Warm Up We are designing an experiment to determine the best growing conditions for carrots. We will plant the seeds in locations with full sun or partial sun. We will also water the seeds every day, every other day or every third day. 1) Define the factors, levels and treatments in this experiment. 2) What would be a good choice for the response variable? 3) If we want to have 20 seeds receive each treatment, how many seeds do we need to plant for the experiment? 4) List at least 3 other factors that should be controlled.

Experimental Design - Blocking Blocks are “groups” of units with a similar characteristic that is expected to be influential on the outcome of the experiment. We use blocking so that we can compare results within each “block” or group. This improves the sensitivity of the experiment. Without blocking the results may be dominated by the differences between these groups.

Experimental Design - Blocking Imagine an experiment to test the effect of a new fitness program on the number of push-ups high school PE students can do. Create blocks of men and women before randomizing the subjects. Group 1 Treatment 1 Men Random Assignment Compare Results Group 2 Treatment 2 Subjects Group 1 Treatment 1 Women Random Assignment Compare Results Group 2 Treatment 2 Creating blocks of men and women allows us to compare results between men and women separately.

Experimental Design - Blocking Why not block for everything you can think of? Each block reduces the number of units in each group. Too many blocks will eliminate the benefits of randomization and replication. Rule of Thumb: “Control what you can, block what you can’t control and randomize for the rest”

Matched Pairs Design Match the subjects in pairs that are similar or identical to account for lurking variables more effectively than simple randomization. Matched pair designs compare 2 treatments only. Example: Compare the yield of two seed types on a farm. Create matched pairs so that the two seed types are always planted near each other. Controls for variation in sunlight, water, pests, etc. Randomize which of the pair receives which treatment (left/right, first/second). Individuals can be paired with themselves (before/after experiments). Data is the difference between the 2 measurements.

Experimental Design - Matched Pairs Imagine an experiment to test the effect of a new fitness program on the number of push-ups high school PE students can do. Each subject is paired with another student who can do the same number of push-ups before the fitness program Treatment 1 Random Assignment 2 students 0 push-ups Calculate Difference Treatment 2 Treatment 1 2 students 1 push-up Random Assignment Subjects Calculate Difference Treatment 2 Treatment 1 2 students 10 push-ups Random Assignment Calculate Difference Treatment 2 Matched pair design eliminates the factor of the students’ fitness before they start the program.

Other Experimental Design Ideas Blind experiment – Subject does not know which treatment he/she is receiving. Double Blind experiment – Neither the subject nor the experimenter know which treatment a subject received. Placebo effect – Positive response of a subject to a “dummy” treatment. If not designed as a separate “treatment” this can be a lurking variable in many experiments.

Experiment – Effect on Your Pulse Rate of a Fast Walk. Each subject (you) will measure his/her pulse rate before walking and after walking. - Measure your resting pulse for 30 seconds and double the value to get beats per minute. - You will walk quickly for 1 lap around the set of basketball hoops. - Immediately after measure your pulse for 30 seconds and double the value to get beats per minute. - Write your data on the board as a matched pair: (Before walking, After walking)

Matched Pairs Design – Effect on Your Pulse Rate of a Fast Walk. 1)Enter the resting pulses in L1 and the after walking pulses in L2. 2) Enter L2 – L1 into L3. 3) Find the mean and standard deviation for the data set in L3. What do the mean and standard deviation mean? Is this significant data that a fast walk increased a person’s pulse rate?

Completely Randomized Design – Effect on Your Pulse Rate of a Fast Walk. 1) Every student will be randomly assigned to the resting or walking group. 2) If you get a red card you are in the resting group – write your resting pulse on the board. 3) If you get a black card you are in the walking group – write your walking pulse on the board. 4) Enter the resting pulses into L1. 5) Enter the walking pulses into L2. 6) Determine the mean and standard deviation for L1 and L2 separately. What do the means and standard deviations mean? Is this significant data that a fast walk increased a person’s pulse rate?

Experiment – Effect on Your Pulse Rate of a Fast Walk. - Which experimental design (matched pairs vs. randomized experiment) is better? Why?

Does plugging your nose affect your ability to taste the difference between milk and dark chocolate? Design an experiment to answer the question above. Work with your table to do this. Consider randomization, control, blocking, replication, matched pairs, blinding and other aspects of experimental design. The class will be your potential experimental subjects. You will have a total of 8 milk and 8 dark chocolate squares for your experiment. We will select one table to conduct the study. If selected you will conduct your study and tabulate your results.

Does plugging your nose affect your ability to taste the difference between milk and dark chocolate? Each table will have 2 minutes to present their experimental plan. We will vote for the best plan (you can’t vote for yourself). If selected you will conduct your study, tabulate your results and report your findings to the class.

Does plugging your nose affect your ability to taste the difference between milk and dark chocolate? Often experiments don’t go exactly as planned and issues are only found after the experiment has begun. Based on the results of the chocolate experiment, revise the experimental plan that was used in order to address any issues that arose. Each person should write their own version of the revised plan. I will collect your revisions.