# Difference between qualitative data and quantitative data

**Main Difference between qualitative data and quantitative data**

Statistics is the practice or science of collecting and analyzing numerical data in large quantities. It is specially assigned for the purpose of inferring proportions on a whole from those in a representative sample. Statistics is quite useful for organizing and collecting data. Mainly, the numeric value or the data in the numeric value is evaluated in the statistics. There are several types of data that are collected and analyzed. Notable data analysis techniques are primary data, secondary data, qualitative data, and quantitative data. Qualitative data is the type of data that collects data in properties and attributes. Qualitative data representation is done with language or words, and not with numbers or numerical values. Conversely, quantitative data is the type of data in which data is sorted by quantity, quantity, or range. Quantitative data is expressed using number, units of measure, or numerical values.

## Comparative chart

Qualitative data | Quantitative data | |

Definition | Qualitative data is the type of data that can be observed but cannot be measured. | Quantitative data is what is represented by numbers, numerical values and units of measurement. |

Properties | Texture, taste, touch, and smell are some of the observable properties used in this interpretation of qualitative data. | Data is classified into different groups based on quantity, quantity, or range in qualitative data. |

Nature | There is a non-statistical analysis for qualitative data. | Statistical analysis is used for quantitative data. |

Representation | In qualitative data, words are used for expression. | In quantitative data, numbers and units of measure are used for the expression. |

**What is qualitative data?**

Qualitative data is the type of data that can be observed but cannot be measured. The classification of objects in this data type is done with respect to attributes and properties. It is approximate data analysis, which cannot be calculated or that precise. The one who analyzes this type of data needs to have previous knowledge about the types of objects and their characteristics. If any of the laymen tries to analyze it, things can get worse as qualitative data is descriptive in nature, and when analyzing it requires an expert approach. During the data analysis process, objects are placed in different categories afterwards. they are distinguished by physical attributes and properties of the object. The interpretation of the data is based purely on observation and properties, which can be observed but cannot be expressed using numbers. In a more compact way, we can say that it is the type of data interpretation in which language and words are used for the ordering and analysis of the data. Texture, taste, touch, smell are some of the observable properties used in this type of data interpretation. Apart from observations, qualitative data are based on interviews or evaluations. Qualitative data is also called categorical data, since the information is classified by category and not by numbers. Apart from observations, qualitative data are based on interviews or evaluations. Qualitative data is also called categorical data, since the information is classified by category and not by numbers. Apart from observations, qualitative data are based on interviews or evaluations. Qualitative data is also called categorical data, since the information is classified by category and not by numbers.

**What is quantitative data?**

Quantitative data is what is represented by numbers, numerical values and units of measurement. The data is classified into different groups by quantity, amount, or range. In other words, we can say that it is the numbers game in which the different arithmetic operations can also be applied, and the validity of it can also be verified. Quantitative data is the method in which data is counted or expressed numerically. Here even tables, graphs and histograms are used for expression purposes. With the use of the aforementioned, evaluating data for one becomes quite easy as it covers everything in a very concise way. Measurement of length, volume, area, and temperature are some of the prominent examples of this type of data analysis. In this case, numbers are required along with units of measure. Experiments

## Qualitative data vs. quantitative data

- Qualitative data is the type of data that can be observed but cannot be measured. On the other hand, quantitative data is what is represented by numbers, numerical values and units of measurement.
- Texture, taste, touch, and smell are some of the observable properties used in this interpretation of qualitative data. Rather, the data is classified into different groups based on quantity, quantity, or range in the qualitative data.
- There is non-statistical analysis for qualitative data, while statistical analysis is used for quantitative data.
- In quantitative data, numbers and units of measure are used for expression, while in qualitative data words are used for expression.