1. Designing Experiments
The Caffeine Experiment

2. Designing Samples Population vs Sample
Is a part of the population that we actually examine in order to gather information
Entire group of individuals that we want information from.
Sampling - involves studying a part in order to gain information about the whole
Census - attempts to contact every individual in the entire population

3. Bias
The design of a study is BIASED if it systematically favors certain outcomes

4. Bias on Wording
Confusing or leading questions can introduce strong bias, and even minor changes in wording can chance the survey’s outcome
Never trust the results of a sample survey until you have read the exact questions posed.

5. 2. Stratified Random Sample
Designing Samples
1. SRS
Simple Random Sample is choosing a sample by equal chance.
2. Stratified Random Sample
Grouping sample with similar individuals called strata. Then choosing an SRS in each stratum.
3. Multi-stage samples
Grouping sample into clusters, then employing an SRS, Stratified RS, or another type of sampling design

6. Placebo Effect
Placebo Is Something That Is Identical (in appearance, taste, smell, etc.) To The treatment received by the treatment group, except that it contains no active ingredients.

7. When a person doesn’t know who is receiving which treatment, that person is BLIND.
When every individual in one of these classes is blinded, the experiment is called SINGLE BLIND.
If every individual in both classes is blinded, then the experiment is DOUBLE BLIND

8. Four Key Principles of a Good Experiment:
Principle #1: DIRECT CONTROL means holding extraneous variables constant for all treatment groups so that their effects are not confounded with the explanatory variable.

9. Principle #2: BLOCKING is when subjects are divided into homogeneous groups (blocks) based on some extraneous variable and then separated into different treatment groups.
What if men have different pulse rates than women?
• The differences in pulse rate due to gender will be an additional source of variability in our experiment, which will make it harder to see the difference due to the treatment.
How can we eliminate this source of variability?
• Eliminate one gender from the study, but then we could only draw conclusions about one gender
• Make sure there is a representative number of men and women in each treatment. For example, if there are 20 women and 30 men in the experiment, then the experimental group should have10 women and 15 men and the control group should have the same.
• In this example, we have formed 2 blocks: men and women. Then, we assigned treatments to the subjects within each block.

10. Principle #3: RANDOMIZATION is random assignment of subjects to treatments to ensure that the experiment doesn’t systematically favor one treatment over the other.
How do we randomize?
Draw names from a hat. The first half chosen are in one group, the remaining names in the other.
Number the class from Then, generate random numbers without replacement until half are chosen for one group. The remaining names go in the other group.
For matched pairs we can flip a coin to determine which subjects go into which group. If its heads, the first person in the pair goes to A and the other to B. If its tails, it’s the opposite.

11. Principle #4: REPLICATION means ensuring that there is an adequate number of observations in each treatment group.
Increasing the SAMPLE SIZE makes randomization more effective. The more subjects we have, the more balanced our treatment groups will be. For example, if we have 10 subjects and only 2 have a certain unknown characteristic, it is quite likely that both of those subjects will end up in the same treatment group simply by chance.

12. Classwork
1. EXPLAIN WHY BLINDING IS REASONABLE STRATEGY IN MANY EXPERIMENTS?
2. GIVE AN EXAMPLE OF AN EXPERIMENT FOR EACH OF THE FOLLOWING:
SINGLE-BLIND EXPERIMENT WITH THE SUBJECT BLINDED
SINGLE-BLIND EXPERIMENT WITH THE INDIVIDUALS MEASURING THE RESPONSE BLINDED
DOUBLE-BLINDED EXPERIMENT
AN EXPERIMENT THAT IS NOT POSSIBLE TO BLIND