1. Sampling and Experimentation
Population: The entire group or observational units of interest
Sample: A small part of population from which data is collected to learn about the population as a whole.
Why Sample????
Parameter: A number that describes a population.
Most common parameters are mean or proportion
Statistic: A number that describes a sample
Simple Random Sample: EVERY group of n individuals chosen from
The population has the same probability of being chosen
Define the population
Choose the sample size
Assign a number or id to every member of the population
Find random numbers – table, calculator, raffle
Use the random numbers to select individuals from the population to measure

2. Sampling Methods
Simple Random Sample (SRS): A method of sampling where every sample of size n has an equal opportunity to be chosen.
Advantage: Completely random. Unbiased in the long run.
Disadvantage: Possibility for wide variability, difficult to access units
Subject to outside biases (non-response)
Stratified Random Sample: Start by classifying the population into
Groups of similar individuals called strata (singular: stratum). Chose a separate SRS in each stratum and combine these to form the sample.
Advantage: Includes units from several categories. Lower variability.
Disadvantage: Stratum must be chosen appropriately
Cluster Random Sample: Start by grouping the population into groups that are near each other called clusters. Use SRS to choose one cluster then all individuals in the chosen cluster are included in the sample.
Advantage: Low cost and easy to access sample
Disadvantage: Each cluster must resemble the population
Systematic Sample: Randomly choose one of the first n units to be sampled. Then follow by choosing every d unit to continue through the population.
Advantage: Good for units that are produced through time
Disadvantage: Not really random as not all combinations can be sampled.

3. Surveys and Bias
Population: The entire group or observational units of interest
Sample: A small part of population from which data is collected to learn about the population as a whole.
Parameter: A number that describes a population.
Most common parameters are mean or proportion
Statistic: A number that describes a sample
Survey: Gathering information about individuals by asking questions.
Census: A survey conducted on the entire population
Why Sample??? We usually can not talk to everyone in the population!!!
Sample Bias: A sampling procedure is said to have sampling bias if it systematically underestimates certain segments of the population and overestimates others. This gives results that do NOT accurately reflect the population.

4. Types of Survey Bias
Voluntary Response Bias: people who choose themselves by
Responding to a general invitation
Nonresponse Bias: People can not be reached or choose not to participate
Quota Sampling Bias: Interviewers choose people to obtain a certain percentage in different categories (poor stratification)
Response Bias: People answer a certain way to impress the interviewer or to avoid embarrassment
Selection (Undercoverage) Bias: The participants are chosen in a non-representative way. These are often convenience samples
Wording Bias: The questions are worded in such a way as to lead towards specific responses

5. Experimentation
Observational Study: observes individuals and measures variables of interest but doesn’t attempt to influence the results.
Experiment: Deliberately imposes a treatment on individuals to measure their responses.
Only an EXPERIMENT can be used to describe CAUSE and EFFECT.
Explanatory Variable: The variable we are changing.
Response Variable: The outcome variable that may be affected by the original change.
Experimental Design:
Comparison – use a design that compares 2 or more treatments
Random Assignment – Use a random number process to assign experimental units to treatments
Control – Keep as many variables the same as possible between the treatment groups. This avoids confounding and reduces response variation (BLOCKING)
Replication – Use each treatment on enough experimental units to distinguish actual change from chance variation.

6. Example Draw a diagram to outline the experiment: 2000 men 4000 men
A researcher wants to know if exercise will reduce the risk of a heart attack. Which scenario is an experiment and which is an observational study?
Find 2000 men over 40 who exercise regularly and have not had a heart attack. Pair them up by similar characteristics with another 2000 men who don’t excersize. Track each pair of men over the next 5 years.
Find 4000 men over 40 who have not had heart attacks and are willing to participate in a study. Assign 2000 of them to a specific, supervised work out plan, while the other 2000 continue their regular habits. Track each of the men over the next 5 years.
Draw a diagram to outline the experiment:
Volunteers –
NOT random
Treatment 1
Supervised
exercise
2000 men
Compare
Rate of heart attacks
4000 men
R.A.T.
2000 men
Random
Assignment
Of Treatment
Treatment 2
Normal routine

7. Experimental Design Example
A utility company wants to encourage customers to conserve energy in their homes. They have an electronic device which can display energy usage and costs to customers. This device is somewhat costly. They also have brochures available to educate consumers on energy saving ideas. They want to conduct an experiment to see if the display device is effective and worth the cost. They have 60 homeowners willing to participate in the experiment.
Experimental Units –
Explanatory variable –
Treatments –
Response variable –
households
Information source
Electronic device, brochure or control
Total electricity used in a year
Treatment 1
Display
20 homes
Compare
Energy
Use
Treatment 2
Brochure
60 homes
R.A.T.
20 homes
20 homes
Treatment 3
Control

8. Blocked Design
If there is an extra variable that we RECOGNIZE may effect responses but can’t control for it,
We can BLOCK for that variable. (Like Stratified Sampling)
Twelve people who suffer from chronic fatigue syndrome volunteer for a study to see if shark fin extract will increase one’s energy. 8 volunteers are men and 4are women. Researchers feel the extract may effect men and women differently, so they want to do a blocked experiment. They plan to give half of the volunteers the extract and the other half will get a placebo.
Treatment 1
Extract
Treatment 2
placebo
4 men
8 men
4 women
RAT
Compare energy level - men 12
Volunteers
Treatment 1
Extract
Treatment 2
placebo
2 women
RAT
Compare energy level - women

9. A study of human development showed two types of movies to groups of children. Crackers were available in a bowl and researchers compared the amount of crackers eaten by children in different types of movies. Movies were shown at 8 am and at 11 am children show up at 8 am while 120 show up at 11 am. Design a blocked experiment to compare how the type of movie shown affects the consumption of crackers.
Explanatory Variable:
Response Variable:
Other Variable to be blocked: