The main difference between qualitative and quantitative data is that qualitative data is descriptive while quantitative data is numerical. For example, qualitative data are gender, country, city, nationality, etc. while quantitative data are length, width, height, weight, area, speed, age, etc. Furthermore, quantitative data can be either discrete data (countable data such as number of vehicles, number of students, etc.) or continuous data (measurable data such as height, weight, etc.).
Data is important for everything. Most business organizations collect sales data, revenues, stock prices and profits. The government collects data on literacy rates, crime rates, birth rate, etc. Data is important for scientific and academic research such as machine learning and neural networks as well. Collecting and analyzing data helps to make better decisions. One emerging technology in the modern world is Internet of Things (IoT). This technology collects data using sensors and actuators and processes them for intelligent decision making. These are some advantages of data.
Key Areas Covered
1. What is Qualitative Data
– Definition, Examples, Collection
2. What is Quantitative Data
– Definition, Examples, Collection
3. Difference Between Qualitative and Quantitative Data
– Comparison of Key Differences
Qualitative Data, Quantitative Data, Statistics
What is Qualitative Data
Qualitative data represent characteristics. This data should be interpreted using plain language than numbers. Conducting interviews and observations are some methods to obtain qualitative data. The descriptive nature of these data makes them difficult to analyze. Some examples of these type of data is gender, country, city, nationality, etc.
Sometimes, it is possible to use numerical labels to prepare and represent qualitative data. Assume a situation to enter gender of employees in the database. For that, 1 can be used to denote male while 2 can be used to signify female.
What is Quantitative Data
Qualitative data represents numerical information. These type of data is easier to compute and analyze. Some examples are length, width, height, weight, area, speed, age, lifetime of an electric bulb, etc. Tables, graphs, charts help to represent quantitative data. It is possible to find quantitative data with the help of surveys, observations, interviews, and other experiments.
Quantitative data further divides into discrete and continuous data. Discrete data has certain values such as whole numbers. Some examples are number of students, number of machines, etc.; they are countable. On the other hand, continuous data can have any value within a range. Some examples are height and weight; they are measurable). Furthermore, applying arithmetic operations such as addition and division to quantitative data gives more meaning to them. For example, adding all heights and dividing the answer by the total number of observations will give the average. It is a significant measurement for analyzing.
Difference Between Qualitative and Quantitative Data
Qualitative data is the data type that consists of descriptive statements. On the other hand, quantitative data is the data type that can be measured and expressed numerically.
Qualitative data is text-based while quantitative data is number based.
Statistical analysis is easier with quantitative data than qualitative data.
Methods of Collecting Data
Interview, written documents, observations help to collect qualitative data. In contrast, surveys, observations, experiments, and interviews help to collect quantitative data.
The main difference between qualitative and quantitative data is that qualitative data is descriptive while quantitative data is numerical. Usually, statistical analysis is easier with quantitative data than qualitative data. Statistics, social sciences, computing are some disciplines that use these type of data.