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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.
The paired t-test is one of the most commonly used statistical tests for comparing two related measurements. It determines whether the mean difference between paired observations is statistically significant. This test is widely applied...
The Student’s t-test is one of the most widely used statistical methods for comparing means. It helps determine whether the observed difference between sample means is statistically significant or simply due to random sampling...
A proportion test is a statistical method used to compare proportions or percentages between one or more groups. It helps determine whether observed differences in proportions are statistically significant or simply due to random...
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...