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PSYC 2030 > Chapter 8 > Flashcards

Chapter 8 Flashcards

1
Q

Factor means

A

an independent variable

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2
Q

Factorial means

A

More than one independent variable

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3
Q

Factorial Design

A

An experiment that contains more than one IV.

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4
Q

Factorial Notation

A

A factorial is described with a numbering system that simultaneously identifies the # of IVs and the # of levels of each IV.

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5
Q

The # of digits =

A

The number of IVs.

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6
Q

The value of digits =

A

The # of levels of that IV.

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7
Q

In order to determine the number of conditions or cells,

A

we multiply the numbers in the notation.

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8
Q

In factorial designs, levels and conditions

A

cannot be used interchangeably, they now refer to different things.

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9
Q

A cell matrix helps

A

us figure out what the study is about.

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10
Q

The inferential statistic to be used in a single-factor two-level design is

A

A t-test.

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11
Q

The inferential statistic to be used in a single-factor multi-level design is

A

The one-way analysis of variance (ANOVA), is followed by a post-hoc test if the ANOVA is significant.

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12
Q

The ANOVA is performed and within it,

A

The inferential statistics are performed on the main effects and the interaction effects.

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13
Q

Main Effect

A

Refers to the overall effect of one particular IV.

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14
Q

The number of main effects =

A

The number of IVs.

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15
Q

To determine the main effect,

A

we combine the data over all levels of the other factor.

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16
Q

We find the mean in the cell matrix by

A

Adding the values of the two levels and dividing them by the number of IVs.

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17
Q

Interaction Effects

A

Occurs when the effect of one IV depends on the level of another IV.

18
Q

Interaction effects take precedence over

A

Main effects

19
Q

The advantage of factorials over single-factor designs is that

A

It is possible to detect interactions that provide more accurate results.

20
Q

In factorial designs, which is better, a line graph, a bar graph, or a histogram?

A

A line graph

21
Q

An easier, more efficient way of determining whether an interaction effect is present is by

A

Looking at the data that is plotted in a line graph. If the lines are not parallel, there is an interaction.

22
Q

The interaction is considered to be more important than the main effect because it

A

Provides a more detailed account of how the variables are related.

23
Q

The independent variable will always be on the x-axis or the y-axis?

A

The y-axis.

24
Q

If we have a study with 2 IVs and want to determine if the main and interaction effects are statistically significant, we will perform

A

An ANOVA test.

25
Q

An ANOVA is an

A

umbrella term for inferential statistics that you perform on each possible effect.

26
Q

Each inferential test is called an

A

F-test

27
Q

If a study has more than one dependent variable, we will have to draw

A

a separate graph for each dependent variable.

28
Q

Ceiling Effect

A

When the mean of 2 or more conditions are near the maximum it gives the impression that no difference exists between them.

29
Q

The floor effect is the exact opposite of a

A

Ceiling effect

30
Q

Mixed Factorial Design

A

Atleast one IV is a between-subject and another IV is a within-subject.

31
Q

Factorial designs can be

A

completely between-subject or completely within-subject.

32
Q

Between-subject

A

All IVs are between-s factors and each condition has a different set of Ss.

33
Q

Within-subject

A

All IVs are within-s factors and the same set of Ss is tested across all conditions.

34
Q

P x E

A

P = person (subject)
E = environment (manipulated)

35
Q

In a Mixed Factorial,

A

at least one IV is a between-subject factor and one IV is a within-subject factor. Now we have two control problems. Creating equivalent groups for the between-subject and controlling for order effect for the within-subject.

36
Q

P x E Factorial Design

A

These between-subject designs have a manipulated IV and a subject IV.

37
Q

P represents

A

subject variable

38
Q

E represents

A

manipulated variable

39
Q

The P x E Factorial Design involves a

A

-Between-subject factor
-Within-subject factor
-Manipulated variable
-Subject variable

40
Q

If the ANOVA indicates that the interaction effect is statistically significant, that gives us the green light to perform a

A

Simple effects analysis to determine the more detailed nature of that interaction and whether these comparisons are statistically significant.

41
Q

Simple Effects Analysis

A

Breaking down the interaction to further understand it. It examines the IV at each level of the other IV.

42
Q

We don’t compare conditions in the matrix that are

A

Diagonal to one another.

PSYC 2030 (9 decks)

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