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A T-test determines if there is a statistical significant difference between 2 independent sample groups. This test asks – whetherthere is a difference between the means of 2 groups because of chance. This test is geared for a samll sample size of <30.

Key points of a T test:

  • All data points are independent.
  • The sample size is small. Generally, a sample size exceeding 30 sample units is regarded as large, otherwise small but that should not be less than 5, to apply t-test.
  • Sample values are to be taken and recorded accurately.

A Z-test is a statistcal calculation that can be used to compare populations to means to a sample. Basically, how far in standard deviation data points are from the mean of the data points. This test compares the sample to a defined population and is used for a large sample size n>30. This tests hypothesis iwhen the S.D. is known.

Key points of a Z-test:

  • All sample observations are independent
  • Sample size should be more than 30.
  • Distribution of Z is normal, with a mean zero and variance 1.

Z Test & T Test: Similarities & Differences. 2018 Retrieved from…

Surbhi, S. March 10, 2018. Difference between t-test and z-test. Retrieved from…