Quantitative data measures and represents behaviors, actions, and other variables in the form of numerical data. This is an ideal method for describing patterns that can be quantified or expressed through numbers, such as size, length, amount, price, duration, and likelihood.
By collecting quantitative data, researchers can also make statistical generalizations, such as, 25% of men above the age of 50 ordered this product, or, The months of November and December see demand rise by up to 38%.
At its simplest, quantitative data is how researchers typically answer the basic questions of what, where, when, which, and who. However, a company's approach to quantitative data collection ultimately depends on the nature of its research, which can be one of the following-
This approach explains the status of variables through structured observational data collection. For example, researchers can focus on specific in-store behavior, such as foot traffic in specific spaces and areas.
This allows them to quantify the behaviors they observe and express them in counts or percentages. When it's time to analyze the data, the researchers can visualize the results using charts, graphs, or tables.
This approach seeks to gather quantitative data that highlights relationships between different events, actions, or entities.
- If the data shows two variables increasing or decreasing at the same time, this means they have a positive correlation.
- If one variable increases and the other decreases, this is a negative correlation.
- There is zero correlation, this means that there is no relationship whatsoever between two variables.
For example, by conducting surveys with customers, a business can discover a positive correlation between faster shipping times and higher customer satisfaction.
Experiments use the scientific method to discover causal relationships between variables.
For example, a retail company can test the usability of its new e-commerce app by randomly assigning two groups of older participants to the current and new versions of the app. The researcher then conducts interviews to measure attitudes and behaviors.
However, it should be noted that depending on numbers and figures to make conclusions without proper context can lead to misleading numerical data. This is where qualitative data comes in.