Category: Methods

Normality Test in R 0

Normality Test in R

Normality Test in R:-In statistics methods is classified into two like Parametric methods and Nonparametric methods. The majority of the test like correlation, regression, t-test, and analysis of variance (ANOVA) assume some certain characteristics about...

correlation analysis in r 0

Correlation Analysis in R?

Correlation Analysis in R? In correlation analysis, we estimate a sample correlation coefficient based on experimental data, in most cases the Pearson Product Moment correlation coefficient is used to find the relationships. The sample...

Random Forest Model in R 0

Random Forest Model in R

The random forest model in R is a highly useful tool in analyzing predicted outcomes for a classification or regression model. The main idea is how explanatory variables will impact the dependent variable. In...

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...