Chapter 7. Hypothesis Testing: Introduction to Hypothesis Testing (Critical Region Approach
Assumptions of the z-test
The following assumptions are required to hold in order for a #z#-test to produce valid conclusions:
The process of inferential statistics heavily relies on the assumption that the sample being analyzed is representative of the larger population it is drawn from. Random sampling helps ensure the representativeness of the sample.
Two observations are said to be independent when the occurrence of one observation does not influence the chances of the second observation occurring.
The value of #\sigma# is unchanged by the treatment
When testing for a treatment effect, it is assumed that the amount of variability in the treated population is equal to the amount of variability in the untreated population.
Normal sampling distribution
When conducting a #Z#-test the Standard Normal Table is used to determine the boundaries of the critical region. This table can only be used when the central limit theorem holds and the distribution of sample means is normal.
Unlock full access
Request a demo account. We will help you get started with our digital learning environment.
Create demo account
Is your university not a partner?
Get access to our courses via Pass Your Math independent of your university. See pricing and more. Or visit omptest.org if jou are taking an OMPT exam.