5.2 Day 1: Designing Experiments

Period 3 – Seating Chart Front Board AlthisarBarnesCreidlerGreenHollowayMcDonaldOliverRoberts EvansCawthorn e AndersonLavendarJeffreysMcKeelMenaSyed CecilGriffinHallAndrewsGivensWhiteSabistonTaylor Scott Martin BockFowlerAyersFabitoO’SheaSigafoosTravers

Period 4 – Seating Chart Front Board AlfordByrdCornstubb le McDanielHamlettPalomaresMarvinWest BrowningColeDanielGanttWhitePiephoffSyedWilkins CarpenterColemanDerbyshir e OsborneKeyFoleyStafford- Louisiana Bailey Hambleto n EllisSternStedmanHillBeckwithWilliams

Experimental Units, Subjects, Treatment The individuals on whom the experiment is done are the experimental units. When the units are human beings, they are called subjects. A specific experimental condition applied to the units is called a treatment.

Factors and Levels The explanatory variables in an experiment are often called factors. Many experiments study the combined effects of several factors. Each treatment is formed by combining a specific value or level of each of the factors.

Ex 1: Does regularly taking aspirin help protect people against heart attacks? This experiment studies the effects of aspirin and beta carotene on the prevention of heart attacks and certain types of cancer. The subjects were 21,996 male physicians. There are two factors: aspirin and beta carotene. Each factor has two levels: yes or no. One-fourth of the subjects were assigned to each treatment group.

Treatments in the Physician’s Health Study On odd numbered days, the subjects took a white tablet that contained aspirin or a placebo (dummy pill) On even numbered days, they took a red capsule containing either beta carotene or a placebo.

Response Variables The study looked for… Heart attacks Several kinds of cancer Other medical outcomes After several years, 239 of the placebo group vs. only 139 of the aspirin group had suffered heart attacks. This outcome is good evidence that taking aspirin does reduce heart attacks. Beta carotene had no apparent effect.

Advantages of Experiments vs. Observational Studies Remember, a survey is not enough to prove a cause!! There must be an experiment!! In principle, experiments can give good evidence for causation. Experiments allow us to study the specific factors we are interested in, while controlling the effects of lurking variables. Experiments also allow us to study the combined effects of several factors.

Comparative Experiments Units TreatmentObserve Response This type of treatment has a simple design with only a single treatment, which is applied to all of the experimental units.

Ex 2: Quitting Smoking Suppose that you wanted to study the effects that anti-depressants have on the relapse rate of individuals who are trying to quit smoking. Smokers Anti-depressants Observe Relapse It would not be enough to give every individual a daily anti-depressant and then measure the rate of relapse after a period of time. You need a control group!

Control Group The subjects of the experiment would need to be divided into two groups: those who actually take anti-depressants and those who think that they are taking anti-depressants Those who are taking the fake anti- depressants are called the control group.

Placebo and Placebo Effect The placebo in this case would be a pill that looks exactly like the anti-depressant, but does not contain the active ingredient. People who take a placebo tend to respond better than those who take nothing, perhaps for psychological reasons. This is known as the placebo effect.

Good experimental design is… always randomized! random, random, random can be replicated! replicate, replicate, replicate CRR CONTROL, RANDOMIZE, REPLICATE

Randomized Comparative Experiments When we introduce the control group to the smokers and anti-depressants experiment, we create a randomized comparative experiment with the following diagram: Random Assignment of 400 Smokers Group Smokers Group Smokers Treatment 1 Anti-Depressant Treatment 2 Placebo Observe Relapse Rate It is very important that we use enough experimental units or subjects to reduce chance variation.

Principles of Experimental Design (CRR) 1) Control the effects of lurking variables on the response, most simply by comparing two or more treatments. 2) Randomize – use impersonal chance to assign experimental units to treatments. 3) Replicate each treatment on many units to reduce chance variation in the results.

Statistically Significant An observed effect so large that it would rarely occur by chance is called statistically significant. This is one of the reasons why it is so important that we replicate experiments!

Completely Randomized Design When all experimental units are allocated at random among all treatments, the experimental design is completely randomized. This can be achieved by numbering all individuals and using the method of SRS to assign individuals to treatment groups.

Ex 3: Studying the effects of a new medication on blood pressure Suppose that you want to conduct an experiment that studies the effects of a new medication on high blood pressure and you have 100 female subjects who are in approximately the same age range. Draw a diagram on your notes that would demonstrate a completely randomized experiment.

Answer… Random Assignment of 100 subjects using Simple Random Sampling Group 1 50 Females Group 2 50 Females Treatment 1 Blood Pressure Medication Treatment 2 Placebo Compare Blood Pressures