**I would say there are two main types of statistics.**

- Descriptive
- Inferential statistics (sometimes known as inductive statistics).

These can also be referred to as quantitative and qualitative statistics. Below, I break the two types down and give more details:

**Descriptive statistics (qualitative)**

Descriptive statistics aim to describe the prominent features within a collection of data quantitatively. It summarizes a collection of data as a description rather than using the data to learn about the field in which the data represents. Generally, descriptive statistics are always used, even when the main conclusions from the data's analysis are gained by use of inferential statistics.

For example, the sports sections of newspapers tend to give statistics on the performance of many players such as the amount of goals scored compared with the amount of goal attempts. This is a descriptive statistic as it summarizes the data in a quantitative manner.

**Inferential statistics (quantitative)**

Inferential statistics is the given title of a process of gaining knowledge from a set of data that are subject to random change or variation. Such data sets would render a descriptive statistic meaningless as the data changes in an unpredictable way. Therefore no knowledge would be gained about the subject that the data represents. The outcome to such a statistical method may be a prediction that can then be used to ensure practical action to be taken. For example, it may have influence when making managerial decisions that affect the future within a business.

There are actually only 2 different types of statistics. Statistics are the collection of data, and the organization of the data. The two types of statistics that can be used are qualitative and quantitative.

Qualitative statistics are collected on the basis that the answers given in the statistical survey will be more in depth, and of a better quality, whereas quantitative statistics are collected in greater numbers, but the information therein will be less detailed, even though a broader amount of people have provided the information.

When a business is launching a new product it will normally be tested on a small number of people first. The cross section of people used will include different age groups, different sexes, and different ethnic groups. This will enable the information gathered to be of more use as a whole, as if the majority of people who try the product like it, it is more likely to be successful across the board. Sometimes, the new product will be aimed at a particular market. For example, if a cosmetics company is launching a new perfume, they will know that women will be the sole group that the product will be aimed at. Therefore the number of women that can be tested can be larger. This enables the business to test a higher number of people, but the age range and the ethnic group may not be taken into account. The sole purpose of this type of statistical collection is to ascertain whether or not a high percentage of the people who try the product like it and would buy it.

There are positive and negative aspects of both methods of statistical collection, as the more people surveyed the better when it comes to making a decision. The downside however, is that the more people that need to be surveyed, the longer period of time it will take to survey them, and thus collect the information needed.