Low participation or presence of outliers in the data can skew statistical summaries, affecting the representation of student performance. Outliers can disproportionately affect metrics like mean and range, leading to misinterpretations of typical student performance. For instance, unusually high or low scores may inflate or deflate the mean, misleading educational stakeholders about the group’s actual performance level . Low participation limits data robustness, increasing variability impact, potentially magnifying outliers’ consequences. Evaluative reliance on median and interquartile range

The range provides a basic understanding of the spread of Math scores by indicating the difference between the highest and lowest scores, which is 95 to 55 . This helps identify the extent of variation in student performance at a glance. However, its limitation lies in its sensitivity to outliers; a single extreme score can disproportionately affect the range. It also doesn't provide information about the distribution among scores, unlike mean or standard deviation, making it less informative about overall performance trends or typical student outcomes .

Calculating the mean and standard deviation of English scores offers insights into central performance and score variability. The mean provides a single measure of the class's average performance, while the standard deviation assesses score variability around this average. Understanding these metrics can highlight whether most students are performing consistently or if there is significant variation, which may indicate the need for differentiated learning approaches . If the standard deviation is high, indicating diverse performance levels, targeted interventions may be necessary to address di