+We will need to reshape the data into long format
+```{r}
+library(reshape2)
+library(dplyr)
+RBD_new<-RBD %>% 
+  melt() %>% 
+  mutate(Block=variable,
+         Treatments=as.factor(Treatments)) %>% 
+  select(-c(variable))
+```
+
+Performing ANOVA
+```{r}
+Model3<-aov(value~Treatments+Block, data=RBD_new)
+summary(Model3)
+```
+
+