My dataset contains over 10.000+ service management tickets. My population is right-skewed. I took 1000 samples with sample size n = 30 from the dataset. Because of the central limit theorem the sampling distribution is normally distributed.
I want to prove that incidents are handled within 14 days on average. My hypothesis is as follows:
H0: incidents are not processed within 14 days on average
H1: incidents are processed within 14 days on average
I was assuming that for sample sizes n > 30 the z-test is the best method to test my hypothesis. But is this correct? Isn't a t-test or maybe another test better?
I want to prove that incidents are handled within 14 days on average. My hypothesis is as follows:
H0: incidents are not processed within 14 days on average
H1: incidents are processed within 14 days on average
I was assuming that for sample sizes n > 30 the z-test is the best method to test my hypothesis. But is this correct? Isn't a t-test or maybe another test better?