Quasi Experimental, Correlational and Descriptive Designs Flashcards

1
Q

What are the general issues of non-experimental designs?

A

Third variable issue (hard to anticipate what the effect of the third variable may be, also hard to establish is variable A is caused by variable B)

Varying reliability of measures (have to be sure the measures are reliable, confuse low reliability and a lack of relationship between 2 variables.

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2
Q

What are non-manipulation designs?

A

No randomisation
No manipulation, more realistic

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3
Q

When can non-manipulated designs be used?

A

Manipulation isn’t possible
Naturalistic setting
Establish an association
Temporal change
Developing/refining measures
Explanatory models
Natural variation

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4
Q

What are quasi-experimental designs?

A

No randomisation
cause and effect relationship
Uses DV and Quasi-independent variables

Quasi-independent variable: variable that naturally varies and isn’t directly manipulated by the researcher

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5
Q

What are the advantages/disadvantages of a quasi-experimental design?

A

+ determine cause and effect relationships and generalisation of findings to the real world

  • Lack of precise control over natural events, influence of extraneous variables
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6
Q

What is a correlational design?

A

Indicates strength of relationship amongst variables
Relationships aren’t always causal
No manipulation or randomisation

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7
Q

What are the strengths and weaknesses of a correlational design?

A

+ estimates strength and direction of relationship amongst variables

  • doesn’t permit the determination of cause and effect relationships, no causation
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8
Q

What are lab experiments?

A

Manipulation of IV
Measures DV

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9
Q

What are the strengths and weaknesses of a lab experiment?

A

+ determine cause and effect relationship

  • data obtained in an artificial lab
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10
Q

What are cross sectional designs?

A

Collect information in the presence of one or more variables, as they exist in a defined population in one point of time
Study people who differ in age very often
Data analysed to determine the distribution of one or more variables

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11
Q

What are the strengths and weaknesses of a cross sectional design?

A

+ age differences, not expensive, little time to conduct

  • extraneous differences between cohorts rather than true changes
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12
Q

What is a cohort?

A

group of people of the same age who are exposed to similar cultural environments and historical events as they are growing up

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