doebioresearch (version 0.1.0)

fcrd2fact: Analysis of Factorial Completely Randomized Design for 2 factors

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

fcrd2fact(data, fact.A, fact.B, Multiple.comparison.test)

Arguments

data

dependent variables

fact.A

vector containing levels of first factor

fact.B

vector containing levels of second factor

Multiple.comparison.test

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 for both the factors as well as interaction.

Examples

# NOT RUN {
data(factorialdata)
#Analysis of Factorial Completely Randomized design along with Dunccan test for Yield only
fcrd2fact(factorialdata[5],factorialdata$Nitrogen,factorialdata$Phosphorus,2)
#Analysis of Factorial Completely Randomized design along with Dunccan test for Yield & Plant Height
fcrd2fact(factorialdata[5:6],factorialdata$Nitrogen,factorialdata$Phosphorus,2)
# }