What Are The Uses Of Paired Data?

Introduction

Paired data is a method which is commonly used in statistics. Data are paired by the linking of two different values. Unlike the normal association of one number with each data as in other statistical methods, a single data point signifies not a single value, but rather an ordered pair belonging to two values. Paired data has a wide range of applications. There are specific situations which require the use of paired data. It is normally used with the aim to diminish or control the effect of confusing variables. A number of examples where paired data can be used proficiently have been mentioned in a number of areas which are mentioned below:-

Twin Studies

In this instance, a paired data point is formed by a set of identical twins. While one is randomly chosen for a treatment, the other will be used as a control and won’t receive any type of treatment. Then, the responsible variable is measured and compared for each of these twins. This type of pairing is valuable as identical twins have similar genetics as well as upbringing. So, the effects of variables which evolve from these sources get lessened. This type of pairings creates much dissimilarity which is observed as an outcome of the treatment, instead of some other source.

Matched Pairs

However, there are cases in which you cannot use subjects which are identical, as in case of twins. But you can still use paired data in such a case if the subjects are similar to each other. This type of paired data is known as matched pair. They are used when there are subjects which can be treated interchangeably. For instance, you may want to verify whether a dietary supplement provided to ducks helps to improve the weight of the eggs they lay or not. Ducks which are alike in weight and other characteristics will be grouped together and then fed with the dietary supplement. The control group will fed on the normal diet. Eggs of ducks from both these categories will be then weighed and compared.

Treatments on a common source

Often you can study two treatments on a particular subject. In these cases, you can randomly assign order of the two treatments in order to remove potential effects which the arrangement of treatments has on your response variable.

Conclusion

There are a number of scientific experiments which require measurement of any particular object before and after treatment has been done. Paired data is ideal for use in these cases. By pairing the data one can test the hypothesis whether the treatment produced the wanted result or not. Paired data is able to test this in a controlled manner as you can calculate the produced change which occurred on individuals.

This article has been compiled by Evelyn, who is a writer on various academic topics.