Combined Analysis

Univariate analysis looks at one variable at a time (like checking how a group of people's ages are distributed) to understand overall patterns such as average or range.

Bivariate analysis involves comparing two variables (such as age and income) to see if there's a relationship between them.

Used together, these methods help identify trends in the data and provide a foundation for asking deeper questions or making predictions.

For example, with the first one analysts might show that customers aged 30 to 40 are the most common in a dataset, while with the second analysis they could reveal that this same age group also tends to spend the most per purchase—leading to valuable marketing or sales insights.