Warm Up Compare and contrast the following concepts as they relate to designing studies and experiments: Stratified Random Sample Blocking How are they similar and how are they different?

Scope of Inference Random Assignment Not Random Assignment Random Generalize to Generalize to Selection Population Population Cause and Effect No Cause and Effect Not Only conclude about Only conclude about Random sample sample Selection (Volunteers) Cause and Effect No Cause and Effect

Scope of Inference Imagine a botanist with the city of San Jose wants to test a new treatment for mildew using the roses in the Rose Garden. She randomly selects a group of 30 rose bushes and randomly assigns 15 of them to receive the new treatment and 15 to receive the standard treatment. At the end of the experiment the new treatment is found to be significantly better at preventing mildew. What conclusion can we make? (A) The new treatment causes fewer roses to get mildew and we can apply the results to all roses in the Rose Garden. (B) The new treatment causes fewer roses to get mildew and we can apply the results to all roses. (C) There may be lurking variables, we cannot assume cause and effect. (D) The new treatment causes fewer roses to get mildew but only applies to the roses tested.

Experimental Design Practice Everyone will get a description of 4 experiments we will design today. We will work on these one at a time. When instructed to begin, work with your partner to design an experiment for the scenario described. You should create a chart, diagram or table that clearly explains your experiment. Be sure to indicate if your experiment uses blocking or matched pairs and where control, randomization and replication are used.

Experimental Design Practice For each scenario we will randomly choose 3 groups to present their experimental design. Show your plan on the document camera and be prepared to answer questions from the audience. The group judged (by the class) to have the best design will receive extra credit. Creativity should enhance your chances of winning, but only if it improves the experimental design.