T-testing & Z-testing
Giving new meaning to the way modern analytics work, our incredible outsourcing solutions for T-testing and Z-testing have benefitted many global companies.
A T-test, also known as the ‘Student T-test’ is a statistical hypothesis test wherein the test statistic follows a Student’s T-distribution if the null hypothesis stands to be true. Being a simple and an easy to use method, this test is one of the most commonly used statistical techniques. Moreover, it is extremely flexible and accommodating under a wide array of circumstances.
This testing is usually done in scenarios where you have a limited sample size (n < 30) with the proviso that the variables are normally distributed and the disparity of scores in the two groups is not constantly dissimilar. It is also a good method to be adopted when the populations’ standard deviation is not known.
In cases where the standard deviation is known, the best approach would be to go for Z-testing. This is done to compare sample and population means in order to ascertain whether there is a noteworthy dissimilarity between them or not. This testing is often performed when the sample size is large (n > 30).
Based on the requirements and the problems that your business is facing, we will choose the best approach and apply it to your business. Since the Z-test often necessitates certain conditions to be reliable, it is not as widely used as the T-test.
After properly assessing the population, the standard deviation and many such imperative aspects of statistical hypothesis testing, we will provide the best solutions for you through the brilliant pool of human resources and the state of the art technologies and methodologies adopted by Research2Systems.
Contact us today and find out how T-testing and Z-testing can assist your business to reach to the apex.
