Task 7 Cause and effect

Question 1

Effect

Answer 1

is the outcome e.g. learning together increases productivity so increased productivity is the effect

Question 2

Cause

Answer 2

is the reason of the effect e.g. learning together increases productivity e.g. learning together is the cause

Question 3

Covariation

Answer 3

not sure about a link between the two variables. They must occur together but you don’t know the relationship

Question 4

Third variable problem

Answer 4

The possibility that correlational relationships may result from the action of an unobserved third variable
→may influence both of them, causing them to vary together even there is no direct relationship between them

Question 5

Directionality Problem

Answer 5

direction of causality is sometimes difficult to determine (causal arrows, what is predictor and what is criterion value)

Question 6

independent variable

Answer 6

Whos values and are chosen and set by the experimenter

Question 7

dependent variable

Answer 7

the variable you want to meassure

Question 8

Extraneous variables

Answer 8

are those that may affect the behaviour but are not of interest for the present experiment, so you can’t investigate them

Question 9

Precedence

Answer 9

the hypothesized causal variable must reliably precede the effect variable.

Question 10

Exclusion of alternative explanations

Answer 10

other explanations for the observed covariation must be reasonably excluded.

Question 11

Logical mechanism

Answer 11

there must be a plausible account for the hypothesized causal relation.

Question 12

Causal relationship

Answer 12

one variable directly or indirectly influences another (changes in the value of one variable directly or indirectly cause changes in the value of a second)
→can be unidirectional A influences B but not other way around (e.g. brick on your toe leads to screaming)
→can also be bidirectional, each variable influences another

Question 13

Correlational relationship

Answer 13

changes in one variable accompany in another, but the proper tests have not been conducted to show that either variable causes changes in the other
→when changes in one variable are accompanied by specific changes in another, the two variables are said to covary

Question 14

Demonstrating

Answer 14

exposes the group to only one treatment condition

Question 15

Confounding variable

Answer 15

Two variables are confounded when their effects on a response variable cannot be distinguished from each other. The confounded variables may be either explanatory variables or lurking variables or both
→damages internal validity, you may not be able to establish a casual relationship between your independent variables and your dependent

Question 16

conceptual confound

Answer 16

It may due to overlapping meaning between to variables (correlation between outcome and another outcome→ makes no sense) e.g. being sad leads to depression is wrong because the one is actual part of depression

Question 17

Quasi-Independent variable

Answer 17

in an experimental design, any of the personal attributes, traits, or behaviours that are inseparable from an individual and cannot reasonably be manipulated (e.g. gender age and ethnicity)

Question 18

Quasi-experiment

Answer 18

Tries to isolate a causal influence by selection rather than manipulation. Rather than causing X to vary, we select cases in which X does vary

Question 19

between subject design

Answer 19

divide participants in two or more groups, and these groups receive different values of the variable that is of interest

Question 20

Simpsons paradox

Answer 20

As is the case with quantitative variables, the effects of lurking variables can strongly influence relationships between two categorical variables
→An association or comparison that holds for all of several groups can reverse direction when the data are combined to form a single group. This reversal is called Simpson’s paradox

Question 21

common response

Answer 21

When the observed association between the variables x and y is explained by a lurking variable z

Question 22

correlational design

Answer 22

examine the relationship between two or more variables
→cross-sectional in which all observations are made at one time
→longitudinal: measurements are made at to or more time points

Question 23

Mediator variable

Answer 23

are variables that are between cause and effect so A leads to D (mediator variable) which leads to B

Question 24

conceptual confound

Answer 24

It may due to overlapping meaning between to variables

Question 25

Moderator variable

Answer 25

there is only a association between your variables under specific circumstances these are the moderators (e.g. people buy more when they are hungry this is only right for impulsive people, impulsiveness is the moderator)

Question 26

No treatment group (control group)

Answer 26

receives no treatment is used as base/control group

Question 27

Placebo control groups

Answer 27

1. Outcome research: simply investigates the effectiveness of a treatment
2. Process research: attempts to identify the active component of a treatment. In process research, it is essential that the placebo effect be separated from other, active components of the treatment

Question 28

Placebo

Answer 28

psychosomatic) The mind (psyche), rather than the placebo itself, has an effect on the body (somatic). It occurs simply because the participants think the medication is effective

Question 29

Development design

Answer 29

o Cross generational: Take different age groups

o Longitudinal: Take one group and observe them over a long time

Question 30

Sources of Confounding

Answer 30

History: specific events other than treatment occur between observations
• Maturation: fatigue or aging change performance over time
• Instrumentation: instrument calibration changes and confounds the effect
• Statistical regression: subjects selected for treatment on the basis of their extreme scores tend to move closer to the mean when retesting
• Biased subject selection: nonrandom • Experimental mortality: dropouts • Demand characteristics: participants know the purpose of the study and behave differently