Question

a farmer wishes to test the effects of a new fertilizer on her wheat yield. she has four equal-sized plots of land-- one with sandy soil, one with rocky soil, one with clay-rich soil, and one with average soil. she divides each of the four plots into three equal-sized portions and randomly labels them a, b, and c. the four a portions of land are treated with her old fertilizer. the four b portions are treated with the new fertilizer, and the four c's are treated with no fertilizer. at harvest time, the wheat yield is recorded for each section of land. how many levels does the treatment have in this experiment?

Answer 1

Using the concept of Randomized Design ,we got 4 levels of treatment heave been done by farmer in this experiment.

1.Completely Randomized Design :-

A completely randomized design is basically the simplest experimental design, in terms of data analysis and convenience. With this design, subjects are randomly assigned to treatments.

This completely randomized design actually relies on randomization to control for the effects of extraneous variables. The experimenter actually assumes that, on average, extraneous factors will affect treatment conditions equally; so any relevant differences between conditions can fairly be attributed to the independent variable.

2.Double Blind Design :-

In an experiment, if subjects in the control group knows that they are receiving a placebo, the placebo effect will be reduced or will be eliminated; and the placebo will not serve its intended control purpose.

Blinding is basically the practice of not telling subjects whether they are receiving a placebo. In this way, subjects which are in the control and treatment groups experience the placebo effect equally. Often, knowledge of which groups receive placebos is also keep from analysts who evaluate the experiment. This practice is called double blinding. It prevents the analysts from "spilling the beans" to the subjects through subtle cues; and it assures that their evaluation is not tainted by the awareness of actual treatment conditions.

3.Matched Pairs Design :-

A matched pairs design is actually a special case of a randomized block design. It can be used when the experiment has basically only  two treatment conditions; and subjects can be grouped into pairs, on the basis of some blocking variable. Then, within each pair, subjects are randomly assigned to different treatments.

4.Randomized Block Design :-

With a randomized block design, the experimenter actually divides subjects into subgroups called blocks, such that the variability within blocks will become  less than the variability between blocks. Then, subjects within each block are randomly assigned to treatment conditions.

Hence, we got 4 levels of treatment have been done by farmer in this experiment.

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