## Type I and Type II errors in Statistics

Type I and Type II Errors In hypothesis testing, there are two possible errors we can make: Type I and Type II errors. If you do reject your null hypothesis, then it is also essential that you determine whether the size of the relationship is practically significant.The hypothesis test procedure …

## Significance level in Statistics: why do researchers use 5%?

Significance Level The significance level in statistics is the level of probability at which it is agreed that the null hypothesis will be rejected. In academic research, usually, a 0.05 level of significance (level of significance) is used. The level of significance is also called a level of risk. Significance …

## Estimation and Types of Estimation in Statistics

The Post is about Introduction to Estimation and Types of Estimation in the Subject of Statistics. Let us discuss Estimation and Types of Estimation in Statistics. The procedure of making a judgment or decision about a population parameter is referred to as statistical estimation or simply estimation.  Statistical estimation procedures …

## Rules for Skewed Data Free Guide

Lack of Symmetry Skewness is the lack of symmetry (lack of normality) in a probability distribution. The skewness is usually quantified by the index as given below $$s = \frac{\mu_3}{\mu_2^{3/2}}$$ where $\mu_2$ and $\mu_3$ are the second and third moments about the mean. This index formula described above takes the …