Category: Methods

Contingency Table in R 0

Contingency Table in R

Contingency Table in R, In the test hypothesis, it is usually assumed sample drawn from a known distribution like binomial, Poisson, normal, etc…It is an assumption but good to check our assumption holds true...

discriminant analysis in r 6

Discriminant Analysis in R

Discrimination tests are more important in sensory analysis. The main idea behind sensory discrimination analysis is to identify any significant difference or not. 

Here are the details of different types of discrimination methods and p-value calculations based on different protocols/methods. 

This article will discuss different types of methods and discriminant analysis in r.

Proportion test in R 1

Proportion test in R

How to do a proportion test in R and what are the conditions that need to meet for the proportion test? The sampling method for each population is simple random sampling. The samples are...

One sample analysis in R 2

One Sample Analysis in R

One sample analysis in R-In statistics, we can define the corresponding null hypothesis  (H0) as follow: Hypothesis: 1.      H0:m=μ,  2.      H0:m≤μ 3.      H0:m≥μ The corresponding alternative hypotheses (Ha) are as follow: 1.      Ha:m≠μ (different) 2.      Ha:m>μ (greater) 3.      Ha:m<μ (less) Outlier Detection: Out.fun<-function{abs(x-mean(x,na.rm=TRUE))>3*sd(x,na.rm=TRUE)} ddply(data,.(sample, variable),transform,outlier.team=out.fun(value)) column heading...