The mean is highly sensitive to extreme values or outliers, which can significantly skew the result and misrepresent the central tendency of a dataset. In contrast, the median and mode are more robust against outliers. While the mean is mathematically useful, its susceptibility to extreme scores makes it less reliable in skewed distributions compared to other measures.

Quartile deviation, also known as the semi-interquartile range, is a measure of statistical dispersion. It is calculated by taking the difference between the upper quartile (Q3) and the lower quartile (Q1) and dividing that value by two. It is particularly useful for describing the spread of data while minimizing the impact of extreme outliers.

A nominal scale is the most fundamental level of measurement. It is used to label or categorize data into distinct groups without implying any quantitative value, hierarchy, or order. Examples include gender, eye color, or nationality, where the categories are mutually exclusive and exhaustive but cannot be ranked.

In statistics, frequency refers to the number of times a particular value or data point appears in a set of observations. Calculating frequency is a fundamental step in descriptive statistics, allowing researchers to organize raw data into frequency distributions, which help in visualizing patterns, trends, and the overall distribution of the collected variables within a study.

The range is a fundamental measure of dispersion in statistics. It is calculated by subtracting the lowest value from the highest value in a given set of data. This provides a quick, albeit simple, indication of the spread or variability of the data points within the distribution.

Standard deviation is the most widely used measure of variability because it accounts for every data point in the set and provides a precise indication of how much the values deviate from the mean. Unlike the range, which only considers the extreme values, standard deviation offers a comprehensive view of data dispersion, making it essential for inferential statistics and comparative analysis in research.

Measures of central tendency, such as the mean, median, and mode, identify the center or typical value of a dataset. In contrast, the standard deviation is a measure of dispersion or variability. It quantifies how much the individual data points deviate from the mean, providing insight into the spread of the data rather than its central location.

The median is the middle value of a data set when the numbers are arranged in ascending or descending order. It effectively splits the data into two equal parts, with 50% of the observations falling below the median and 50% falling above it. This makes it a robust measure of central tendency, especially in skewed distributions where extreme values might otherwise distort the mean.

The Intelligence Quotient (IQ) is calculated using the formula: (Mental Age / Chronological Age) * 100. If the mental age and physical (chronological) age are equal, the ratio is 1, which, when multiplied by 100, results in an IQ score of 100, representing average cognitive development.

In multiple-choice questions, distracters are the incorrect options provided to mislead the test-taker and increase the difficulty of identifying the correct answer. They are intentionally designed to appear plausible, thereby testing the examinee's true understanding of the subject matter rather than relying on simple elimination or guessing.