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Gathering Useful Data for Examining Relationships: Chapter 4 by Mind Map: Gathering Useful Data for
Examining Relationships: Chapter 4
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Gathering Useful Data for Examining Relationships: Chapter 4

Cause & Effect

Yes

No

Experiment

Control Groups

Placebo

Blinding

Double Blinding

Single Blinding

Double Dummy

Pairing & Blocking

Matched Pair Designs

Block Design

Repeated Measure Designs

Randomization

Randomizing type of treatment, Chances of being assigned same for each participant

Randomizing order of treatment

Research Studies

Observational

Observe or Question

Weaker cause & effect relationship

Experimental

Manipulate

Randomization is a crucial element

Volunteers

Stronger cause & effect relationship

Study Units

Subjects

Participants

People

Difficulties and Disasters

Confounding Variables

Extending results inappropriately

Interacting variables

Hawthorne and experimenter effects

Ecological validity and generalizability

Using the past as a source of data

Rule for concluding cause & effect

Cause-and-effect relationships can be inferred from randomized experiments but not from observational studies.

Look at Variables

Response (aka, outcome or dependent)

Categorical data

Quantitative data

Confounding

Lurking

Explanatory

Independent

Observational Studies

Case Control

Efficient

Reduces confounding variables

Retrospective (looking back)

Prospective (looking forward)

Confounding variables

Less likely to be problem for randomized experiment

Lurking Variable

Related to explanatory variable