Z - Test

Presented by Aminata E. Bamba Adewumi

Z-test

Definition

A Z-test is a statistical test used to establish whether two population means are unlike when the variances are known and the sample size is big.

Hypothesis test that follows a normal distribution under the null hypothesis (Ho) and stated the alternative hypothesis, alpha, and z-score

Under the Central Limit Theorem, if the sample size is greater than or equal to 30 (n >= 30), the sampling distribution will approximate a normal distribution. Therefore, we need to know the mean of the sampling distribution and the standard deviation to be able to calculate the normal distribution.

The Standard Deviation (σ), Sample Size (x̄), and Population mean (μ) should be known.

Z score table is then needed to calculate the probability or percentage of a value occurring in a normally distributed data set

Z-Test - One Sample

References:

Chen,J. (2019). Z-test. Investopedia, Retrieved from https://www.investopedia.com/terms/z/z-test.asp

Doseman-Flaws, D. (n.d). Sample problems of Normal Curve. Retrieved from http://www.deeannef.com/apstats/normal/problems.htm

Glen, S. (2015). Hypothesis Testing Example #1 Z Test. Retrieved from https://www.youtube.com/watch?v=FU9UR9XVZwc

Salkind, N. J. (2017). Statistics for people who (think they) hate statistics (6th ed.)

Z-test. https://en.wikipedia.org/wiki/Z-test

Z-test Formula: https://www.slideshare.net/MuhammadAnas96/ztest-with-examples

Z-test Table: http://www.z-table.com/