ABSTRACT
Agriculturalists and other scientists in biological fields who are involved in research constantly face problems associated with planning, designing, and conducting experiments. Basic familiarity and understanding of statistical methods that deal with issues of concern would be helpful in many ways. Practitioners (researchers) who collect data and then look for a statistical technique that would provide valid results may find that there may not be solutions to a problem and that the problem could have been avoided in the first place by conducting a properly designed experiment. Obviously, it is important to keep in mind that we cannot draw valid conclusions from poorly planned experiments. Second, the time and cost involved in many experiments are considerable, and a poorly designed experiment increases such costs. For example, agronomists who carry out a fertilizer experiment know the time limitations on the experiment. They know that, in the temperature zone, seeds must be planted in the spring and harvested in the fall. The experimental plot must include all the components of a complete design. Otherwise, what is omitted from the experiment will have to be carried out in subsequent trials in the next cropping season or the next year. This additional time and expenditure could be minimized by a properly planned experiment that would produce valid results as efficiently as possible.
