Statistics - Describe The Characteristics Of An Experiment

Objective 1: Describe the Characteristics of an Experiment – Experiment: is a controlled study conducted to determine the effect of varying one or more explanatory variables or factors has on a response variable. Any combination of the values of the factors is called a treatment ● Experimental Unit (or subject): is a person, object or some other well-defined item upon which a treatment is applied ● Control Group: serves as a baseline treatment that can be used to compare to other treatments ● Placebo: is an innocuous medication, such as a sugar tablet, that looks tastes, and smells like the experimental medication ● Treatment: any combination of the values of the factors (explanatory variables) ● Response Variable: the quantitative or qualitative variable for which the experimenter wishes to determine how its value is affected by the explanatory variable ● Factor: a variable whose effect on the response variable is to be assessed by the experimenter ● Confounding: the effect of two factors (explanatory variables on the response variable) cannot be distinguished What does it mean for the experiment to be “placebo-controlled?” The experiment will have a control group that takes a placebo, which is a innocuous medication, such as a sugar tablet. This control group serves as a baseline treatment that can be used to compare to the group that is actually taking the medication. From Homework: ● In a single-blind experiment, the subject does not know which treatment is received. This helps ensure that individuals do not adjust their behavior because of the treatment they are receiving. In a double-blind experiment, neither the subject nor the researcher in contact with the subject knows which treatment is received. When the researcher also does not know which treatment is received, it helps ensure that they observe each group the same way. Objective 2: Explain the Steps in Designing an Experiment 1. Identify the Problem to be Solved. a. The statement of the problem should be as explicit as possible and should provide the experimenter with direction. The statement must also identify the response variable and the population to be studied. Often, the statement is referred to as the claim. 2. Determine the Factors that Affect the Response Variable a. The factors are usually identified by an expert in the field of study. In identifying the factors, ask, “what things affect the value of the response variable?” After the factors are identified determine which factors to fix at some predetermined level, which to manipulate, and which to leave uncontrolled. 3. Determine the Number of Experimental Units. a. As a general rule, choose as many experimental units as time and money allow. Techniques exist for determining sample size, provided certain information is available. 4. Determine the Level of Each Factor a. Control: there are two ways to control the factors i. Set the level of a factor at one value throughout the experiment (if you are not interested in its effect on the response variable) ii. Set the level of a factor at various levels (if you are interested in its effect on the response variable). The combinations of the levels of all varied factors constitute the treatments in the experiment. b. Randomize: randomly assign the experimental units to treatment groups. Because it is difficult, if not impossible, to identify all factors in an experiment, randomly assigning experimental units to treatment groups reduces the effect of variation attributable to factors (explanatory variable) not controlled. That is, randomly assigning experimental units to treatment groups tends to “even out” any uncontrollable factors. 5. Conduct the Experiment a. Replication occurs when each treatment is applied to more than one experimental unit. Using more than one experimental unit for each treatment ensures the effect of a treatment is not due to some characteristic of a single experimental unit. It is a good idea to assign an equal number of experimental units to each treatment. b. Collect and process the data. Measure the value of the response variable for each replication. Then organize the results. The idea is that the value of the response variable for each treatment group is the same before the experiment because of randomization. Then any difference in the value of the response variable among the different treatment groups is a result of differences in the level of the treatment. 6. Test the Claim a. This is the subject of inferential statistics. Inferential statistics is a process in which generalizations about a population are made on the basis of results obtained from a sample. Provide a statement regarding the level of confidence in the generalization. Objective 3: Explain the Completely Randomized Design A completely randomized design is one in which each experimental unit is randomly assigned to a treatment Objective 4: Explain the Matched-Pairs Design A matched-pairs design is an experimental design in which the experimental units are paired up. The pairs are selected so that they are related in some way (that is, the same person before and after a treatment, twins, husband and wife, same geographical location, and so on). There are only two levels of treatment in a matched-pairs design.