Section 5.2 – Designing Experiments

Vocab Experimental Units – Subjects – Treatment – Factors – Individuals on which the experiment is being done. Subjects – Human beings for experimental units. Treatment – Specific condition applied to an experimental unit. Factors – Explanatory variables.

Vocab Placebo – Placebo Effect – Control Group – Experimental Group – Dummy Pill/Treatment. Placebo Effect – Psychological effect of responding favorably to any perceived treatment. Control Group – Group receiving no treatment or placebo treatment. Experimental Group – Group receiving experimental treatment.

Three Basic Principles of Experimental Design Control – Control the effects of lurking variables on the response, most simply by comparing 2 or more treatments. Randomize – Use chance to assign units to treatments. Replicate – Use the same treatment on many units to reduce chance variation.

Completely Randomized Design A completely randomized design happens when all experimental units are allocated at random among all treatments.

Example #1: What is the best way to answer each of the questions below: an experiment, a sample survey, or an observational study? Explain your choices. Are people generally satisfied with how things are going in the country right now? Survey, no treatment, and cannot tell if someone is satisfied by observing them.

Example #1: Do college students learn basic accounting better in the classroom or using an online course? Experiment, has two treatment that results can be compared. How long do your teachers wait on the average after they ask their class a question? Observational Study, no treatment given, and responses to survey questions would be bias.

Example #2: New varieties of corn with altered amino acid content may have higher nutritional value than standard corn, which is low in the amino acid lysine. An experiment compares two new verities, called opaque-2 and floury-2, with normal corn. The researchers mix corn-soybean meal diets using each type of corn at each of three protein levels, 12% protein, 16% protein, and 20% protein. They feed each diet to 10 one- day-old male chicks and record their weight gains after 21 days. The weight gain of the chicks is a measure of the nutritional value of their diet.

Example #2: What are the experimental units and the response variable in this experiment? Experimental Units – one-day-old male chicks Response Variable – weight gain

Example #2: How many factors are there? How many treatments? How many experimental units does the experiment require? Factors – 2, amino acid content and protein level. Treatments – 6, 2 different types of amino acid with 3 levels of protein for each type. Number of experimental units – 60, 6 treatments with 10 chicks each.

Example #2: Use a diagram to describe a completely randomized design for this experiment. Random assignments Group 1 10 Chicks Group 2 Group 3 Group 4 Group 5 Group 6 Treatment 1 Opaque-2, 12% P Treatment 2 Opaque-2, 16% P Treatment 3 Opaque-2, 20% P Compare Weight Gains 60 Chicks Treatment 4 Floury-2, 12% P Treatment 5 Floury-2, 16% P Treatment 6 Floury-2, 20% P

More Vocab Double Blind– Matched-Pairs Design – Block – Block Design– Neither subject nor the people that have contact with them know the treatment being used. Matched-Pairs Design – Compare just two treatments. A design to compare two treatments through one-sample procedures. Block – A group of experimental units that are known to be similar in some way that is expected to affect the response to the treatments. Block Design– In a block design, the random assignment of units to treatments is carried out separately within each block.

Example #1: Do consumers prefer the taste of a cheeseburger from McDonald’s or from Wendy’s in a blind test in which neither burger is identified? Describe briefly an experiment that could be used to answer this question. Make the experiment a combination of double-blind and matched pairs procedures. The source of the cheeseburger can’t be know ahead of time by the tasters, it could bias their opinion. Each subject must taste both cheeseburgers in order to identify with one they prefer.

Example #2: Is the number of days a letter takes to reach another city affected by the time of day it is mailed and whether or not the zip code is used? Briefly describe the design of a two-factor experiment to investigate this question. Be sure to specify the treatments exactly and to tell how you will handle lurking variables such as day of the week on which the letter is mailed.

Example #2: Use a diagram to describe this experiment. Group 1 X/n Mail Group 2 Group 3 Group 4 Group n-1 Group n Treatment 1 Zip given, Time 1 Treatment 2 Zip given, Time 2 Treatment 3 Zip given, Time 3 Compare number of days X Pieces of Mail Treatment 4 No Zip, Time 1 Treatment n-1 No Zip, Time 2 Treatment n No Zip, Time 3

Example #2: Things to think about. Since the only factors that we are concerned about are: Time of day, and Zip Code (Yes or No), then All letters need to be the same size All letters need to be sent to the same city. Mail letters on same day of week, but not around holidays.