Unit 7

Question 1

what are the two different groups that the independent variable has?

Answer 1

at least 2 groups
ex. control and experimental

Question 2

what are the levels of the independent variable?

Answer 2

more than two conditions within each independent variable
ex. for the independent variable “drug” there might be four levels: control dose, low dose, medium dose, high dose

Question 3

why might you want to have three or more levels of the independent variable?

Answer 3

1. researchers are interested in comparing more than two groups
2. design with only two levels of the independent variable may not provide enough information about the relationship between the independent and dependent variables

Question 4

can a curvilinear relationship (i.e inverted U curve) only have two variables?

Answer 4

NO, needs at least 3

Question 5

what is a factorial design?

Answer 5

an experimental design that involves at least two independent variables and each independent variable having more than one level
ex. for the independent variable “drug” there might be four levels: control dose, low dose, medium dose, high dose and the other independent variable “gender” has two levels: male and female
4x2= 8 different cells

Question 6

how does a factorial design work?

Answer 6

all levels of each independent variable are combined or crossed in a matrix so each cell in the matrix becomes a possible condition or treatment of the experiment

Question 7

for the independent variable “drug” there is four levels: control dose, low dose, medium dose, high dose. the other independent variable “gender” has two levels: male and female. the third independent variable “blood type” has three levels: A, B and O. how many levels or treatment conditions would we have?

Answer 7

4x2x3= 24

number of levels of first independent variable is 4, number of levels of second independent variable is 2,
number of levels of third independent variable is 3

Question 8

what are the three different ways factorial designs can be conducted?

Answer 8

between subjects
within subjects
mixed factorial design

Question 9

what are the three terms that surface regularly in factorial designs?

Answer 9

main effects
simple main effects
interaction effects

Question 10

what are main effects?

Answer 10

the consistent total effect of a single independent variable on a dependent variable over all other independent variables in an experimental design. thus there is one main effect for each independent variable.

Question 11

what does it mean that main effects are averaged over the levels of the other independent variables?

Answer 11

ex. the main effect for drug would be averaged over both males and females

Question 12

what are simple main effects?

Answer 12

the mean difference at each level of the independent variable at a particular level of the other independent variable
ex. in the drug study we would compare the means only for males

Question 13

an advantage of the factorial design is the interaction effect, what is it?

Answer 13

the interaction effect occurs as a consequence of the joint manipulation of the independent variables in a study. interactions occur when the pattern of results that occurs with the manipulation of one independent variable is disrupted or changed when another independent variable is included in the experiment
ex. as dose increases pain decreases, however one cell in the matrix resists this trend (at medium drug doses males show an increase in their perception of pain) this is an interaction between drug and gender on pain prescription

Question 14

what is the 2x2 between subjects factorial design?

Answer 14

indicates that there are two independent variables and each independent variable has two levels

Question 15

what is a 3x3x2 between subjects factorial design?

Answer 15

indicates that there are three independent variables with two three levels and one with two levels

Question 16

weed has two dose levels: zero dose and moderate dose, the other independent variable is drug history with two levels: those who have never tried weed and those who use the drug frequently, what factorial design is this?

Answer 16

2x2 factorial design

Question 17

in a 2x2 between subjects factorial design, how many null hypothesis are there?

Answer 17

three (one for each of the two main effects and one for the interaction)

Question 18

in a factorial design the first step is to look for an interaction, how do you do that?

Answer 18

graph the data (dependent variable on the vertical axis and independent variable on the horizontal axis (each level of the independent variable represents one point on the horizontal axis) a different symbol or colour is used to represent each level of the remaining independent variable)

Question 19

when does interaction occur in a factorial design?

Answer 19

when one level of an independent variable is influenced by one level of another independent variable

Question 20

how do you determine if an interaction is present or not?

Answer 20

if the lines on your graph are parallel then there is no interaction and if the lines are not parallel then there is an interaction

Question 21

if there is an interaction between variables do we reject or fail to reject the null hypothesis?

Answer 21

reject the null hypothesis for the interaction effect

Question 22

once you have established that an interaction is present or not what step is next?

Answer 22

look into simple main effects or the main effects

Question 23

if an interaction is present then why do the main effects only be interpreted in context of the interaction?

Answer 23

due to the fact that the main effect may be misleading given an interaction (the main effect may only exist because of the interaction)
ex. the main effect might be that “people eat more food when an eating companion takes more rather than less food to eat” but in this case there is an interaction (body type) so “people eat more food when an eating companion overindulges only when the companion is thin; when the companion takes little food, the amount people eat is not influenced by the companions body type”

Question 24

how do you predict a main effect is present or not?

Answer 24

add an additional row mean and column mean to the table (also are called marginal means)

Question 25

before you interpret any main effect for certain, what must you look at?

Answer 25

simple main effects

Question 26

what is a moderator variable?

Answer 26

a variable that influences the relationship between two other variables
ex. body type in the food indulging example

Question 27

what are the three possibilities when analyzing 2x2 factorial design results?

Answer 27

there may or may not be a main effect for independent variable A
there may or may not be a main effect for independent variable B
there may or may not be an interaction between the independent variables

Question 28

what is a mixed factorial design?

Answer 28

combination of within subjects and between subjects designs

Question 29

when are line graphs used?

Answer 29

when the levels of the independent variable on the horizontal axis are quantitative and continuous with low and high amounts

Question 30

when are bar graphs used?

Answer 30

when the levels of the independent variable are nominal, representing different categories (i.e. one type of therapy compared to another type)

Question 31

what are the independent and dependent variables in this scenario: Effect of age of defendant, and type of substance use during a crime, on sentencing. Participants read a scenario of a male, age 20 or 50, who was found guilty of causing a traffic accident while under the influence of either alcohol or marijuana, and then assigned him a jail sentence.

Answer 31

Independent variable A: Type of offence (alcohol versus marijuana) Independent variable B: Age of defendant (20 versus 50 years of age) Dependent variable: Months of sentence (range from 0 to 10 months)

Question 32

what are the independent and dependent variables in this scenario: Effect of previous mood on the recall of humorous advertisements. Participants viewed a video that was either happy or sad, intended to induce a positive or negative mood. Next, they read print ads for eight different products over the next three minutes. These ads were either humorous or totally serious. The dependent variable was the number of ads correctly recalled.

Answer 32

Independent variable A: Mood induction (happy versus sad video)
Independent variable B: Ad content (humorous versus serious)
Dependent variable: Number of ads recalled (range from 0 to 8)

Question 33

what is an independent variable by participant variable design/ IV x PV design?

Answer 33

a type of factorial design that includes both experimental (manipulated) and non experimental (measured or non manipulated) variables

Question 34

why might researchers use an independent variable by participant variable design?

Answer 34

because it allows researchers to investigate how different types of people (different ages, ethnic groups, personality characteristics…) respond to the same manipulated variable

Question 35

what does the simplest independent variable by participant variable design contain?

Answer 35

one manipulated independent variable that has two levels and one participant variable with two levels (different age groups that are low or high on a personality trait for ex)

Question 36

why are factorial designs that combine manipulated independent variables and participant variables useful?

Answer 36

for investigating many interesting research questions

Question 37

why can we never make causal claims when interpreting the results associated with participant variables?

Answer 37

because participant variables can never be manipulated and randomly assigned