stats unit 3

sampling

process of collecting data from a sample to make statements about the population

voluntary response sample

people who chose to include themselves into the sample by responding to a question or survey
- very opinionated
- unreliable and should be avoided
- bias

convenience sample

type of sample chooses individual who are easiest to reach
- bias

bias

systematically favours certain outcomes over other

simple random sampling

- "put names in a hat" , choose "n" of them
- every "n" individuals has an equal chance to be the sample actually selected

random

2 or more possible values with a known probability of being observed

stratified random sampling

sampling from a population which can be partitioned into subpopulations
- select how many units we want from each group

stratum

a group of similar individuals

multistage sampling

- multistage sampling is the taking of samples in stages using smaller and smaller sampling units at each stage
- often used when we need large numbers of respondents in close proximity to one another
- not every "n" has a chance of being selected

systematic random sampling

- start with a numbered list of all "N" individuals in the population, to select a sample of "n" individuals we randomly select a number from 1- k , where k = N/n, our sample will consist of the 4th individual on the list and every 5th individual after that.
- easy and fast
- dont need whole list of the entire population

the value of k

sampling interval

leading question

intentionally or unintentionally framed queries that prompt a respondent to answer in a particular way.

nonresponse

respondents refuse to answer the questions

census

a sample of the entire population

under coverage

when some units in the population have no chance of being included in the sample

confounding

confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association.

experimental units

the individuals on which the experiment is performed

subjects

the individuals are people

treatment

specific set of experimental conditions applied to the units

factors

explanatory variables in an experiment

completely randomized design

design in which all units are randomly assigned to receive the various treatments

placebo effect

when effects are seen in a group of people who did not actually receive a treatment.

control group

portion of participants in an experiment that are shielded from exposure to variables

double blind experiment

neither the subject nor the person knows anything about the experiment

replication

administration of each treatment to more than one unit

randomization

the experimental units to the various treatments

control

the effects of lurking variables on the response by comparing several treatments one of which may be a control treatment

replication

the assignment of each treatment to several individuals to reduce variation in the result

block

group of experimental units or subjects that are similar in ways that are expected to affect the response to the treatments

randomized block design

the random assignment of treatments to units is carried out separately within each block