Research Methods ALL

Question 1

Aim

Answer 1

An intention of an investigation to see if or to investigate whether

Question 2

Hypothesis

Answer 2

Statement of expected outcome. A prediction and what you find. Null and alternative hypothesis and operationalised

Question 3

Null

Answer 3

IV does not effect DV

Question 4

Alternative

Answer 4

IV effects DV

Question 5

Directional

Answer 5

Specific about what the effect will be (sufficient background evidence)

Question 6

Non directional

Answer 6

IV will affect DV but not specifically (when no previous research or to avoid bias)

Question 7

Extraneous variables

Answer 7

Could effect DV but should be controlled

Question 8

Confounding variables

Answer 8

Already have affected the DV

Question 9

Operationalised

Answer 9

Telling how you will conduct and measure to make hypothesis clear and testable

Question 10

What is the point of an experiment

Answer 10

Keep variables constant and manipulate one variable to se effect on DV, establishing a causal relationship

Question 11

Summarise lab experiments

Answer 11

• High control of extraneous variables
• Controls IV and measures DV
• Good as increase confidence that IV affects DV and more reliability due to high control
• Bad because artificial situation so lacks ecological validity and lacks mundane realism

Question 12

Summarise field experiments

Answer 12

• Real world, so little control over extraneous variables
• P’s do not know
• Good as no demand characteristics and high validity as P’s act naturally
• Bad as loses control of extraneous variables so less causal
• Harder to replicate

Question 13

Natural

Answer 13

IV is a situation or environmental factor

Question 14

Quasi

Answer 14

IV is an individual difference

Question 15

What is good and bad about Natural and Quasi

Answer 15

• Study variables that we cannot in other ways due to ethics

- Cannot manipulate the IV so may not be causal as no control

Question 16

Summarise repeated measures

Answer 16

• Ps take part in both so effect in DV due to IV and not pts variables
• Controls individual differences as score 1 and 2 compared so higher internal validity
• Less pts
• Demand characteristics
• Practice and order effects

Question 17

How can we deal with p and e effects

Answer 17

• Counterbalancing ABBA
• Assign randomly
• Randomisation

Question 18

Summarise matched pairs

Answer 18

• Each person in one condition matched with someone in the other on a factor such as age
• controls panda effects and individual differences
• practically difficult
• hard to decide which factors are more important
• how to measure the variable we are matching
• Hard to find a match in large sample sizes

Question 19

Summarise independent measures

Answer 19

• Divides randomly into 2 groups, P only completes once
• Reduces demand characteristics
• Avoids panda effects
• More ps needed
• Individual differences

Question 20

Randomisation

Answer 20

Use of chance to control for effect of bias when designing materials and order of conditions

Question 21

Standardisation

Answer 21

All procedures standardised so all ps subject to same environment

Question 22

Demand characteristics

Answer 22

• Features or cues which help ps work out what is expected

- May respond according to what they think is being investigated so invalid results

Question 23

Social desirability bias

Answer 23

• ps behave in way to present the best behaviour

- researcher should focus on experimental realism, so task is engaging and ps forget they are being observed

Question 24

Investigator effects

Answer 24

• Any effect of investigators behaviour on the research outcome

Question 25

Pilot study

Answer 25

• Small scale trial to identify potential issues and modify design and save time and money

Question 26

What must a sample be

Answer 26

Representative to generalise

Question 27

Random sample

Answer 27

• Each person has same chance of being picked
• Unbias selection and probability means it will usually be representative
• Chance of being unrepresentative so cannot generalise

Question 28

Systematic sample

Answer 28

• Taking every nth person so avoids bias as no control
• probability means it will usually be representative
• Chance of being unrepresentative so cannot generalise
• Not as objective as random as researcher may decide on who is listed before selection and the nth number

Question 29

Stratified sample

Answer 29

• Sampling frame divided into groups
• Number from each group taken that is representative
• Ensures sample representative and objective as after stratas, left to chance
• Time consuming
• Researcher may not identify all key characteristics

Question 30

Opportunity sample

Answer 30

• Made up of ps available at the time
• Easy and convenient and less time
• Biased as small, and only certain people say yes
• Researcher may show bias when selecting ps

Question 31

Volunteer sample

Answer 31

• Ps volunteer to take part
• Access tow idea population
• Only a certain type of person

Question 32

Questionnaires

Answer 32

• Self report
• Open and closed questions
• Collect large data quickly, see what people are thinking and good reliability
• Influenced by motivation, social bias and does not reflect thinking

Question 33

What makes a good questionnaire?

Answer 33

• Clarity so understand Q
• Unbiased
• Quant for closed and vice versa
• Enough responses for useful data, too many = boredom
• May need filler question s to avoid demand characteristics
• More challenging ones at the end to build trust
• Pilot study

Question 34

Structured Interview

Answer 34

Face to face with Qs

• Pre determined questions asked in fixed order
• Easy to replicate
• Interviewee cannot elaborate and so may miss useful information

Question 35

Unstructured interview

Answer 35

Convo

• Topic discussed and interaction free flowing
• Interviewee expands
• More flexibility but risk of social bias

Question 36

Natural observation

Answer 36

Observed in natural setting

- Investigator does not interfere