 Producing Data: Experiments Vs. Surveys Chapter 5

Discussion Example 1  One school board member noticed that students in band tended to be in the top 25% of their school. She compiled a list from each high school’s band director and took a random sample of 25 students from each school’s band.  She then took a random sample of 25 students from each high school that wasn’t in band. She found a slightly higher average G.P.A. of student’s in band.

Discussion example 1  Will this study give evidence that being in band causes an increase in a students G.P.A?  Will this study help her generalize that student’s in band tend to have a slightly higher G.P.A. than students not in band?

Vocabulary from example 1  Observational study  a study based on data collected from individuals that meet a determined criteria ie study or survey  Lurking variable  an outside factor that is not the explanatory nor response variable  prevents causal relationships from being established in observational studies  associated with observational studies, so they are difficult to minimize

Discussion Example 2  Another school board member is surprised the increase is so slight. First, he s each band director and asks for a list of 30 students. He then accesses each high school’s roster, takes the first 40 listed striking any student’s name he already has. He found the average G.P.A. of student’s in band to be more significant than the first study.

Discussion example 2  Will this study give evidence that being in band causes an increase in a students G.P.A?  Will this study help her generalize that student’s in band tend to have a slightly higher G.P.A. than students not in band?

Discussion example 3  Walmart is considering buying a gasoline additive that is suppose to improve gas mileage. They found 30 employees in Texas that drive the same car. Fifteen employees are randomly selected to receive the additive, the remaining fifteen are given a bottle with just gas. Each employee is given a set route around the city to drive. The gas mileage is recorded by an onboard computer which shows the additive gives the driver 12% better gas mileage.

Discussion example 3  Will this study give evidence that using the additive will give a car better gas mileage?

Vocabulary from example 3  Experiment  a planned study where deliberate conditions are imposed to see how the response variable will change  Confounding variable  a variable associated (noncausal) with the explanatory variable that affects the response variable in some way  prevents us from knowing causation  associated with experiments

Lurking versus Confounding Observation study xy z Lurking Experiment xy z Confounding ? ?

Randomized comparative experiments  Goal of an experiment:  collect statistically significant evidence for a cause-and-effect relationship.

Principles of Experimental Design  comparison minimizes effects of confounding variables allowing effects of treatments to be better evaluated 1. Control :  using comparison ensures that outside factors operate equally on all groups  control groups allow us to accurately assess the change in the response variable

Principles of Experimental Design 1. Control : 2. Randomization :  use of impersonal chance in order to equalize unanticipated factors so that groups should be similar in all respects.  homogenous groups reduce variability allowing better assessment of treatments

Principles of Experimental Design 1. Control : 2. Randomization : 3. Replication :  perform the experiment on as many subjects to reduce chance variation in the results

Homework  Packet p. 92 1) Determine if experiment or observation study/survey 2) If study/survey, identify sampling method and one source of bias

Experimental Design Examples  Read each design example and write a description on how each experiment should be run.  Key terms: groups, treatments, comparison, randomization

Completely Randomized Design Random Allocation Group 1 15 babies Group 2 15 babies Treatment 1 Her product Treatment 2 Competitor’s Compare weight gain Babies will be numbered 01 to 30. Using a random number table, the first 15 selected will be in Group 1 with the remaining placed in group 2. Each babies’ weight will be measured in pounds and compared.

Block Design Subjects African American men White men Random assignment Group 1 Group 2 Group 3 Group 4 Treatment 1 Calcium Treatment 2 Placebo Compare blood pressure All African American men will be assigned a random number. Half the men who have the smallest numbers will be assigned group 1, the half with the largest numbers will be assigned group 2. The process will repeat for the white men. The reduction in blood pressure will be compared.

Matched pair Design Random Allocation Group 1 Group 2 Treatment 1 left hand Treatment 2 right hand Compare difference A coin will be flipped to decide which hand will be measured first by each participant. Heads will squeeze the left hand first, tails will squeeze the right hand first. The different in the pounds on the scale will be compared. Treatment 1 left hand Treatment 2 right hand

Calcium experiment revisted  What potential problems might be have because we started with random assignment?  How should we alter our experiment? Random Assignment Group 1 Group 2 Treatment 1 Calcium Treatment 2 Placebo Compare blood pressure

Block Design All participants African American men White men Completely randomized experiment

Improving the Design  A block is a group of experimental units or subjects that are known before the experiment to be similar in some way that is expected to affect the response to the treatments.  Block design has the same rationale as a stratified random sample.  Blocks allow us to reduce the amount of variation to improve the accuracy of our conclusions by creating homogeneous groups.  single blind versus double blind

Improving the Design  In a matched pair design, each subject in the experiment will receive two (and only two) treatments.  The order that each subject receives both treatments is randomly selected to preserve the important aspect of randomization.