Answer:
The type 1 error here is a. Deciding that the absorption rates are different, when in fact they are not.
Step-by-step explanation:
A type I error is the rejection of a true null hypothesis (also known as a "false positive" finding or conclusion).
More generally, a Type I error occurs when a significance test results in the rejection of a true null hypothesis. By one common convention, if the probability value is below 0.05, then the null hypothesis is rejected.
In inferential statistics, the null hypothesis is a general statement or default position that there is nothing significantly different happening, like there is no association among groups or variables, or that there is no relationship between two measured phenomena.