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These assumptions ensure that our sampling distribution is normal when working with two means. That way, we can use z-scores / t-scores!
#1: Both samples are randomly selected from the population.
#2: Both sample sizes (n1 and n2) is less than or equal to 10% of their respective population sizes.
#3: Both sample sizes (n1 and n2) are greater than or equal to 30, or the populations themselves are normally distributed.
- Once sample size reaches 30, the Central Limit Theorem ensures that the sampling distribution will be normal.
- If the underlying population distribution is normal, then our sampling distribution will automatically be normal!
#4: Both samples are independent of each other.
