In this video, get an explanation of qualitative and quantitative data with examples and observations.
- Now that we have an understanding of what Ware One does, let's start by defining the types of data that exist. Data can be separated into two categories, quantitative and qualitative. Quantitative data is data that can be measured in numerical form. Qualitative data is information that is gathered in non-numerical form that is typically descriptive and may be recoded to try and quantify its meaning. For example, quantitative data can include: the total annual sales of Ware One, employee performance review ratings on a scale of one to 10, a report with last month's profitability by store location.
Qualitative data includes things such as: summaries of written comments on customer cards collected from suggestion boxes at stores, results from interviews of store managers by an outside consultant, a paragraph taken from an employee's self-evaluation on a performance review. While the scripted statistics can be generated from both of these information sets, their potential applications and tools you use to draw conclusions from them can be quite different. Whether quantitative or qualitative, one phrase you'll hear often is that data is made up of a set of observations, the individual units being measured.
An observation can be: at the person level, for example, total dollars of merchandise sold by each salesperson. at the store level, for example, the profitability at each store location. at the country level, for example, the total GDP of each G7 country. or even time, for example, the temperature month by month for the last year. Let's dive into some of the stats and observations shown by our first case study.
- Qualitative vs. quantitative data
- Data analytics success stories
- Making predictions
- Asking the right questions
- Collecting data
- Understanding averages
- Sampling: pros and cons
- Cause and effect