What are the 3 requirements for an experiment?

The practical steps needed for planning and conducting an experiment include: recognizing the goal of the experiment, choice of factors, choice of response, choice of the design, analysis and then drawing conclusions. This pretty much covers the steps involved in the scientific method.

Table of Contents Show

Factors Section
Try It! Section
What are 3 things an experiment must have?
What are the 3 principles of experimental design?

Recognition and statement of the problem
Choice of factors, levels, and ranges
Selection of the response variable(s)
Choice of design
Conducting the experiment
Statistical analysis
Drawing conclusions, and making recommendations

What this course will deal with primarily is the choice of the design. This focus includes all the related issues about how we handle these factors in conducting our experiments.

Factors Section

We usually talk about "treatment" factors, which are the factors of primary interest to you. In addition to treatment factors, there are nuisance factors which are not your primary focus, but you have to deal with them. Sometimes these are called blocking factors, mainly because we will try to block on these factors to prevent them from influencing the results.

There are other ways that we can categorize factors:

Experimental vs. Classification Factors

Experimental FactorsThese are factors that you can specify (and set the levels) and then assign at random as the treatment to the experimental units. Examples would be temperature, level of an additive fertilizer amount per acre, etc.SampleText

Classification FactorsThese can't be changed or assigned, these come as labels on the experimental units. The age and sex of the participants are classification factors which can't be changed or randomly assigned. But you can select individuals from these groups randomly.

Quantitative vs. Qualitative Factors

Quantitative FactorsYou can assign any specified level of a quantitative factor. Examples: percent or pH level of a chemical.

Qualitative FactorsThese factors have categories which are different types. Examples might be species of a plant or animal, a brand in the marketing field, gender, - these are not ordered or continuous but are arranged perhaps in sets.

Try It! Section

Think about your own field of study and jot down several of the factors that are pertinent in your own research area? Into what categories do these fall?

Get statistical thinking involved early when you are preparing to design an experiment! Getting well into an experiment before you have considered these implications can be disastrous. Think and experiment sequentially. Experimentation is a process where what you know informs the design of the next experiment, and what you learn from it becomes the knowledge base to design the next.

Randomization is the cornerstone underlying the use of statistical methods in experimental designs. Randomization is the random process of assigning treatments to the experimental units. The random process implies that every possible allotment of treatments has the same probability. For example, if number of treatment = 3 (say, A, B, and C) and replication = r = 4, then the number of elements = t * r = 3 * 4 = 12 = n. Replication means that each treatment will appear 4 times as r = 4. Let the design is

ACBCCBABACBA

Note from the design elements 1, 7, 9, 12 are reserved for treatment A, element 3, 6, 8 and 11 are reserved for Treatment B and elements 2, 4, 5 and 10 are reserved for Treatment C. P(A)= 4/12, P(B)= 4/12, and P(C)=4/12, meaning that Treatment A, B, and C have equal chances of its selection.

Replication

By replication, we mean that repetition of the basic experiments. For example, If we need to compare the grain yield of two varieties of wheat then each variety is applied to more than one experimental units. The number of times these are applied to experimental units is called their number of replication. It has two important properties:

It allows the experimenter to obtain an estimate of the experimental error.
The more replication would provide the increased precision by reducing the standard error (SE) of mean as $s_{\overline{y}}=\tfrac{s}{\sqrt{r}}$, where $s$ is sample standard deviation and $r$ is number of replications. Note that increase in $r$ value $s_{\overline{y}}$ (standard error of $\overline{y}$).

Local Control

It has been observed that all extraneous source of variation is not removed by randomization and replication, i.e. unable to control the extraneous source of variation.
Thus we need to a refinement in the experimental technique. In other words, we need to choose a design in such a way that all extraneous source of variation is brought under control. For this purpose we make use of local control, a term referring to the amount of (i) balancing, (ii) blocking and (iii) grouping of experimental units.

Balancing: Balancing means that the treatment should be assigned to the experimental units in such a way that the result is a balanced arrangement of treatment.

Blocking: Blocking means that the like experimental units should be collected together to far relatively homogeneous groups. A block is also a replicate.

The main objective/ purpose of local control is to increase the efficiency of experimental design by decreasing the experimental error.

What are 3 things an experiment must have?

A properly designed experiment usually has three kinds of variables: independent, dependent, and controlled.

What are the 3 principles of experimental design?

Three main pillars of experimental design are randomization, replication, and blocking, and we will flesh out their effects on the subsequent analysis as well as their implementation in an experimental design.