On a response variable in an experiment, as well as the factor whose effect is being investigated, there may be many other factors which may also influence it. The most widely used and well known method, named as completely randomized design, help us to investigate whether there is a statistically significant difference between the groups by comparing the responses obtained from subjects which were randomly selected from the k (k >= 2) groups. In such a design, other than the factor being investigated, all other factors which may influence the response variable, are expected to be similar between the groups due to random selection of the subjects. However, this may not always be provided. In order to overcome this situation, if homogeneous experimental units, so called the blocks are formed and each trial (group) is run on these blocks, then it may be possible to examine the effect of the factor more precisely. This design, where all the trials are tested on each block is named as randomized block design. By means of randomized block design it is possible to decrease the sample size to achieve the same power with completely randomized design and hence to reach more accurate results. This feature made this method very popular in agriculture, industry and health sciences. In the manuscript titled as "Influence of brewing pots on mineral content of black tea infusions", the authors investigate the effect of brewing pots on the mineral content of different black tea infusions. Here, the factor being investigated is the brewing pot type (porcelain, glass, steel and aluminum). When the black tea brands are considered as blocks and each brand of black tea is brewed in all types of pots then randomized block design can be applicable. With this method it will be possible to draw the effect produced by the probable differences in the mineral contents of different brands of black tea infusions from brewing pot effect, thus will display the differences, if any, arising from pots more accurately. This method allows reducing the experimental error and has some different modifications which are applicable in situations where it is not possible to test all treatments in each block.