Mean: Sensitive to outliers, best for symmetric data | Median: Resistant to outliers, best for skewed data.

Standard Deviation: Measures spread using all data, sensitive to outliers | IQR: Measures spread of middle 50%, resistant to outliers.

Parameters: Describe populations, usually unknown | Statistics: Describe samples, used to estimate parameters.

Resistant: Not affected by outliers, e.g., median, IQR | Nonresistant: Affected by outliers, e.g., mean, standard deviation.

1. 5 x IQR: Based on quartiles, resistant to extreme values | Standard Deviations: Based on mean and standard deviation, sensitive to extreme values.

The average value, calculated by summing all values and dividing by the number of values.

The middle value when data is ordered. If there's an even number of data points, it's the average of the two middle values.

A measure of how much individual data points vary from the mean.

The interquartile range, representing the range of the middle 50% of the data (Q3 - Q1).

Data points that are unusually far from the rest of the data.

Resistance refers to a statistic's sensitivity to outliers. Resistant statistics are not greatly affected by extreme values.

We subtract 1 from 'n' (degrees of freedom) when calculating the sample standard deviation to make it a better estimator of the population standard deviation.

In a symmetric distribution, the mean and median are approximately equal. In a right-skewed distribution, the mean is greater than the median. In a left-skewed distribution, the mean is less than the median.

Quartiles divide a dataset into four equal parts. Q1 is the 25th percentile, Q2 (median) is the 50th percentile, and Q3 is the 75th percentile.

The mean is most appropriate for symmetric distributions without significant outliers, as it uses all data points and reflects the overall trend.