Stats 119 - Lecture 1

Only thos ewho volunteer information is recorded

individuals selected to be in the sample who do not respond to the survey have different opinions from those who do

Individuals, subjects, or elements under a study. Basically people or objects we gather information about

anything in a survey design that influences responses

observes individuals and measures variables of interest but does not attempt to influence the responses

Looks back on past data or information

Observational study that follows subjects through set time line without interfering with these individuals

Researchers apply treatment. They do have a say in what goes on then they observe

Compares effects of different treatments and views results. Direct affect on what each group does.

the individuals on which the experiment is done

Things that affect the outcome of the study

Specific condition applied to the experimental unit/subject(s)

Dummy treatment that does nothing

Fake treatment that improves the patient's condition

an observation whose true purpose is hidden from both the observer and the person being observed

Subject does not know which treatment they have received but researchers have the knowledge

an observed effect so large that it would rarely occur by chance

the treatments are assigned to all the experimental units completely by chance

participants are matched based on as many matching variables as possible.
Give 2 different treatments and compare the results

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

A variable that effects outcome but is unknown to researchers

A variable that effects outcome but is impossible to determine which variable effects outcome more.

Characteristics of individuals measured and units. They can differ from one individual to the next

A variable that is not a number but can produce a number of how many individuals fall within a category (EX: Number of peolpe above 5 feet tall)

Numerical values

n= Sample Size
Measurements made on sample data

Comes from sample and is a measurement based on a SAMPLE

N=Population Size
Entire collection of individuals/elements that are being studied. This is unknown most of the time unless there is. a small population

Measurements made on a population's data. Basically data from entire group

Tendecy to favor selecting people or elements. Poor sampling plan causes sampling bias

1. Slect individuasl at random
2.More sample size

Attempt to survey every individual in a population.
*Some residents left out
*Populations ar enot static
*Some people do not complete all information asked for
*Cost is high

Each member of population has exact same change of being chosen . (Ex: names in a hat)

Taking some from all
*Subjects are in non overlapping groups
*Random selection from all these groups (Choose some from all the groups)

ALL FROM SOME
Take a SRS of groups then sample all items within slected clusters (Groups)

*Seperate into random groups
*Slelect random groups
*Take all informaiton from sleect groups