Designing Experiments Chapter 2 Designing Experiments 1

Definitions: 1) Observational study - observe outcomes without imposing any treatment 2) Experiment - actively impose some treatment in order to observe the response

Experimental unit – the single individual (person, animal, plant, etc Experimental unit – the single individual (person, animal, plant, etc.) to which the different treatments are assigned Factor – is the explanatory variable – it’s what we test Level – a specific value for the factor

Response variable – what you measure Treatment – a specific experimental condition applied to the units

Control group – a group that is used to compare the factor against; can be a placebo or the “old” or current item Placebo – a “dummy” treatment that can have no physical effect

blinding - method used so that units do not know which treatment they are getting double blind - neither the units nor the evaluator know which treatment a subject received

Definition: Confounding variable – A variable whose effect on the response cannot be separated or distinguished from the effects of the factor on the response. - a variable that is related to both group membership and the response variable of interest in a research study Because observational studies may contain confounding variables, their results can NOT be used to show cause-effect relationships.

Principles of Experimental Design Control the effects of extraneous variables on the response Randomization – the use of chance to assign subjects to treatments Replication of the experiment on many subjects to quantify the natural variation in the experiment

The ONLY way to show cause & effect is with a well-designed, well-controlled experiment!!!

Example 1: A farm-product manufacturer wants to determine if the yield of a crop is different when the soil is treated with three different types of fertilizers. Fifteen similar plots of land are planted with the same type of seed but are fertilized differently. At the end of the growing season, the mean yield from the sample plots is compared. Experimental units? Factors? Levels? Response variable? How many treatments? Plots of land Type of fertilizer Fertilizer types A & B Yield of crop 2

Why is the same type of seed used on all 15 plots? Example 3: A farm-product manufacturer wants to determine if the yield of a crop is different when the soil is treated with three different types of fertilizers. Fifteen similar plots of land are planted with the same type of seed but are fertilized differently. At the end of the growing season, the mean yield from the sample plots is compared. Why is the same type of seed used on all 15 plots? What are other potential extraneous variables? Does this experiment have a placebo? Explain To control the factor of type of seed. Type of soil; amount of water, sunlight, etc. No, one would compare the three types of fertilizers It is part of the controls in the experiment. Type of soil, amount of water, etc. NO – a placebo is not needed in this experiment

Example 2: A consumer group wants to test cake pans to see which works the best (bakes evenly). It will test aluminum, glass, and plastic pans in both gas and electric ovens. Experiment units? Factors? Levels? Response variable? Number of treatments? Cake batter Two factors - type of pan & type of oven Type of pan has 3 levels (aluminum, glass, & plastic & type of oven has 2 levels (electric & gas) How evenly the cake bakes 6

Experimental Designs Completely randomized design –experimental units are assigned at random to treatments Talk through the process of the experimental design. Treatment A Measure response for A Experimental Units Random Assignment Compare treatments Treatment B Measure response for B

Experimental Designs Continued . . . Units should be blocked on a variable that effects the response!!! 2. Randomized block – units are blocked into groups (homogeneous) and then randomly assigned to treatments Treatment A Measure response for A Block 1 Random Assignment Compare treatments for block 1 Treatment B Measure response for B Compare the results from the 2 blocks Experimental Units Create blocks Treatment A Measure response for A Block 2 Random Assignment Compare treatments for block 2 Treatment B Measure response for B

Matched pairs - a special type of block design match up experimental units according to similar characteristics & randomly assign on to one treatment & the other automatically gets the 2nd treatment have each unit do both treatments in random order

Pair experimental units according to specific characteristics. Treatment A Treatment B Next, randomly assign one unit from a pair to Treatment A. The other unit gets Treatment B. Pair experimental units according to specific characteristics. This is one way to do a matched pairs design – another way is to have the individual unit do both treatments (as in a taste test or “before and after”).

What type of design is this? Why use this method? Example 3: Suppose that the manufacturer wants to test a new fertilizer against the current one on the market. Ten 2-acre plots of land scattered throughout the county are used. Each plot is subdivided into two subplots, one of which is treated with the current fertilizer, and the other with the new fertilizer. Wheat is planted and the crop yields are measured. What type of design is this? Why use this method? When does randomization occur? Matched - pairs design Randomly assigned treatment to first acre of each two-acre plot

Is this an experiment? Why or why not? Example 5: Four new word-processing programs are to be compared by measuring the speed with which standard tasks can be completed. One hundred volunteers are randomly assigned to one of the four programs and their speeds are measured. Is this an experiment? Why or why not? Yes, a treatment is imposed. Yes, a treatment was imposed Completely randomized one factor, word processing program & 4 levels, the four new programs Speed at which standard tasks can be done What type of design is this? Factors? Levels? Response variable? Completely randomized one factor: word-processing program with 4 levels speed

Can this design be improved? Explain. Example 5: Four new word-processing programs are to be compared by measuring the speed with which standard tasks can be completed. One hundred volunteers are randomly designed to one of the four programs and their speeds are measured. Is there a potential confounding variable? You could do a block design where each person uses each program in random order. a) Speed/expertise of each individual b) Use a matched pairs design where each volunteer uses all four programs in random order Can this design be improved? Explain. NO, completely randomized designs have no confounding