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# Types of Data

## Two Groups of Data

There are two group of data we can collect and analyze:

* Categorical
* Numerical

### Categorical (Qualitative)

Categorical data involves non-numeric data points in a dataset. These data points fall into one of the following characteristics.

1. **Ordinal (each data point can be sorted and ranked against each other)**

   *Example: Netflix Show's Personal Rating: hate, dislike, neutral, like, love*
2. **Nominal (each data point categorizes without inherent order, ranking, or level of strength)**

   *Example: Types of Dog Breeds: Westie, Samoyed, Golden Doodle*

### Numerical (Quantitative)

Numerical data involves numbers being collected for a dataset. The individual data points will have one of the following numeric characteristics.

1. Discrete
2. Continuous

*Numerical Data Type will be studied in its own page.*

{% hint style="warning" %}
The following is an example table containing qualitative data.
{% endhint %}

| Netflix Shows Watched | Personal Rating |
| --------------------- | --------------- |
| Brooklyn 99           | Good            |
| Superstore            | Meh             |
| Squid Game            | Meh             |
| Arcane                | Good            |
| Grey's Anatomy        | Boring          |

## Ordinal Categorical Data

With ordinal typed data, each data point can be ranked against each other.

> *In the example table, it is clear that the rankings go from Boring, Meh, to Good.*

### Key Points on Ordinal Data

* There must be ranking or distinct order
* The difference between each rank does not need to be numerically measurable
* The difference between each rank does not need to be evenly spaced out
* Numbers can be used as ordinal data, but it is only for ranking; the numbers should not provide mathematical analysis

## Nominal Categorical Data

With nominal typed data, each data point contains information with no ranking and no measurable distance between each data point.

> *In the example table above, the column containing "Netflix Shows Watched" is our nominal data*

### Key Points on Nominal Data

* Nominal data is often collected for classification (*example: favourite brand, participant's name, types of products produced in a factory*)


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