Most statistics and data science textbooks use the letter n to represent this number, and sometimes, they call it the number of observations.
The number of distinct data points depends on how the unit of data is defined in the dataset. In tabular datasets, this number is the number of rows.

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- Number of data points (instances)
- Attributes (variables)
- Types of attributes (variables)
- Number of attributes (variables)
- Statistical measures

Characteristics of a dataset

Number of data points (instances)

A datapoint, instance, sample, or observation, is a unit of data in a dataset.
When datasets are tabular, $x_{ij}$ usually represents the value of the $j$th variable (attribute) in the $i$th data point, where $i=1,2,...,n$ indicates the index of the variable and $j=1,2,...,p$ identifies the variable. This way, a dataset can be represented as an $n\times p$ matrix X, where the row (or vector) $x_i$ represents a datapoint that consists of the $p$ values of $x_{i1}, x_{i2}, x_{i3}, \dots , x_{ip}$ corresponding to each variable.
$$X=\begin{bmatrix}
    x_{11} & x_{12} & x_{13} & \dots  & x_{1p} \\
    x_{21} & x_{22} & x_{23} & \dots  & x_{2p} \\
    \vdots & \vdots & \vdots & \ddots & \vdots \\
    x_{n1} & x_{n2} & x_{n3} & \dots  & x_{np}
\end{bmatrix}
=\begin{bmatrix}
    x_1^T \\
    x_2^T \\
    \vdots \\
    x_n^T \\
\end{bmatrix}$$ 

Datapoint

Most statistics and data science textbooks use the letter p to represent this number, and sometimes, they call it the number of covariates.
In tabular datasets, this number is the number of columns.

Number of attributes/variables/predictors/independent variables/features

• mean

• median

• mode

• percentiles

• range

• variance

• standard deviation

• mean squared error

• consistency

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