So, you have decided to find someone to date. You are excited about it but you have don't know where to find a perfect person who shares interests as you.
Its the same with data. You have this uncleaned data from yesterday that you want to polish it up. What do you do with it? You know what you want but you have no idea how to get there yet. Do you need to change the way you view the data or should you change the data to view how you want? Well, the answer is both. When dealing with data, you need to have perspectives.. Lots of them! So lets jump into our second analysis with data and see what you can do! :)
QUESTION EVERYTHING:
To find that perfect soul mate, you need question everything. Minor imperfections (initially ;-)) are acceptable (Nothing is perfect in this world) but we all strive to achieve perfection. Every data has a story to tell.
Lets start with WHAT IS DATA? Wikipedia defines data as a set of values of qualitative or quantitative variables. So what does that mean? In layman terms, it means anything and everything that has a value attached to it is DATA. For example, you are a repository of data yourself! How? Your name is a value. Your height, weight, qualities, etc, everything is a value. You are an entire source of unique information for others. Look around you. Everything is filled with data. From a tiny stone (well the stone has a type/name/color/texture which is all data) to the planets and solar system. Just everything around you is data.
Since I am a woman, when I see another woman, I judge her on the outside by the data(read: vital stats). Who doesnt? ;-) Probably something like this!
Lets use the above example to define the two major categories of data:
Qualitative Data: The name gives it away. Anything that refers to the quality of something is Qualitative Data. In the above picture, we can consider the picture color (black & white), the model body type (you may say well built?), the model's facial expression (here fake smile? ;-)) .. Now you get the idea what a qualitative data defines.
Quantitative Data: Quantitative Data is something that is measured up. Something, that is defined by a number. In the picture, the model's vital stats (bust size, hip size, etc) are all quantitative data.
There might be also other different categories of data like :
Categorical Data: Sometimes you need to describe a category or condition of an item. Here, in the picture, you can say, she is a "young" woman. She is a "tall" woman. She a "healthy" woman.
Discrete Data: Data that has gaps in it. Discrete data is always a whole number. There is definitely only 1 woman in this picture. There cannot be 1.5 women (even though she might weigh an average weight of 1.5 women).
Continuous Data: Numerical data with a continuous range. The lady in this picture is probably 25 years and 12 days old. That is a sort of continuous data. In continuous data, all sorts of values is possible.
I am confident that we have done enough preparation to actually test the waters and go dive into a date with Data. What do you think?
Its the same with data. You have this uncleaned data from yesterday that you want to polish it up. What do you do with it? You know what you want but you have no idea how to get there yet. Do you need to change the way you view the data or should you change the data to view how you want? Well, the answer is both. When dealing with data, you need to have perspectives.. Lots of them! So lets jump into our second analysis with data and see what you can do! :)
QUESTION EVERYTHING:
To find that perfect soul mate, you need question everything. Minor imperfections (initially ;-)) are acceptable (Nothing is perfect in this world) but we all strive to achieve perfection. Every data has a story to tell.
Lets start with WHAT IS DATA? Wikipedia defines data as a set of values of qualitative or quantitative variables. So what does that mean? In layman terms, it means anything and everything that has a value attached to it is DATA. For example, you are a repository of data yourself! How? Your name is a value. Your height, weight, qualities, etc, everything is a value. You are an entire source of unique information for others. Look around you. Everything is filled with data. From a tiny stone (well the stone has a type/name/color/texture which is all data) to the planets and solar system. Just everything around you is data.
Since I am a woman, when I see another woman, I judge her on the outside by the data(read: vital stats). Who doesnt? ;-) Probably something like this!
Lets use the above example to define the two major categories of data:
Qualitative Data: The name gives it away. Anything that refers to the quality of something is Qualitative Data. In the above picture, we can consider the picture color (black & white), the model body type (you may say well built?), the model's facial expression (here fake smile? ;-)) .. Now you get the idea what a qualitative data defines.
Quantitative Data: Quantitative Data is something that is measured up. Something, that is defined by a number. In the picture, the model's vital stats (bust size, hip size, etc) are all quantitative data.
There might be also other different categories of data like :
Categorical Data: Sometimes you need to describe a category or condition of an item. Here, in the picture, you can say, she is a "young" woman. She is a "tall" woman. She a "healthy" woman.
Discrete Data: Data that has gaps in it. Discrete data is always a whole number. There is definitely only 1 woman in this picture. There cannot be 1.5 women (even though she might weigh an average weight of 1.5 women).
Continuous Data: Numerical data with a continuous range. The lady in this picture is probably 25 years and 12 days old. That is a sort of continuous data. In continuous data, all sorts of values is possible.
I am confident that we have done enough preparation to actually test the waters and go dive into a date with Data. What do you think?
