Student's t-test

Terms from Statistics for HCI: Making Sense of Quantitative Data

Student's t-test is a statistical test that is usually used to compare the means of two or more groups to see if they are different. For example, comparing the average task completion time for a group of people using an old version of a system vs that of a second group using a new improved user interface. It is calculated by taking the difference of the means and dividing by an estimate of the standard deviation of the difference obtained from the standard deviation of the sample for each of the groups.
      t = (μ1 – μ2) / √(σ12/N1 – & sigma;22/N2)
The theoretical distribution of the value of this t-test follows the Student's t distribution. The t-test depends on the data being approximately Normal, but is fairly robust if this is not perfect.
The theoretical t distribution is a Normal variable divided by the square root of an independent variable with the Chi-squared distribution. This is because the sample variance follows the chi-squared distribution.

Used in Chap. 13: page 150

Also used in hcistats2e: Chap. 1: page 4; Chap. 4: pages 51, 55, 59; Chap. 8: page 89; Chap. 9: page 108; Chap. 10: page 115; Chap. 14: page 164; Chap. 15: page 189

Also known as: t-test

Used in glossary entries: approximately Normal, chi-squared distribution, mean (μ), sample variance, standard deviation (s.d., σ), standard deviation of the sample, Student's t distribution, task completion time, theoretical distribution