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Measure of Central Tendency:

The measure of central tendency represents a single value that describes the center of the data set. In other words, it gives an idea about where the data points are clustered around. The three most commonly used measures of central tendency are:

1. Mean: It is the arithmetic average of all the values in a data set. It is calculated by adding up all the values and dividing by the total number of values.

2. Median: It is the middle value in an ordered data set. To find the median, the data set is arranged in ascending or descending order, and the middle value is chosen.

3. Mode: It is the value that occurs most frequently in a data set. If no value occurs more than once, then there is no mode.

Measure of Dispersion:

The measure of dispersion represents how spread out the data points are from the center of the data set. The three most commonly used measures of dispersion are:

1. Range: It is the difference between the largest and the lowest values in a data set. It gives an idea about the extent of the variability in the data.

2. Variance: It is the average of the squared differences from the mean. It measures how far the data points are from the mean.

3. Standard deviation: It is the square root of the variance. It gives an idea about how much the data points vary from the mean.

Correlation:

Correlation refers to the relationship between two or more variables. It measures how closely the variables are related to each other. It can be positive or negative. Positive correlation means that as one variable increases, the other variable also increases. Negative correlation means that as one variable increases, the other variable decreases. Correlation is measured by the correlation coefficient, which ranges from -1 to +1. A correlation coefficient of +1 means a perfect positive correlation, whereas a correlation coefficient of -1 means a perfect negative correlation. A correlation coefficient of 0 means no correlation.

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