Descriptive statistics are used to summarize and describe the characteristics of a sample or population, such as measures of central tendency, variability, and correlation. Inferential statistics, on the other hand, are used to make predictions and draw conclusions about a population based on a sample of data.

The NPC displays the central tendency and variability of a dataset and can show deviations from normal distribution, but it does not include information about the sample size.

The standard deviation is the most commonly used measure of variability in inferential statistics because it is sensitive to variations within a dataset and can help estimate the parameters of a population.

Measures of Central Tendency in statistics refer to the ways of summarizing a set of data into a single value that represents the center or typical value of the data. It includes three measures: mean, median, and mode.

Correlation is a statistical measure that describes the relationship between two variables, indicating how closely they are related to each other.

Outliers can significantly affect the mean as it takes into account all the values in the dataset. A single outlier can shift the mean significantly towards its direction.

The range is computed as the difference between the highest and the lowest score in a dataset.

The median is the most suitable measure of central tendency for skewed data because it is not influenced by extreme values and represents the value at the midpoint of the data.

The NPC is a graphical representation of the probability distribution of a set of scores, displaying the frequency of scores in the form of a curve.

The mode is the most frequent observation or value in a dataset.