1. Arrangements or patterns for producing data are called designs

2. Anecdotal Evidence
Evidence based on haphazardly selected individual cases, which often come to our attention because they are striking in some way.
One of the scientific rules is that anecdotal evidence doesn't cut it (at least not alone).
The main value of the collection of anecdotal evidence is that it might inspire someone to look into the matter properly.

3. Basic Terms
Available data are data that were produced in the past for some other purpose but that may help answer a present question.
Population: The collection of individuals or items of interest
examples: all residents of KY, all hospitals in U.S., all trees in a forest
Sample: The subset of the population on which we make measurements. We call the measurements data.

4. Experiment: a planned activity whose results yields data
Select 3 people and record weight
Flip 8 coins and count # of heads
Sampling frame: list of elements in population
Simple random sample: sample selected such that all possible samples have an equal chance of being selected

5. Inferential Statistics
Methods of making inference about a population based on the information in a sample 
We wish to control the probability of errors
How do we select the sample?
How large is the sample?
How do we collect the data?
How do we analyze the data?

6. Types of Data qualitative: non-numerical categorization
Gender, religion preference, hair color
quantitative: numerical data
discrete: things that can be counted
# of children, # of accidents
continuous: things that are measured
time, weight, distance

7. statistic: a numerical characteristic of a sample
parameter: a numerical characteristic of a population

8. Design of Experiments: Basic Vocabulary
The individuals on which the experiment is done are the experimental units.
If human, they are called subjects.
Treatments are specific experimental conditions applied to the units.
Independent variables in an experiment are often called factors.
Specific values of these factors are classified as levels.

9. Principles of Statistical Design of Experiments
Control the effects of lurking variables on the response, most simply by comparing two or more treatments
Randomize: use chance to assign subjects to the treatments
Table of random digits
Random number generator
Replicate: reduces the role of chance variation and makes the experiment more sensitive to differences among the treatments

10. Sampling Design
Voluntary Response Sample: consists of people who choose themselves by responding to a general appeal
Simple Random Sample: consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected
Probability Sample: sample chosen by chance; must know what samples are possible, and what probability each possible sample has

11. Stratified Random Sample: Divides population into groups of similar individuals, called strata, then chooses separate simple random samples in each stratum and combines these to form the full sample
Multistage samples select successively smaller groups within the population in stages, resulting in a sample consisting of clusters of individuals. Each stage may employ a simple random sample, a stratified sample, or another type of sample.