The design of experiments is the process of choosing which variables to manipulate in order to determine their effect on the response.
What is an Experiment?
An experiment is a test designed to answer a specific question about some aspect of nature. For example, if I wanted to know what affects the yield of a crop, I would need to perform several different tests to find out the best conditions for growing them. These conditions might include:
•Type of fertilizer used
•Amount of water added
•Time of planting
In this case, the "response" is the crop yield. The "variables" are the things that can be changed in each test. In our case, we have different variables such as fertilizer, watering, temperature, time of planting etc.
How Does the Design of an Experiment Work?
To conduct an experiment, you must first choose your variables. This means deciding exactly what factors will affect the outcome of the study. You then set up the experiment. Each variable has a range of values it can take. When setting up the experiment, you want to make sure that all possible combinations of these variables are represented (in the case of a full-factorial design).
For example, let's say we were studying the effects of temperature and fertilization on the growth of plants. We could use two levels of both temperatures and fertilizers to create four treatments. If we had three replicates per treatment, we'd end up with 12 experiments.
Once you've chosen your variables, you can start planning your experiment. You randomly assign each variable to one of the treatments. Then, you measure the response at the end of the study. Finally, you analyze the data to see which combination produced the highest or lowest response.
This was a plain and simple explanation of the Design of Experiments.
As you see here, we have taken seven steps to perform a Design of Experiments. These are summarized below:
1. Define the objective of the experiment
2. Choice of factors and levels
3. Choose the response variable
4. Design the experiment
5. Conduct the experiment
6. Analyze results
7. Draw a conclusion and make recommendations
Basic Design of Experiment Definitions
Response: The output(s) of a process. This is also called dependent variable(s).
Factors: Factors are the independent variables in an experiment. They are not necessarily numerical but may also be categorical.
Level: A level is a value within a factor. It represents a particular condition of the factor.
Treatment: A treatment is a specific combination of factor levels whose effect is to be compared with other treatments.
Replicate: An experimental unit that receives the same level of every factor.
Experiment: Experiment means testing something systematically, usually under controlled conditions.