RM - Intro to Design + Data Flashcards

1
Q

WithinControl Condition

A

Helps understand the role of the IV + rule out alternative explanations for results

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2
Q

Extraneous Variable.

A

Not controlled in the experiment, could effect the DV - unlikely to change the direction of the effect

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3
Q

Confounding Variables

A

Extraneous variable that varies systematically with the IV to influence the DV

E.g. Every Monday class there is a football match outside

Likely to influence the results change the direction of events

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4
Q

Between subject Experimental design

A

Either in 1 condition or the other
Each ppt contributes to 1 data point

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5
Q

Between subject design benefits

A

1) Avoids pt/experimenter effects
2) Avoids order+ fatigue effects

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6
Q

Between subject design disadvantages

A

1) Takes longer
2) Is less powerful
3) Introduces variation due to indiv differences

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7
Q

within subject design

A

Takes part in both conditions compare your score in 1 condition and another

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8
Q

Within subject design Benefits

A

1) Accounts for indiv differences
2) cost + time effective (recruit half as many ppt)

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9
Q

within subject design disadvantage

A

order effects and fatigue Effects

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10
Q

Matched pairs Design

A

Different ppt in all conditions, ppts matched e.g Twin Studies

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11
Q

Matched pairs Design Benefit

A

1) Accounts for indiv differences

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12
Q

Matched pairs Design Disadvantage

A

Difficult to match people accurately so matched on what is relevant to the experiment

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13
Q

categorical Data

A

nominal and ordinal
labels
can be called discrete

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14
Q

Nominal categorical Data

A

No hierarchical order
can be presented as frequencies

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15
Q

ordinal categorical Data

A

Have hierarchy
e. g illness stage

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16
Q

Numerical/continuous data

A

Presented as means and standard deviations in text, graph or table

17
Q

Interval continuous data

A

scalar that has no meaningful zero
Temperature

18
Q

Ratio continuous data

A

scalar with an absolute data, time, heartrate

19
Q

Standard Error

A

standard deviation divided by square root of N

20
Q

Z scores

A

Standardised score
represents datapoints relationship to the mean
useful when comparing ppts or conditions
useful when the units differ (scores out of 10 VS 25

21
Q

Z score equation

A

(score-mean)/Standard deviation