A statistical test used to compare three or more mean scores is known as:

The statistical test used to compare three or more mean scores is known as analysis of variance (ANOVA). This method is particularly useful in research scenarios where it is necessary to determine if there are statistically significant differences between the means of multiple groups.

ANOVA works by assessing the variability within each group and the variability between the groups. If the variability between the means is greater than the variability within the groups, it suggests that at least one group mean is different from the others, leading to further analysis or post-hoc tests to pinpoint the specific differences.

In contrast, chi-square tests are often used for categorical data to assess how likely it is that an observed distribution is due to chance. Multiple regression analysis is used to understand the relationship between one dependent variable and several independent variables, primarily focusing on predicting outcomes rather than comparing means. T-tests, on the other hand, are specifically designed to compare the means of two groups, rather than three or more, making it less suitable for questions involving multiple group comparisons. Thus, analysis of variance is the appropriate method for comparing mean scores across three or more groups.