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A z-test is used when comparing a sample mean to a population mean, and the population standard deviation is known.
z-test because the distribution is in a z_scale
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NHST
In a z-test, the parameters of the population are known. There is no estimation, there's not a family of sampling distributions, the distribution is just a perfectly normal.
If you were doing null hypothesis significance testing, we would expect to get, z of 0.
The actual cut-off in the z distribution with a non-directional test with alpha 0.05, is 1.96.
So if we get beyond 1.96 in a z distribution, that's going to be significant at the level of alpha .05.