2 How to Think About Data
When a data analyst thinks about data they will likely view that data in a table format with some visualization of that data
A data analyst likely thinks of mathematical and statistical abstractions. This may involve putting things in terms of relationships or associations, perhaps theoretical mathematical models that take various forms; linear, quadratic, non-parametric.
In general, we should have the following in our minds when thinking of variables in our data
- quantitative vs. qualitative
- continuous vs. discrete
- numerical vs. categorical
- scales: ratio, interval, ordinal, nominal
- dependent vs. independent
- descriptors (predictors) vs, response
- input vs. output
- correlations
- theoretical models (linear, quadratic, etc.)
Let’s define so of these terms
- Quantitative:
- Relating to, measuring, or measured by the quantity of something rather than its quality.
- Example
- The folllowing are all examples of quantitative data
- weight in pounds
- length in centimeters
- dollar value of a company’s stocks
- Qualitative:
- Relating to, measuring, or measured by the quality of something rather than its quantity.
- Continuous:
- Discrete:
- Numerical: