Parametric Test

Test Parametric or Parametric Test is a statistical method used to compare two or more groups of data that have a normal distribution. This test is used to determine the significance of differences between groups of data and allows conclusions to be drawn about whether there are statistically significant differences between groups.

The Parametric test is based on comparing the means and variances of two or more groups. The test calculates a t-statistic, which is a measure of the difference between group means. If the t-statistic value exceeds the critical value corresponding to the significance level, then we can conclude that the differences between the means of the two groups are statistically significant.

One of the advantages of the Parametric test is its ability to take into account sample size and distribution, which allows for more accurate results compared to non-parametric methods. However, this test may be less accurate for small samples and when there are outliers in the data.

Overall, the Parametric test is an important tool for analyzing data and drawing valid conclusions about differences between groups. It allows you to determine whether differences are statistically significant and make decisions based on this in various fields such as medicine, business and education.

A parametric test is a statistical test that is used to determine the difference between two means using a Gaussian distribution. This test is the most common method for comparing two samples and is used in many fields such as medicine, psychology, business, etc. The method is that it is necessary to calculate the difference between the variables under consideration by comparing their average values ​​(we can compare this if they are equal). Data statistics show whether a sample differs from the overall theoretical value by a distribution using a normal curve plot on which experimental points are superimposed. If they are scattered throughout