Performing Z-tests
When making decisions, it is important to know whether decision error can be controlled or measured. In other words, we want to prove that the hypothesis formed is unlikely to have occurred by chance, and it is statistically significant. In hypothesis testing, there are two types of hypothesis: null hypothesis and alternative hypothesis (research hypothesis). The purpose of hypothesis testing is to validate whether the experiment results are significant. However, to validate whether the alternative hypothesis is acceptable, the alternative hypothesis is deemed to be true if the null hypothesis is rejected.
A Z-test is a parametric hypothesis method that can determine whether the observed sample is statistically significantly different from a population with known standard deviation, based on standard normal distribution.
Getting ready
Ensure that you installed R on your operating system.
How to do it…
Perform the following steps to calculate the Z-score:
First, collect the volume...
