Which among the following is used for judging the significance
of several statistical measures, particularly the mean?

The correct option is Z-test.

In statistics, different tests are used to determine the significance of various statistical measures depending on the sample size, data distribution, and parameters being compared.

A Z-test is a statistical test used to determine whether two population means are different when the variances are known and the sample size is large (typically n ≥ 30). It is specifically used for judging the significance of several statistical measures, particularly the mean, by comparing a sample mean to a known population mean or comparing two sample means.

Let us briefly look at why the other options are not the primary choice for this specific definition:
1. χ²-test (Chi-Square test): This is a non-parametric test used primarily to determine the association between categorical variables or the goodness of fit, rather than comparing means.
2. F-test: This test is primarily used to compare the variances of two populations or in the analysis of variance (ANOVA) to compare multiple group means by analyzing variances.
3. Kruskal-Wallis test: This is a non-parametric alternative to one-way ANOVA used to compare three or more independent groups when the data do not follow a normal distribution.

Therefore, the Z-test is the standard statistical test used for judging the significance of statistical measures, particularly the mean, under large sample conditions.