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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...
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...
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...