correlations

Question 1

define correlations (1)

Answer 1

a mathematical technique in which a researcher investigates an association between 2 variables (covariables)

Question 2

define covariables (2)

Answer 2

the two variables in a correlational study that are measured to see if there is a relationship between them.
they are not manipulated, just observed as they naturally occur.

Question 3

define positive correlation

Answer 3

as one co-variable increases so does the other

Question 4

give an example of positive correlation

Answer 4

the number of people in a room and noise are positively correlated

Question 5

define negative correlation

Answer 5

as one co-variable increases the other decreases

Question 6

give an example of negative correlation

Answer 6

number of people in a room and the amount of personal space is negatively correlated

Question 7

define zero correlation

Answer 7

when there is no relationship between co-variables

Question 8

give an example of zero correlation

Answer 8

the association between the number of people in a room in Manchester and the total daily rainfall in Peru

Question 9

what does correlation illustrate ?

Answer 9

the strength and direction of an association between 2 or more co-variables

Question 10

where are correlations plotted on ?

Answer 10

scattergram

Question 11

what does one co-variable and the other form ?

Answer 11

the x-axis + the other the y-axis

Question 12

how would an individual work out to see if the use of caffeine is correlated with high anxiety ? (3)

Answer 12

• may get people to work out how many caffeine drinks they consume over a weekly period
• then use the same people to self-report their level of anxiety (using a 20-point scale) at the end of the week

Question 13

what may one expect to see between caffeine and high levels of anxiety ? (2)

Answer 13

• might expect to see a positive correlation
  –> means more caffeine people drink the higher the level of anxiety

Question 14

how would an individual work out to see if the use of caffeine is correlated with amount of sleep one has ?

Answer 14

• could use the same people to record how many hours of sleep they have over a week
• may get people to work out how many caffeine drinks they consume over a weekly period

Question 15

what may one expect to see between caffeine and amount of sleep one has ?

Answer 15

• drinking a lot of caffeine disrupts sleep patterns
  –> so perhaps more caffeine someone drinks the less sleep they have hence negative correlated

Question 16

how could we find a result of no correlations with the variables above ? (3)

Answer 16

• the number of dogs one sees in the street within the same week
• there is no relationship between the number of dogs one sees in the street and the number of caffeine drinks one drinks
• expect to find something close to 0 correlation or exactly 0 correlation

Question 17

what does the researcher do in experiments with the IV and why ?

Answer 17

controls and manipulates it –> in order to measure the effect on the DV

Question 18

why is it possible to infer that the IV caused any observed changes in the DV ?

Answer 18

as a result of this deliberate change in one variable

Question 19

if there is no manipulation of one variable in correlation it means … ?

Answer 19

it is not possible to establish cause and effect between one co-variable and another

Question 20

give an example of the fact there is no manipulation in variable: (CAFFEINE) (3)

Answer 20

if one found a strong positive correlation between caffeine and anxiety level we cannot assume that caffeine was the cause of anxiety
–> people may be anxious for all sorts of reasons (stressful job , personality type)

Question 21

define intervening variables (3)

Answer 21

factors that come between the independent variable (IV) and the dependent variable (DV) in an experiment and explain how or why the IV affects the DV. They are not directly measured but influence the outcome

Question 22

give an example of intervening variables

Answer 22

if higher income (IV) leads to better health (DV), an intervening variable could be access to healthier food

Question 23

draw a positive correlation labelled correctly and without the coefficient

Answer 23

+ 1 and look in textbook :)

Question 24

draw a negative correlation labelled correctly and without the coefficient

Answer 24

-1 and look in textbook :)

Question 25

draw a zero correlation labelled correctly and without the coefficient

Answer 25

0 and look in textbook :)

Question 26

give a strength of correlations - (PT)

Answer 26

- a useful preliminary tool for research --> assessing the strength and direction of a relationship could suggest possible ideas for future research if the variables are strongly related or indicate some kind of interesting pattern --> often used as a starting point to assess possible patterns between variables before researchers commit to an experimental study

Question 27

give a strength of correlations (EF) (3)

Answer 27

- quick and easy (economical) to carry out - no need for a controlled environment and no manipulation of variables is required - secondary data can be used which means that correlations in less time-consuming than experiments

Question 28

give a limitation of correlations (W) (3)

Answer 28

can only tell us how variables are related but not why - due to lack of experimental manipulation and control within a correlational study - cannot demonstrate cause and effect and therefore we can't be sure which variable is causing the other to change

Question 29

give a limitation of correlations

Answer 29

- could be another untested variable causing the relationship between the 2-co-variables we are interested in ( an intervening variable)

Question 30

an example of the 3rd variable problem

Answer 30

- people who have high pressured jobs --> may spend a lot of their time feeling anxious --> drink a lot of caffeine because they work for long hours and need to remain alert --> unaccounted variable is job type

Question 31

give a limitation of correlations (4)

Answer 31

misuse of results - relationships are often quoted as facts when they aren't -single parent households and crime -->being raised in S-P-H increased the likelihood of being involved in crime --> doesn't mean that S-P-H cause crime or children from the families will go on and commit crime --> so may 3rd variables and S-P-H tend to be less well off which may explain the link between one-parent families and crime - hence results are being misused and misinterpreted