Use the sample mean to estimate each magnetic susceptibility, and the unbiased sample variance with denominator to estimate the repeatability of individual readings. In the numerical scale supplied by the paper,
If the repeated measurements have independent random errors, their mean estimates have standard errors
The difference and its estimated standard uncertainty are therefore
The separation is about standard errors. Under an approximately normal distribution model with no experimenter-dependent bias, Welch's t-test gives about statistical degrees of freedom and a two-sided p-value of . Thus there is modest evidence against equal underlying susceptibilities at a conventional significance level; overlap of the ranges of individual readings is not an adequate comparison of the means. Five readings per sample provide limited information about the error distribution.
Crucially, material and student exhibit complete confounding: each student measured only one sample. An experimenter-dependent systematic error could mimic the difference. Paramagnetism also depends on conditions such as temperature, so equal material alone does not guarantee equal readings without controlling those conditions. The defensible physical conclusion is the data suggest a difference, but do not establish different materials. Both students should measure both samples in randomized or alternating order, with calibration and temperature controlled, to separate a sample effect from an operator effect. No unit or scale factor absent from the original table has been invented.

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