Experiments

Question 1

Strengths and weaknesses of field experiments

Answer 1

A: true to everyday life and high in ecological validity - more likely to act normal.
Less effort.
D: not controlled and lots of extraneous variables.
Reducing reliability because it’s not standardised and replicable.

Question 2

Strengths and weaknesses of lab experiments

Answer 2

A: controlled environment minimises extraneous variables.
Reliable
D: Low ecological validity because may not reflect how people behave in everyday life so can’t be generalised to everyday scenario.
Participants might change the way they behave. (Demand characteristics).
More effort.

Question 3

Strengths and weaknesses of Quasi experiments

Answer 3

A: high in ecological validity because they’re not manipulating the IV.
Helps us study variables we cannot manipulate.
D: difficult to conduct.
Can’t control some participant variables that may influence the results.

Question 4

Strengths and weaknesses of repeated measures design

Answer 4

Same people in each condition

A: no participant variables (personality and persons life won’t effect results).
Only need to get half the people so it’s easier to collect sample.
D: the participants could change their behaviour if they work out what the study is about (demand characteristics).
Order effects- may get better or worse next time they do it as they’ve had practice.

Question 5

Strengths and weaknesses of independent measures design.

Answer 5

Different people in each condition

A: no demand characteristics (because the participant won’t know what the opposite participant is doing so won’t be able to work out the aim of the procedure and change their behaviour.)
No order effect- no practice.
D: Extraneous variables - participant variables.
Double people needed- effort.

Question 6

Strengths and weaknesses of matched participant design.

Answer 6

Using different people in each condition but making them as similar as possible on key characteristics. Done by testing individual on characterises, pairing them based on similar scores then placing one member of each pair into each group.

A: reducing participant variables.
No order effects or demand characteristics.
D: Can’t get rid of participant variables completely.
More effort.

Question 7

How can participant variables be controlled?

Answer 7

Have same people in each condition - repeated measures design or extremely similar groups of people- matched participants design.
Use random sampling so participant variables are more likely to be evenly distributed.

Question 8

How can order effects (situational variables) be controlled?

Answer 8

Having different people in each condition - independent measure design or matched participants design.
If repeated measures design used, this should be counter-balanced (participants split into 2 groups; group 1 doing condition A and group 2 doing condition B.)

Question 9

How can environmental factors (situational variables) be controlled?

Answer 9

Impose controls on the experiment to ensure there are as few differences as possible between the two conditions e.g. same room, same temperature levels, same colour walls, same lighting.

Question 10

How can demand characteristics (situational variables) be more controlled?

Answer 10

Don’t tell participant the aim of the experiment (single blind procedure).

Question 11

Null hypothesis

Answer 11

The IV will have no significant effect on the DV. Any difference will be due to chance factors.
‘There will be no significant difference between… any difference will be due to chance factors’

Question 12

Alternative hypothesis

Answer 12

The IV will significantly affect the DV

‘There will be a significant difference between…’

Question 13

Two tailed hypothesis

Answer 13

The IV will affect the DV but no direction is given.

Question 14

One tailed hypothesis

Answer 14

The IV will affect the DV in a certain direction.

Question 15

Operationalisation

Answer 15

The process of making variables physically measurable or testable. This is done by recording some aspect of observable behaviour that is assumed to be indicative of the variable under consideration.

Question 16

Strengths and weaknesses of a self selecting sample.

Answer 16

A: participants will be cooperative because they want to do it + more likely to continue for the entire study.
Easy to obtain.
D: Demand characteristics.
Unrepresentative sample- all part of one group e.g. unemployed or keen on psychology.
Expensive if given money incentive.
Could mean a small sample size.

Question 17

Strengths and weaknesses of opportunity sampling.

Answer 17

A: easy to obtain at the time of study.
Act naturally - no demand characteristics.
D: unrepresentative sample.
Researcher bias.

Question 18

Strengths and weaknesses of random sampling.

Answer 18

Each member of target population has equal chance of being selected (names in a hat).

A: everyone has equal chance of being selected.
Representative of target population.
D: Everyone has equal chance of being selected -outliers.
Sometimes hard to ensure all have equal chance.
Selected people may not be willing to take part.

Question 19

Strengths and weaknesses of snowball sampling.

Answer 19

When participants are asked to contact their friends and family to ask them to also take part in the research.

A: Easy to obtain (especially if difficult target population).
D: participant variables.
Not able to generalise sample- family and friends often have similar characteristics.

Question 20

4 key principles to make sure participants are treated with appropriate respect.

Answer 20

Respect:
Consent
Right to withdraw
Confidentiality

Competence:
Not giving advice to participants if not qualified + check research with peers.

Responsibility:
Protection from harm
Debrief

Integrity:
Deception.

Question 21

Primary data

Answer 21

Collecting data directly

Question 22

Secondary data

Answer 22

Analyse information that already exists (crime statistics).

Question 23

Quantitative results

Strengths and weaknesses

Answer 23

Numerical data

Easy comparison to be made between participants.
No researcher bias.
Easy to summarise.
Easier to establish reliability of results.

May not be representative of a participants everyday behaviour- low ecological validity.
Don’t tell us why.

Question 24

Qualitative data

Strengths and weaknesses

Answer 24

Written data

More detailed about participants experience.
Richer data to improve validity of results.

Harder to compare participants.
Cannot present in a graph.
Harder to analyse.
Researcher bias.

Question 25

Mean
How is it calculated?
Advantages and disadvantages.

Answer 25

Total / (divided by) how many figures.

Involves all the data.

Includes outliers which may skew the results.
Can give us decimal figures.

Question 26

Median
How is it calculated?
Advantages and disadvantages.

Answer 26

Arrange numbers in numerical order. Crops off numbers at each end until you get to the middle.

Discounts outliers so not skewed.

Doesn’t include all the data.
May be a decimal figure.

Question 27

Mode
How is it calculated?
Advantages and disadvantages.

Answer 27

The number which appears most.

Easy to calculate.
Always a whole value.
Can be done with qualitative data.

May be none or more than one mode.
Doesn’t include all data points.

Question 28

How is the range calculated

Advantages and disadvantages.

Answer 28

Subtracting the highest number from the lowest number.

Gives a sense of how dispersed the results are.
Vulnerable to being skewed.

A
Easy to calculate.
Shows the spread between the min and max values.

D
Does not show if the spread is even.
Can be skewed by outliers.

Question 29

Variance
What is it?
How to calculate?
Advantages and disadvantages.

Answer 29

Indicates how spread apart the data is within each condition from the mean score. The smaller the variance, the less spread out the participants are in their scores in each condition of the experiment from the average score.

Calculate the mean score per condition in the experiment.
For each participant, subtract the mean score from their score. This is the ‘d’ (difference).
Square each ‘d’ score (d^2).
Add all of the d^2 scores together to get the sum of the difference squared.
Divide the sum of the difference squared by N-1.
N= number of participants in the sample for that condition.

A
Takes into account all values in the data set.
Less likely to be affected by outliers.

D
More time consuming to calculate.
Not in the same units as the original measure.

Question 30

Standard deviation?
What is it?
How is it calculated?
Advantages and disadvantages.

Answer 30

Solves the problem of variance being in a different unit as the original data.

The square root of the variance.

A
Same unit as original measure.
Easy to calculate if variance is already done.

D
Time consuming and more difficult to calculate than the range score.
Takes into account extreme outliers.