The mean is easily affected by extreme values, making it more sensitive to outliers compared to the median and mode.

The range is the difference between the maximum and minimum values in a dataset.

Variance is the sum of squared deviations from the mean divided by the number of observations.

The coefficient of variation is a measure of relative variability, calculated by dividing the standard deviation by the mean.

A histogram is a graphical representation that shows the frequency distribution of data by dividing the range of values into bins and displaying the number of observations in each bin.

The cumulative frequency distribution shows the total frequency of observations up to and including a given value.

The mode is the value that appears most frequently in a dataset.

The median is the middle value when the data is arranged in ascending order. If there are an even number of observations, the median is the average of the two middle values.

The quartiles divide the data into four equal parts: the first quartile (Q1), the second quartile (Q2 or median), the third quartile (Q3), and the fourth quartile (Q4).

Mean Absolute Deviation (MAD) is the average of the absolute deviations from the mean.

The interquartile range (IQR) is the difference between the third quartile (Q3) and the first quartile (Q1).

The median is less affected by outliers compared to the mean and mode because it is based on the middle value of the dataset.

The standard deviation is a measure of variability, indicating how spread out the data is around the mean.

A normal distribution is characterized by both symmetry around the mean and a bell-shaped curve.

The empirical rule states that, in a normal distribution, approximately 68% of data falls within one standard deviation of the mean.