CHAPTER 3- DESIGNING EXPERIMENTS

Response Variable- * A variable that measures an outcome or result of a study Explanatory Variable- * A variable that we think explains or causes changes in the response variable Subjects- * Individuals in an experiment

Treatment- * A specific condition applied to all individuals in an experiment Experiment vs. Observational Study (again!) * Experiment = treatment applied to all subjects * Obs. Study = no treatment imposed, just observe subjects and record data

Example 1: Go back to our activity 3.1 with the coin and the blindfold. Identify:   Subjects: Treatment: Explanatory Variable: Response Variable: Experiment or Obs. Study:

Example 2: I want to test out a new plant food Example 2: I want to test out a new plant food. So I take 20 plants, and give half the new plant food and half no food at all. All of the plants get the same amount of water and sunlight each day. After 30 days, I measure the height that the plant has grown, and also how many flowers it has on it.   Subjects: Treatment: Explanatory Variable: Response Variable: Experiment or Obs. Study:

EXPERIMENTING BADLY Lurking Variable- * A variable that has an important effect on the relationship among the variables in a study but is not included in the study (is not one of the expl. Variables) Confounded- * Two variables are said to be confounded when their effects on a response variable cannot be separated from each other.

Examples & how to draw pictures of the variables

Let’s go over HW problems #1 - 4

Placebo- * A dummy treatment * Example: sugar pill, “vitamin” water Placebo effect- * When an individual reacts to the placebo * The reaction can be positive or negative * Example: feeling better because of sugar pill, claiming you are performing better because of “vitamin” water

Designing Experiments! *drawing randomized comparative experiments

Explanatory variable = medication (aspirin or placebo) HW: p. 143 #6 Subjects = 22,000 physicians Explanatory variable = medication (aspirin or placebo) response variable = # of heart attacks b) 11,000 male physicians Aspirin every other day Compare number of heart attacks 22,000 male physicians 11,000 male physicians Placebo every other day

Try examples #1-5 in the notes

Logic of Experimental Design: * Randomization produces groups of subjects that should be similar in all respects before we apply the treatments * Comparative design ensures that influences other than the experimental treatments operate equally on all groups. * Therefore differences in the response variable must be due to the effects of the treatments

PRINCIPLES of Experimental Design: CONTROL - the effects of lurking variables on the response, by the comparing of 2 or more treatments RANDOMIZATION - use impersonal chance to assign subjects to treatments (SRS) REPLICATION - use enough subjects in each group to reduce chance variation in the results - repeat the experiment numerous times!

Statistically Significant- - An observed effect so large that it would rarely occur by chance - Seeing similar results over and over again = significant results! - can be from a large sample size or from repeating the experiment a lot