Mathematics is a branch of study. From school to higher educational level, you continually study mathematics. It starts from basic mathematics, and then you need to go for its complex aspects. In mathematics, all of the data collection and analysis is done in statistics. Furthermore, statistics covers the interpretation of data based on its analysis. So, you can better present your data through statistics. In this way, it becomes manageable to deal with financial aspects at any organisation.

Statistics is a broad field that covers so many sub-domains. One of the subdomains is descriptive statistics. The use of this domain is very frequent. You can see its wide usage in statistics as well as in engineering. As per its importance, this article aims to discuss about descriptive statistics and its types.

Descriptive statistics is the description of data set. You can take it as an abstract of data available to you. For a better understanding of this term, it is necessary to understand the basic classifications linked with it. There are two basic classifications of this domain. The first category is a central tendency, while the second one is variability. You can also take variability as a spread of data by hiring UK assignment writing services. Both of the categories have different aspects to show in a particular domain.

By using central tendency, you can evaluate data in terms of mean and median. Also, you can go for the mode of a data set. On the other hand, the working area of variability is totally different. In this category, you can come up with a standard deviation of the data. It works well for variance and different ranges of variables. For example, the least value of a variable and the highest value of a variable. In the last, it also covers kurtosis and skewness. One of the best examples to understand descriptive statistics is GPA (Grade Point Average) at the university level.

Let’s discuss each type briefly.

In different software of statistics, you can find the option of frequency as well as descriptive frequency. What you have to do is to make data entrance on the sheet. After that, select the option of required frequency, you will get the data representation in different forms. It can be in the form of a chart and table as well. The best example of software that can be used for such purposes is SPSS (Statistical Package for the Social Sciences)

Similarly, you can go for the standard deviation. You just need to calculate the mean for standard deviation and note the observed score. The difference between the observed score and mean is standard variation.

Most of the experts take only three types of descriptive statistics. From above mentioned four, they focus on the first three only. It includes a measure of frequency, central tendency and variation. It is better to understand all of four types, but it is your choice if you want to skip the last one.

Statistics is a broad field that covers so many sub-domains. One of the subdomains is descriptive statistics. The use of this domain is very frequent. You can see its wide usage in statistics as well as in engineering. As per its importance, this article aims to discuss about descriptive statistics and its types.

**What is Descriptive Statistics?**

Descriptive statistics is the description of data set. You can take it as an abstract of data available to you. For a better understanding of this term, it is necessary to understand the basic classifications linked with it. There are two basic classifications of this domain. The first category is a central tendency, while the second one is variability. You can also take variability as a spread of data by hiring UK assignment writing services. Both of the categories have different aspects to show in a particular domain. By using central tendency, you can evaluate data in terms of mean and median. Also, you can go for the mode of a data set. On the other hand, the working area of variability is totally different. In this category, you can come up with a standard deviation of the data. It works well for variance and different ranges of variables. For example, the least value of a variable and the highest value of a variable. In the last, it also covers kurtosis and skewness. One of the best examples to understand descriptive statistics is GPA (Grade Point Average) at the university level.

## What Are Four Types Of Descriptive Statistics?

There are four major types of descriptive statistics. All of types are designed based on their function. So, you can remember the functions of each type by its name. These types are mentioned below:- Measure of Frequency
- Measure of Central Tendency
- Measure of Variation
- Measure of Position

Let’s discuss each type briefly.

### Measure of Frequency

The type of descriptive statistics that focuses on an event’s occurrence is named as measure of frequency. In this type, you can easily get how often an event can happen. Other than the event, you can cover so many other aspects as well. Under this type, you can go for counts of data set. Also, you can calculate the percentage of data available to you. As per the name of this type, its major function is descriptive frequency. In any project, whenever you have to come up with any of these functions, you can use a measure of frequency.In different software of statistics, you can find the option of frequency as well as descriptive frequency. What you have to do is to make data entrance on the sheet. After that, select the option of required frequency, you will get the data representation in different forms. It can be in the form of a chart and table as well. The best example of software that can be used for such purposes is SPSS (Statistical Package for the Social Sciences)

### Measure of Central Tendency

In measure of central tendency, you can find out different points in data. The core purpose of this type is to identify the central point of whole data. For finding the central location, it covers the mean, mode and median of the data set. In research work, you have to collect a large sample of data for better representation of a particular aspect. In a large data sample, it is mostly required to know about the response that has more counts. Also, it can be in the form of an average of each response in collected data. In both cases, a measure of central tendency can work best for you.### Measure of Variation

In descriptive statistics, variation is the spread of data. You can also call it as dispersion of data. In a variation, you can calculate and represent different ranges of data. Also, representation of standard deviation is a part of the measure of variation. In a large sample of data, the spread of data causes impacts on a mean. In such cases, you have to see how much data spread is there in your work. In case of range, you can find the highest and lowest point in your data. For example, the range of your data is 0-100. Here, 0 is the lowest point, and 100 is the highest point in your data.Similarly, you can go for the standard deviation. You just need to calculate the mean for standard deviation and note the observed score. The difference between the observed score and mean is standard variation.

### Measure of Position

The last type of descriptive statistics is a measure of position. The use of this type is common to observe when you have to come up with a comparison of different scores. The comparison can be in between the available score and the normalised one. You can do this with the help of percentile ranks and quartile ranks.Most of the experts take only three types of descriptive statistics. From above mentioned four, they focus on the first three only. It includes a measure of frequency, central tendency and variation. It is better to understand all of four types, but it is your choice if you want to skip the last one.

## Final Thoughts

Descriptive statistics is the simplest summarisation of quantitative data. Its different types have different features to represent. Understand the above-mentioned points related to each type. After that, identify the best suitable type for use in your project. The use of right type makes your end results effective. In this way, you can achieve your objective in a better way.