In <strong>artificial-intelligence</strong>, you can end up dealing with all sorts of data.
For example —
</p>
<ul>
<li>maybe you are working with <em>photos</em> of people's faces;</li>
<li>maybe you are creating a list of <em>city names</em> of cities in the Near East;</li>
<li>maybe you have a list of <em>blood types</em> for all the patients that have visited the hospital;</li>
<li>maybe you are working with hospital patient data about how severe their pain was — ex: "<em>no pain</em>", "<em>mild pain</em>" , "<em>moderate pain</em>", "<em>it hurts bad</em>", and "<em><abbrtitle="oh my fucking! god">OMF!G</abbr>, this is the worst pain I have ever felt!</em>";</li>
<li>maybe you are looking at student <em>test scores</em>, graded oon a curve;</li>
<li>maybe you are recording the <em>birth order</em> (i.e., 1st child, 2nd child, 3rd child, etc) of all the people who work in a company;</li>
<li>maybe you are have <em>temperature<.em> records in °C (degree celsius);</li>
<li>maybe you are looking at the year every customer of a company was born;</li>
<li>maybe you are recording the <em>heights</em> of all the children in an elementary school;</li>
<li>maybe you are collecting the prices of houses in the city of Isfahan;</li>
<li>maybe you are are looking the number of photo each person takes every day on their mobile-phone;</li>
<li>etc etc etc.</li>
</ul>
</section>
<section>
<h2>Some Differences</h2>
<p>
Some of these data are very different than each other.
</p>
<p>
For example — if the price of one house is $1,000,000 and the price of another house is $500,000, then I can say the price of the first house is 2× (two times) bigger than the first.
(Since $1,000,000 = 2 × $500,000.)
</p>
<p>
But it is nonsense to say — <em>2 × type O+ blood</em>.
There is no concept of multiplying blood types.
</p>
<p>
The same is true for city names.
It is nonsense to say — <em>5 × the city of Vancouver</em>.
</p>
</section>
<section>
<h2>Types of Data</h2>
<p>
The <strong>levels of measurement</strong> are a way of understanding these <em>different types of data</em>.
An example of <strong>nominal data</strong> is <em>blood types</em>:
</p>
<ul>
<li>type A+</li>
<li>type A-</li>
<li>type B+</li>
<li>type B-</li>
<li>type AB+</li>
<li>type AB-</li>
<li>type O+</li>
<li>type O-</li>
</ul>
</section>
<section>
<p>
Another example of <strong>nominal data</strong> is <em>sex</em>:
</p>
<ul>
<li>female</li>
<li>male</li>
</ul>
</section>
<section>
<p>
Another example of <strong>nominal data</strong> is <em>family names</em>:
</p>
<ul>
<li>Alves</li>
<li>Beg</li>
<li>Chen</li>
<li>Cho</li>
<li>Choi</li>
<li>da Silva</li>
<li>Dickson</li>
<li>dos Santos</li>
<li>Esfahani</li>
<li>Fernández</li>
<li>Ferreira</li>
<li>García</li>
<li>Jung</li>
<li>Kang</li>
<li>Kerr</li>
<li>Kim</li>
<li>Krempeaux</li>
<li>Li</li>
<li>Liu</li>
<li>Martin</li>
<li>Müller</li>
<li>Pahlavi</li>
<li>Park</li>
<li>Parsi</li>
<li>Pereira</li>
<li>Rodríguez</li>
<li>Safavi</li>
<li>Sasani</li>
<li>Wang</li>
<li>Yun</li>
<li>Zhang</li>
<li><em>etc</em></li>
</ul>
</section>
<section>
<p>
Another example of <strong>nominal data</strong> is <em>hair color</em>:
</p>
<ul>
<li>brown</li>
<li>black</li>
<li>blond</li>
<li>gray</li>
<li>red</li>
<li><em>etc</em></li>
</ul>
</section>
<section>
<p>
Another example of <strong>nominal data</strong> is <em>cities</em>:
</p>
<ul>
<li>Beijing</li>
<li>Bangalore</li>
<li>Bangkok</li>
<li>Bogotá</li>
<li>Buenos Aires</li>
<li>Cairo</li>
<li>Chennai</li>
<li>Chicago</li>
<li>Chongqing</li>
<li>Dallas</li>
<li>Delhi</li>
<li>Dhaka</li>
<li>Guangzhou</li>
<li>Hyderabad</li>
<li>Kinshasa</li>
<li>Kolkata</li>
<li>Isfahan</li>
<li>Istanbul</li>
<li>Jakarta</li>
<li>Karachi</li>
<li>Lagos</li>
<li>Lahore</li>
<li>Lima</li>
<li>London</li>
<li>Los Angeles</li>
<li>Moscow</li>
<li>Nagoya</li>
<li>New York City</li>
<li>Osaka</li>
<li>Manila</li>
<li>Mexico City</li>
<li>Mumbai</li>
<li>Paris</li>
<li>Rio de Janeiro</li>
<li>São Paulo</li>
<li>Seoul</li>
<li>Shanghai</li>
<li>Shenzhen</li>
<li>Tehran</li>
<li>Tianjin</li>
<li>Tokyo</li>
<li>Toronto</li>
<li>Vancouver</li>
<li><em>etc</em></li>
</ul>
</section>
</section>
<section>
<h2>Operations</h2>
<p>
One way of understanding the <strong>levels of measurement</strong> is — what type of <strong>operations</strong> are meaningful and valid for that type of data‽
</p>
<p>
Here is a table that summarizes what <strong>operations</strong> are and are <em>not</em>meaningful and valid for each <strong>levels of measurement</strong> category:
