Data is an integral part of any statistical analysis. But how do you know which method to apply to get the results? Well, it depends entirely on the type of data you have in hand. There are two major types of data – categorical data and numerical data. There are different statistical methods for both types of data. However, in today’s article, we will not be looking at their statistical methods. Instead, we will discuss the similarities and differences that exist between numerical and categorical data. Before that, let’s define them briefly.

**What is numerical data in research?**

Numerical data is any data which is expressed in terms of numbers. This kind of data is also collected in the form of numbers. This type of data is also called quantitative data in scientific terms. Discrete data is a perfect example of this data which has a one-to-one mapping with natural numbers. This data is countable, like 1,2,3 and 4.

**What is categorical data in research?**

The second type of data is known as categorical data. This is a data type that can be stored and identified based on the numbers given to them. This kind of data is mostly stored in the form of groups and categories. Each group is categorised using its label. The grouping or categorisation is usually done based on the data characteristics.

**Similarities between categorical and numerical data**

As discussed earlier, both categorical and numerical data are different from each other. However, they are not always different. There are also some similarities between them. Do you know about those similarities? A brief description of the similarities is as follows:

**1. The similarity in collection method**

The first similarity exists in the data collection methods. The data collection methods used for the collection of categorical data can also be applied to the collection of numerical data. For example, you can use methods like surveys, questionnaires, and interviews for both types of data. Hence, both data types are similar in this context.

**2. The similarity in value**

Another similarity that can be observed between categorical and numerical data is that they can have the same numerical value. In the case of categorical data, the researcher can assign numerical values to the data collected and the categories made. On the other hand, numerical data is always in the form of numbers. However, if you do not know how to categorise the data numerically, you can ask for help from a dissertation writing service.

**Differences between categorical and numerical data**

After discussing the similarities, it is now time to have a look at the differences. The differences are a bit high in number than the similarities. However, we will only mention the primary ones here. Hence, the differences between these two data types are as follows:

**1. The difference in the application of data**

The first difference that lies between numerical and **categorical** data is the difference in the application data and the meanings derived from the data. The numerical data just gives a numerical value and is not that useful as compared to categorical. In contrast, the categorical sets of data reveal many things about the population. These data sets unearth many hidden themes and patterns about the target population.

**2. The difference in analysis methods**

A huge difference lies in the analysis methods of both types of data. Both datasets use different analysis methods. Numerical data being data consisting of numbers, mostly employ arithmetic operations like addition, subtraction etc. It also uses some advanced methods like regression analysis and ANOVA tests to analyse the data.

On the other hand, categorical data consists of words, expressions, and statements. This data can only be analysed using methods like thematic analysis, content analysis etc. If you do not know how to do these analyses, do not hesitate to contact dissertation writers UK and ask for help.

**3. The difference in data visualisations**

What do you get after performing an analysis? Yes, you get some research results. The difference that we are going to discuss is related to the presentation of those results in the research study. Yes, both types of data utilise two different ways of data visualisation. The pie chart is the most widely used method for the visualisation of categorical data. The reason is that it is based on categories. In the meantime, you can use line charts or scatterplots for the visualisation of numerical data.

**Conclusion**

Conclusively, both categorical and numerical types of data are different from each other. Although there are some **similarities** between them, still, their similarities are lesser than their differences. This is why categorical data is perceived as totally different data from numerical data. We have discussed the major differences here in this post. So, learn about them and use the right method for a particular data type.

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