The Practice of Statistics (Yates): Designing Samples (Lesson 5.1)

Observational study:

Observing individuals and measure variables of interest but do not attempt to influence the responses.

Experiment

Deliberately imposing some treatment on (that is, do something to) individuals in order to observe their responses.

Population

The entire group of individuals that we want information about. 

Sample

The information given from which we draw conclusions about the whole.

Sampling

Involves studying a part in order to gain information about the whole.

Census

 involves attempting to contact every individual in the entire population

Voluntary response sample

Sample that consists of people who choose themselves by responding to a general appeal.

Bias of Voluntary responses samples:

These samples are biased because people with strong opinions, especially negative opinions, are most likely to respond.

Convenience sampling:

Choosing individuals who are easiest to reach.

Biased Sampling Method

A sampling method that systematically favors certain outcomes.

How to prevent bias in choosing a sample:

allow impersonal chance to do the choosing.

Simple Random Sample:

The size of n individuals 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. This sampling method gives each individual an equal chance to be chosen (thus avoiding bias in the choice) but also gives every possible sample an equal chance to be chosen

If you don't use a computer or calculator, you can randomize by ____

using a table of random digits.

Each entry in a random digits table _ :

is equally likely to be any of the 10 digits 0 through 9

The entries in a random digits table are _

Independent of each other. That is, knowledge of one part of the table gives no information about any other part.

These are the steps of choosing an SRS:

Step 1: Label. Assign a numerical label to every individual in the population. Step 2: Table. Use Table B to select labels at random. Step 3: Stopping rule. Indicate when you should stop sampling. Step 4: Identify sample. Use the labels to identify subjects selected to be in the sample.

Probability Sample

A sample chosen by chance. We must know what samples are possible and what chance, or probability, each possible sample has.

These are the steps of selecting a stratified random sample:

first divide the population into groups of individuals, called strata, that are similar in some way that is important to the response. Then choose a separate SRS in each stratum and combine these SRSs to form the full sample.

Cluster sampling:

Divides the population into groups, or clusters. Some of these clusters are randomly selected. Then all individuals in the chosen clusters are selected to be in the sample.

Undercoverage:

occurs when some groups in the population are left out of the process of choosing the sample.

Nonresponse

 occurs when an individual chosen for the sample can't be con-tacted or does not cooperate.

Sample survey

Selects a sample from the population of all individuals about which we desire information. We base conclusions about the population on data about the sample.