Ap Stats Summer Reading

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Francis Bacon

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(1561-1626) inventor of modern science; casual observation is not enough to establish relationships

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comparitive expirement

Back 2

an expirement comparing two groups of people

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randomized expirement

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expirement using a random device

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expirement

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active manipulation of a subject and then careful oberservations/recording of the events that result; helpful in establishing causal relationships

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causal relationship

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establishing that one thing is the cause of something else

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observational study

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no intervention, just observations of a certain situation; more difficult to establish causal relationships; descriptive studies; suggest relationships but do not provide proof

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descriptive study (purpose)

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to observe and gather data; suggest relationshiups for future study

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randomness required for what inferences

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1)inferring characteristics from a sample to a whole population
2)inferring a cause-effectrelationship

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random selection

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also called random sampling; necessary to infer from sample to population; tends to produce smaples that represent the diversity of the population

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random assignment

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necessary to be able to infer a cause-effect relationship; assign treatments randomly so that extraneous variables will not give any group an advantage/disadvantage

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goals of an expirement

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1)demonstrate/explain the causes of an observed outcome
2)assess the effect of manipulating a (known) causal variable w/ the intent of a particular effect

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how to extablish a causal relationship

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1)random assignment 2)sound expiremental methodaology 3)logic

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big saying

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correlation does not imply causation

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requirements (Mill) for extablishing causal relationship btwn X & Y

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1)X preceeds Y
2)X is related to/associated with Y
3)No plausible alternative explanation for Y, other than X, can be found

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prospective study

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looks forward. gather data; consider a variable that may affect the data; collect follow-up data.
easy to establish time sequence

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retrospective study

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looks backward. notice the effect first; rewinds to find the potential cause of the effect. difficult b/c there are many possible causes for a single event

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Statistics

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study of variation; how to quantify it, control it, and draw conclusions from it.

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treatments

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set of circumstances manipulated by the expirementor

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expiremental unit

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smallest unit to which a treatment is applied at random and a response is obtained

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design of expirement

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overall plan for conducting the expirement. good design makes it possible to give unambigious answers to questions

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scope of inference

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what the investigator can ultimately infer from the expirement; determined by sampling procedure

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strategies for designing an expirement

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1)eliminate sources of variability
2)isolate sources of variabity so that their effect can be later seperated
3)ensure that the remaining sources of variability produce only chancelike variability

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confounding variable

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extraneous variable that makes us unable to distinguish which variable produced the result.

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how to eliminate sources of variability

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1)direct control-holding the potential source constant
2)blocking or grouping
3)randomization
4)replication
5)control group
6)use a placebo
7)conduct single-blind or double-blind expirements

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blocking

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creating groups that are similar as possible with respect ot one or more variables thought to be sources of variability

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blocks

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expiremental groups similar in some feature we would like to control

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grouping

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same as blocking expect the group size need not be equal to the number of treatments

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matched-pairs design

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experiments are paired based on the value of some vairable thought to be related to the response variable

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randomization

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random assignment to expiremental groups

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replication

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using several trials and runs; multiple observations for each expiremental condition

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single-blind experiment

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subjects don't know what treatment they've received; human mind odesn't affect outcome

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double-blind

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subjects and those measuring the response don't know what treatment the subject has received