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P PERSONAL > RESEARCH METHODS AS COMPLETE STACK > Flashcards

RESEARCH METHODS AS COMPLETE STACK Flashcards

1
Q

What are the 4 primary codes of the BPS?

A

Respect
Competence
Responsibility
Integrity

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2
Q

How do ethics community decide whether a research project should happen?

A

Ethics communities weigh up cost-benefit analysis and take into account the reputation of psychology.

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3
Q

What are Ethical Issues?

A

Ethical Issues arise when there is a conflict between the rights of the participant and the steps taken to reach the goals of the research.

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4
Q

What are Ethical Considerations to take into account?

A
  1. Consent
  2. Deception
  3. Confidentiality
  4. Debriefing
  5. Right to withdraw
  6. Protection from all harm
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5
Q

What is the general formula for a consent form?

A

-Purpose of study
-What happens
-Time needed
-Right to withdraw
-Any harm or help given
TICK BOXES
-Have read and asked any questions and understand rights to withdraw.
-Consent

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6
Q

What is debriefing?

A

Debriefing = AFTER the experiment, participants are informed of:
-Their data and rights around it
-If any deception occurred
-The results collected

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7
Q

What is the difference between a general population, target population and sample?

A

General Population
= Big, generalised group of people within an area.
Target Population
=Group of people who are the focus of the research project.
Sample
= Small group of people from the target population that are chosen to take part in the project.

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8
Q

What is the difference between bias and generalisation?

A

Bias is when certain groups are over or under represented, whereas generalisation is when findings from a study can be applied to a larger population.

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9
Q

What is Random Sampling?

A

Random Sampling is randomly selecting participants.

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10
Q

What are the advantages of Random Sampling?

A

ADV - free from researcher bias, all participants have equal chance of being chosen and should be fairly representative.

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11
Q

What are the disadvantages of Random Sampling?

A

DISADV - difficult and time consuming as participants might refuse to take part. May still be unrepresentative.

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12
Q

What is Systematic Sampling?

A

Selecting every nth member of the target population to take part

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13
Q

What are the advantages of Systematic Sampling?

A

ADV - Free from researcher bias and fairly representative

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14
Q

What are the disadvantages of Systematic Sampling?

A

DISADV - Every person doesn’t have an equal chance at being selected, time consuming and participants might refuse to take part.

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15
Q

What are the advantages of Opportunity Sampling?

A

ADV - Cost efficient and easy to conduct.

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16
Q

What is Opportunity Sampling?

A

Selecting anyone who is willing or available at the time.

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17
Q

What are the disadvantages of Opportunity Sampling?

A

DISADV - Open to researcher bias and fairly unrepresentative.

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18
Q

What is Volunteer Sampling?

A

Participants self selecting (volunteering) to take part.

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19
Q

What are the advantages of Volunteer Sampling?

A

ADV - Easy and minimal input from the researcher. Participants more engaged as they chose to take part.

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20
Q

What are the disadvantages of Volunteer Sampling?

A

DISADV - Open to volunteer bias and demand characteristics. Volunteers tend to be helpful, outgoing people so will be fairly unrepresentative.

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21
Q

What is stratified sampling?

A

Definition: Where the composition of the sample reflects the population of people in in certain subgroups - this represents the wider population.

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22
Q

What are the advantages of Stratified Sampling?

A

ADV - Avoids researcher bias and produces fairly representative sample.

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23
Q

What are the disadvantages of Stratified Sampling?

A

DISADV - Not a perfect sample and cannot reflect the way in which all groups are different. Time consuming.

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24
Q

What is the formula for stratified sampling?

A

(Sample size ÷ Population size) x Number of participants in sub group.

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25
Q

EXAM QUES
A researcher wants to study a sample size of 70 students from different subjects in college:
Latin - 145 total students
Spanish - 121 total students
German - 198 total students
French - 186 total students
Using stratified sampling, decide how many students should be used from each subject for a fair representation.

A

FORMULA
(Sample size ÷ Population size) x Number of participants in sub group.
Population size = 145 + 121 + 198 + 186 = 650
Sample size = 70 (states it in question)
(70/650) x 145 = 16 Latin students
(70/650) x 121 = 14 Spanish students
(70/650) x 198 = 21 German students
(70/650) x 186 = 21 French students

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26
Q

What are variable and what are the two main types of variables?

A

Variables = The things that you are investigating that changes
TYPES:
-Independant Variable = Variable that is manipulated by researcher or changes ‘cause’
-Dependant Variable = Variable that experimenter measures ‘effect.’

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27
Q

What does it mean when there are levels to the Independant Variable?

A

When the Independant Variable has different levels, this means there are different experimental conditions - a hypothesis will be written about these IVs.
For example - Group 1 drinks water whilst Group 2 drinks coffee - the ‘levels’ to the IV are the drinks.

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28
Q

What are extraneous variables?

A

‘Nuisance variables.’ These cause an effect on the DV which means the results are not accurate. These need to be controlled.

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29
Q

What are confounding variables?

A

These are a type of Extraneous Variable. They are found AFTER the data has been collected and HAVE had an EFFECT on the results.

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30
Q

What are participant variables?

A

Independant Variables related to participants that can effect results - such as eye colour, personality, etc (things in the participants that are DIFFERENT.)

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31
Q

What are situational variables?

A

Independant Variables related to participants that can have an effect on results - such as the environment, temperature, day, time of day, etc.

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32
Q

What are researcher variables?

A

Independant Variables related to the reseatcher that can affect resulst - such as body language, tone of voice, type of questions, etc.

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33
Q

What are controls?

A

Things you do to stop extraneous variables from affecting the overall results of the study.

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34
Q

What is operationalisation?

A

Taking something that is qualitative (not measureable) and making it clearly defined and measureable.

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35
Q

What are Demand Characteristics?

A

Demand Characteristics = Cues from the researcher which may lead to changed behaviours from the participants - angel / devil. Leads to inaccurate results.

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36
Q

What is the Social Desirability Bias?

A

Participants changing behaviours to be seen as more normal and socially desirable.

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37
Q

What are Investigator Effects?

A

Things that affect the study due to researcher behaviours - e.g. body language. This might be because they want to prove the hypothesis right.

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38
Q

How can you overcome Investigator Effects (EXPLAIN.)

A

Overcome by RANDOMISATION - this is use of chance methods during the processes of the experiment to reduce any biases. For example, using random sampling to select participants.

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39
Q

One example of randomisation is random allocation - what is random allocation?

A

Randomly allocating participants to the groups / conditions. This prevents bias and all participants have equal chance to be in all groups.

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40
Q

What are order effects?

A

Order effects are when the order of tasks participants take part in affects the study results. For example, taking part in a physical task first would mean participants might be too tired to concentrate on the next task and this effects results,

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41
Q

How can you overcome Order Effects? (EXPLAIN)

A

Overcome with COUNTER- BALANCING. This would mean that different groups take part in each conditions at different times. (REMEMBER ‘ABBA’ Group 1 A then B and Group 2 B then A)

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42
Q

What is standardisation?

A

Standardisation is the process by which all procedures and actions in an experiment is kept the SAME.

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43
Q

Give 5 examples of how you could standardise an experiment?

A
  1. Same time of day
  2. Same room / place of experiment.
  3. Same questions being asked
  4. Same temperature of surroundings
  5. Given identical standardised instructions.
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44
Q

What are researcher aims?

A

General statement of what the researcher intends to investigate.

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45
Q

What are researcher hypotheses?

A

Clear, precise, testable statements which state the relationship between variables to be investigated.

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46
Q

What is the difference between alternate and null hypotheses?

A

BOTH are a statement of prediction about your research, however alternate hypotheses say the research WILL yield significant results whilst null hypotheses say your research WILL NOT yield significant results.

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47
Q

Before you start a research, which types of hypotheses will you write?

A

BOTH alternate and null hypotheses are written, however at the end, only ONE is accepted.

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48
Q

What are Experimental Hypotheses?

A

A type of alternate hypothesis. Used for causal relationships. Predicts a significant difference or effect.

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49
Q

What are Correlational Hypotheses?

A

A type of alternate hypothesis. Used for non-causal relationships. Predicts a significant relationship or correlation.

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50
Q

What is the difference between Experimental and Correlation Hypotheses?

A

Experimental = causal, Correlational = non causal. In the question words such as ‘difference’ and ‘effect’ means Experimental Hypothesis whilst words like ‘link’ ‘correlation’ ‘relationships’ is correlational.

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51
Q

What is a Directional Hypothesis?

A

‘One tailed’ States the direction of the difference, relationship, etc.

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52
Q

Give an example of a Directional Hypotheses?

A

Women will score higher than men on a memory test.

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53
Q

What is a Non-Directional Hypothesis?

A

‘Two tailed’ Does not state the direction of the difference, relationship, etc.

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54
Q

Give an example of a Non-Directional Hypotheses?

A

There will be a significant difference in memory scores between women and men.

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55
Q

What is the difference between experimental method and design?

A

METHOD = Type of experiment being used e.g. Lab, field, quasi.
DESIGN = How the participants are used by researchers.

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56
Q

What is a Laboratory Experimental design?

A

A strictly controlled experimental method in which the IV is manipulated by researcher and DV is measured strictly.

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57
Q

What are the advantages of Lab experiments?

A

ADVANTAGES - High control over extraneous variables, replicable and standardised. Clear effect of IV on DV.

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58
Q

What are the disadvantages of Lab experiments?

A

DISADV - Lacks ecological validity and might lead to demand characteristics which means its less accurate.

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59
Q

What is a Field Experimental design?

A

Mimicks natural experimental design but isn’t fully natural as IV is still manipulated by researcher and DV is measured.

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60
Q

What are the advantages of Field experiments?

A

ADV - Higher ecological validity due to natural setting. Less demand characteristics.

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61
Q

What are the disadvantages of Field experiments?

A

DISADV - Difficult to control extraneous variables and more ethical issues are present.

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62
Q

What is a Natural Experimental design?

A

Full natural setting in which IV naturally happens and would have always happened (no manipulation from researcher.) DV measured by researcher.

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63
Q

What are the advantages of Natural experiments?

A

High external validity means more accurate results. Can research rare opportunities / IVs we don’t manipulate.

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64
Q

What are the disadvantages of Natural experiments?

A

DISADV - Needs a naturally occurring IV that are rare and hard to replicate. Lacks control over other variables.

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65
Q

What is a Quasi Experimental design?

A

Almost an experiment. IV is naturally occurring and recorded by researcher. Groups are decided in a non random manner.

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66
Q

What are the advantages of Quasi experiments?

A

Quite controlled which means more accurate. Any changes to DV is due to IV. Useful when ethics get in the way of true experiments.

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67
Q

What are the disadvantages of Natural experiments?

A

May have confounding variables which will affect the results.

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68
Q

What is an Independant Groups experimental design?

A
  • Each participant only takes part in one condition and these results are compared with other participants.
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69
Q

What are advantages of Independant Groups experimental design?

A

ADV - Order effects less likely, less likely to guess aims so less demand characteristics.

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70
Q

What are disadvantages of Independant Groups experimental design?

A

DISADV - Needs more participants which means more costly / time consuming. Participant variables likely.

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71
Q

What is a Repeated Measures experimental design?

A

All participants take part in all conditions and their own personal scores are compared

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72
Q

What are advantages of Repeated Measures experimental design?

A

ADV - Participant variables are controlled - increases validity. Fewer participants so more cost efficient and cheaper.

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73
Q

What are disadvantages of Repeated Measures experimental design?

A

DISADV - Repetition and lots of tasks might lead to order effects / Demand Characteristics.

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74
Q

What is an Matched Pairs experimental design?

A

Each participant is matched with another participant, who shares relevant variables e.g age.

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75
Q

What are advantages of Matched Pairs experimental design?

A

ADV - No order effects, participant variables controlled, less likely to guess aims and so less demand characteristics.

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76
Q

What are disadvantages of Repeated Measures experimental design?

A

DISADV - Time consuming and much less efficient. Can’t fully contol participant variables.

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77
Q

What are the problems of Independant Groups Design and Repeated Measures Designs and how can you overcome these?

A

Independant Groups Designs have participant variables - overcome by random allocation Repeated Measures Designs have order effects - overcome by counterbalancing.

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78
Q

Give two examples of a self-report techniques?

A

Questionnaires.
Interviews.

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79
Q

EVALUATE Self-Report Methods.

A

+Detailed, free to express
-Subject to social desirability bias and lacks validity.

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80
Q

What type of questions make up questionnaires? (2)

A

Open and closed questions.
OPEN - allow as much detail as needed.
CLOSED - pick from pre-determined options.

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81
Q

EVALUATE open and closed questions.

A

OPEN
+Qualitative and rich in detail
+Participants feel less restricted
-Difficult to analyse and compare; often misinterpreted
CLOSED
+Easier to analyse and compare
- Limits details and participants feel frustrated.

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82
Q

What are the 6 types of closed questions?

A
  1. Forced / Fixed choice
  2. Likert Scale
  3. Rating Scale
  4. Ranking Scale
  5. Checklists
  6. Semantic differential rating scale.
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83
Q

What are forced or fixed questions?

A

A type of closed question.
Have to choose from a list of options.

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84
Q

Give strengths of forced or fixed questions.

A

+Easier to analyse and compare
and this is time efficient.

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85
Q

Give weaknesses of forced or fixed scale questions.

A

-Data lacks detail
-Participants feel forced to pick options.

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86
Q

What are likert scale questions?

A

A type of closed question.
Participants indicate how far they agree or disagree with something.

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87
Q

Give strengths of Likert scale questions.

A

+Allows for slight more detail whilst data remains easy to analyse and compare

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88
Q

Give weaknesses of Likert scale questions.

A

-Still lacks detail
-Participants might not agree too much to seem less extreme (central tendency.)

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89
Q

What are rating scale questions?

A

A type of closed question.
Participants give ratings on their own personal opinions.

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90
Q

Give strengths of rating scale questions.

A

+More insight / detail
+Still quite comparable

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91
Q

Give weaknesses of rating scale questions.

A

-Participants might interpret the ranks differently
-Might stick to middle to avoid looking extreme (central tendancy)

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92
Q

What are ranking scale questions?

A

A type of closed question.
Participants rank options.

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93
Q

Give strengths of ranking scale questions.

A

+Provides much more detail
+Comparisons can still be made

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94
Q

Give weaknesses of ranking scale questions.

A

-No options to rank 2 as equal, lacks validity
-Responses might be biased towards the values they see first -Lacks detail

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95
Q

What are checklist questions?

A

A type of closed question.
Allow participants to answer by choosing multiple options from the pre-determined choices.

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96
Q

Give strengths of checklist questions.

A

+Easy to analyse and compare
+Can select multiple options so more valid.

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97
Q

Give weaknesses of checklist questions.

A

-Data has a narrow range and lacks detail
-Difficult to interpret
-Participants might feel forced to select an answer.

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98
Q

What are semantic differential rating scale questions?

A

A type of closed question.
Questions which allow participants to indicate attitudes towards something on a scale between opposite words.

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99
Q

Give strengths of semantic differential rating scale questions?

A

+Easy to analyse and compare
+Allows for much more detail

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100
Q

Give weaknesses of semantic differential rating scale questions?

A

-Participants might interpret scales differently
-They may stick to middle to prevent seeming extreme
-Central tendancy bias

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101
Q

If you are conducting a questionnaire, what should you do to ensure that ethics are kept in line?

A

-Brief participants at start.
-Make the purpose clear.
-Make their data protection rights clear / right to withdraw
-Make sure questions are not ambiguous or leading
-Use simple language.

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102
Q

If you are conducting a questionnaire, what should you NOT do?

A

-Do not have overlapping choices or too few choices.
-No personal details unless absolutely necessary.
-No technical, confusing terms.

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103
Q

Give strengths of questionnaires.

A

-Quick
-Cost efficient
-Less demand characteristics, social desirabillity bias compared to interviews.

104
Q

Give weaknesses of questionnaires.

A

-Low number of responses
-Questions could be misinterpreted = less valid
-Social desirabillity bias.

105
Q

EVALUATE interviews in general as a whole.

A

+Participants free to express
+More detail
-Subject to social desirability bias -Time consuming
-Interviewers need to be trained which is costly
-Investigator variables

106
Q

Describe structured interviews.

A

-Pre-determined questions
-Pre-determined order of questions

107
Q

Give strengths of structured interviews.

A

+Relevant, comparative data
+Reliable and replicable
+Objective analysis

108
Q

Give weaknesses of structured interviews

A

-Participants unable to expand answers = frustration.
-Lacks ecological validity.

109
Q

Describe semi-structured interviews?

A

-Pre-determined questions and order BUT researchers can ask more questions to develop the data further.

110
Q

Give strengths of semi-structured interviews.

A

+More detail and relevant data
+Free expression

111
Q

Give weaknesses of semi-structured interviews

A

-Requires highly trained interviewers = COSTLY
-Only replicable to an extent
-Hard to interpret and compare

112
Q

Describe unstructured interviews?

A

-Conversational style
-No set questions
-General aim is explored
-Interviewer encourages answers to be developed.

113
Q

Give strengths of unstructured interviews.

A

+Less likely to show demand characteristics.
+Ecologically valid data

114
Q

Give weaknesses of unstructured interviews.

A

-Need highly skilled interviewer so costly
-Not possible to replicate so unreliable
-Data difficult to compare
-Time consuming.

115
Q

What are Naturalistic Observations?

A

Naturalist = Watching and recording behaviour in a setting where it would always occur.

116
Q

What are strengths of Naturalistic Observations?

A

+Realistic environment means externally valid and realistic data

117
Q

What are weaknesses of Naturalistic Observations?

A

-Less control over variables so replication is difficult.

118
Q

What are Controlled Observations?

A

Watching and recording behaviours within a structured environment.

119
Q

What are the strengths of Controlled Observations?

A

+Can focus on particular behaviours = replicable
+Controlled and standardised so only IV should affect DV.

120
Q

What are weaknesses of Controlled Observations?

A

-Unnatural, so may lead to demand characteristics
-Social desirability bias
-Less external validity

121
Q

Give a clear difference between Naturalistic and Controlled via an example.

A

Naturalistic - observing and analysing animals in the wild.
Controlled - observing and analysing animals in the zoo

122
Q

What is an Overt Observations?

A

Participants behaviours observed and recorded with their consent or knowledge.

123
Q

What are the strengths of Overt Observations?

A

+Reduced ethical issues as you have consent

124
Q

What are the weaknesses of Overt Observations?

A

-Participants more likely to change their behaviours.
-Lacks validity

125
Q

What is a Covert Observation?

A

Participants behaviours observed and recorded without their consent or knowledge.

126
Q

What are the strengths of Covert Observations?

A

+Participants behaviour reflects their natural behaviour more.
+Increased external validity

127
Q

What are the weaknesses of Covert Observations?

A

-More ethical issues are present e.g. invasion of privacy.

128
Q

How can you overcome ethical issues in Covert Observations?

A

Use public spaces where CCTVs would already capture behaviours
Ask for retrospective consent after the study.

129
Q

What are participant observations?

A

When the researcher becomes part of the group they are studying.

130
Q

What are strengths of participant observations?

A

+Participants are unaware of being observed so behaviour is more natural - externally valid.
+Researcher can develop answers and ask questions for clarity.

131
Q

What are the weaknesses of participant observations?

A

-Higher chance of observer/ researcher bias and variables.
-Ethical issues e.g. consent.
-Difficult to observe / take part in the study at the same time.
-Researcher may lose focus.

132
Q

What are non-participant observations?

A

When the researcher remains outside the group but observes and records behaviours.

133
Q

What are strengths of non-participant observations?

A

+Much more objective and researcher likely to not lose focus.

134
Q

What are weaknesses of non-participant observations?

A

-If participants are aware of being observed, behaviour may change (Demand Characteristics) -Researcher might misinterpret behaviours.
-Reduced ecological validity.

135
Q

What are Structured Observations?

A

Identifies target behaviours (e.g. stretching, itching, etc) and observes these and systematically records them.

136
Q

What are the strengths of Structured Observations?

A

+Collecting data is easier as you have a target behaviour.
+Data is easier to analyse.

137
Q

What are the weaknesses of Structured Observations?

A

-Some behavioural categories may be irrelevant.
-May have missed some behavioural categories.
-Data might lack details.

138
Q

What are Unstructured Observations?

A

The researcher will observe and record ALL behaviours in front of them.

139
Q

What are strengths of Unstructured Observations?

A

+Provides more in depth, detailed results.
+Less likely to have irrelevant data.

140
Q

What are weaknesses of Unstructured Observations?

A

-Produces qualitative data which is harder to analyse.
-Risk of observer and researcher biases.
-Researcher cannot observe and record all data at once - DIFFICULT.

141
Q

Sometimes a clearly defined Predetermined System is used for a structured observation.
What is a predetermined system?

A

A predetermined system:
Splits the structural observation into clearly defined behavioural categories. E.G. Anxiety (structural observation) = shaking, stuttering, stutter, etc.

142
Q

What are Sampling Methods?

A

The method of sampling DATA for a structured observation.

143
Q

What are the two types of Sampling Methods/

A
  1. Time Sampling
  2. Event Sampling
144
Q

What is Event Sampling?

A

Observing at all times.
Counting the number of times a behaviour / event happens.
Must not miss any behaviours.

145
Q

What are the strengths of Event Sampling?

A

+Useful if the behaviour doesn’t happen often and would be missed with time sampling.

146
Q

What are the weaknesses of Event Sampling?

A

-Quite complex as many behaviours are present.
-Easy to overlook and miss some behaviours.

147
Q

What is Time Sampling?

A

Using pre-determined time intervals- e.g. every 5 mins.
Every 5 minutes record and observe what happens.

148
Q

What are strengths of Time Sampling?

A

+Effective in reducing number of observations that must be made TIME EFFICENT.

149
Q

What are the weaknesses of Time Sampling?

A

-Behaviours can often be missed between intervals.
-Less representitive data.

150
Q

What is a correlation?

A

Used to investigate associations, links and relationships between two co-variables.

151
Q

What are Correlational Hypotheses?

A

-Uses existing, intervening data. -No variables manipulated.
-Predicts a LINK.
-The hypothesis can be a NULL or RESEARCH hypothesis.

152
Q

What are Null Correlational Hypotheses?

A

States that there are NO correlations or links between the variables.

153
Q

What are Research Correlational Hypotheses?

A

States that there is some form of correlation or link between the variables.W

154
Q

What does a positive correlation mean?

A

As one variable increases, so does the other.

155
Q

What does a negative correlation mean?

A

As one variable decreases, the other increases.

156
Q

What does a zero correlation mean?

A

No correlation between the two variables.

157
Q

What is a correlation coefficient?

A

Shows how strong a correlation is between the variables.

158
Q

Describe the levels of the correlation coefficient.

A

1 / -1 = Perfect correlation.

0.7 < R < 1 OR -0.7 < R < -1 = Strong correlation.

0.3 < R < 0.7 OR -0.3 < R < -0.7 = Moderate correlation.

0 < R < 0.3 OR 0 < R < -0.3 = Weak correlation.

0 = Zero correlation.

159
Q

What is a Pilot Study?

A

-A small scale version of an investigation carried out beforehand.
-Similar to a trial run.

160
Q

What are the aims of pilot studies?

A

-Checks if procedures, measurements, etc are correct.
-Identifies other mistakes and quick fixes that can be made.

161
Q

When are pilot studies used?

A

-Used beforehand in investigations and self reports.

162
Q

Give an example of a scenario where pilot studies are used?

A

E.G. A questionnaire is sent out to 50 people before sending to 500. Some questions are ambiguous, so the researcher changes the wording of the questions to make it clearer.

163
Q

What is a single blind trial?

A

Participants are unaware of the aims and other aspects of the experiment. This is done to control demand characteristics.

164
Q

What is a double blind trial?

A

Neither the researcher nor participant knows aims of study. REDUCES investigator effects and biases.

165
Q

What is Peer Review?

A

The assessment of scientific work by other specialists in the same field to ensure the research is of high quality.

166
Q

What are the 3 aims of Peer Review?

A
  1. Allocates research funding to those who deserve it most.
  2. Validates the quality and relevance of research.
  3. Suggests easy fixes and amendments before publishing.
167
Q

What are strengths of Peer Review?

A

+It ensures all data is accurate and appropriate research receives appropriate funding.
+Maintains the reputation of psychology.
+It is ANONYMOUS so produces objective, honest reviews.

168
Q

What are weaknesses of Peer Review?

A

-Anonymous reviews might mean more critical / harsh.
-Researchers and reviewers are usually in competition for funding so may be more critical. -Some journals only publish headline grabbing research IGNORING other research.
-Researchers may ignore research that goes against long, old-term research which slows down the rate of change.

169
Q

What is the economy?

A

The state of a country or region in terms of the production and consumption of goods and services.

170
Q

What is meant by the ‘Implications of Psychology on the Economy?’

A

Psychologists must take into account the effects that a research will have on the economy - a good or bad implication.

171
Q

Give a scenario where psychology had a good implication on the economy?

A

Mental Disorder Research.
Improving treatments of mental disorders would lead to more people working and less people being unemployed or on paid leave. BOOSTS economy.

172
Q

Give a scenario where psychology had a bad implication on the economy?

A

Attatchment Research.
This explained that fathers ALSO need to build an emotional connection with their children. This led to paternity leave, which meant more people were on paid leave.

173
Q

What is Quantitative Data?

A

Numerical data - expressed in numbers.

174
Q

What are the strengths of Quantitative Data?

A

+Easy to analyse and compare.
+More objective
+Less open to bias.

175
Q

What are the weaknesses of Quantitative Data?

A

-Lacks details
-May be misleading
-May be invalid and not represent real life.

176
Q

What is Qualitative Data?

A

In depth, descriptive data such as words and images.

177
Q

What are the strengths of Qualitative Data?

A

+Provides more detail, opinions and thoughts.
+Increased external validity.

178
Q

What are the weaknesses of Qualitative Data?

A

-Harder to analyse / subjective.
-Expensive and time consuming. -Harder to compare

179
Q

What is Primary Data?

A

Data collected for a study is directly collected by the researcher.

180
Q

What are strengths of Primary Data?

A

+Authentic data
+Fits aims of study

181
Q

What are the weaknesses of Primary Data?

A

-Time consuming
-Expensive to obtain

182
Q

What is Secondary Data?

A

Data which is collected by other sources and already exists. It should link to the study in some way.

183
Q

What are the strengths of Secondary Data?

A

+Less time consuming
+Inexpensive
+Easily accessed.

184
Q

What are weaknesses of Secondary Data?

A

-May be outdated
-May not match or fully link to your research projects.

185
Q

What is Meta Analysis?

A

The method of looking at many studies and selecting a hypotheses and aims which link to all the studies. Using this, after analysing, a joint conclusion is produced.

186
Q

What is meant by Descriptive Statistics?

A

Use of tables, graphs, summary tables to represent and analyse data while showing trends.

187
Q

What is meant by Measures of Central Tendancy?

A

A general term for any measure of average value in a data set.

188
Q

What is meant by Measures of Dispersion?

A

A general term for any measure which shows spread and variation within scores.

189
Q

What are 3 main examples of Measures of Central Tendancy?

A
  1. Mean
  2. Median
  3. Mode
190
Q

What are 2 main examples of Measures of Dispersion?

A
  1. Range
  2. Standard Deviation.
191
Q

What is meant by Mean?

A

An average of the data.

192
Q

What are the strengths of calculating a mean value?

A

+Each value is accounted for and represented.

193
Q

What are the weaknesses of calculating a mean value?

A

-It is easily affected by outliers.

194
Q

What is meant by Median?

A

The middle score of all the ranked data.

195
Q

What are the strengths of calculating a median value?

A

+Less affected by outliers and skewed data.

196
Q

What are the weaknesses of calculating a median value?

A

-Middle value doesn’t represent all the values / data as a whole.

197
Q

What is meant by Mode?

A

The most common score among all the data.

198
Q

What are the strengths of calculating a modal value?

A

+Useful with categorical and qualitative data to analyse.

199
Q

What are the weaknesses of calculating a modal value?

A

-Modes are not unique. Sometimes more than one modal value is present.
-The mode relies on a value repeating and this isn’t always the case.

200
Q

What is meant by Range?

A

-One example of a measure of dispersion which shows the spread of data.

201
Q

What are the strengths of calculating a range?

A

+Quick and easy to calculate
+Time efficient.

202
Q

What are the weaknesses of calculating a range?

A

-Vulnerable to outliers and extreme scores which means misrepresented data

203
Q

What is meant by Standard Deviation?

A

A sophisticated measure of dispersion that tells us how data is spread over the mean value.

204
Q

What are the strengths of calculating a standard deviation?

A

+Is much more accurate at showing how data is distributed +Also shows distribution around mean so more detailed.
+Less affected by outliers.

205
Q

What are the weaknesses of calculating a standard deviation?

A

-Doesn’t show full range.
-Hard and time consuming to calculate.
-Can only be used when an independant variable is measured against a frequency.
-Assumes a normal distribution which isn’t always the case.

206
Q

What is meant by a high standard deviation?

A

High Standard Deviation = Data is more spread out over the mean.

207
Q

What is meant by a low standard deviation?

A

Low Standard Deviation = Data is much more clustered tightly around the mean.

208
Q

What are the 4 main ways to present and display quantitative data in psychology?

A
  1. Summary Tables
  2. Bar Charts
  3. Scatter Graphs
  4. Histograms.
209
Q

What is meant by a normal distribution?

A

-Heavy on the middle, low on the sides, showing few outliers.
-Mean, median and mode occupy same midpoint.

210
Q

What is meant by a positively skewed distribution?

A

-Heavy on the left.
-Mode at highest point, followed by median then mean.
-Mean towards tail, as it is easily manipulated by outliers.

211
Q

What is meant by a negatively skewed distribution?

A

-Heavy on the right.
-REST SAME AS NEGATIVELY SKEWED.
-Mode at highest point, followed by median then mean.
-Mean towards tail, as it is easily manipulated by outliers.

212
Q

What is probability?

A

The likelihood of an event happening.

213
Q

What is significance?

A

A statistical term that indicates the strength of correlations and helps decide which hypotheses to accept or reject.

214
Q

What is meant by the ‘Standard level of significance?’

A

This is an indication as to which research is acceptable. Psychologists usually accept research at a probability of 0.05 or below - this means there is LESS than 5 in 100 probability that results occurred due to chance.

215
Q

In what instance might the 5% rule not apply?

A

When you need results to be definite. For example, during drug trials you may have to have a stricter 1% rule.

216
Q

What would you do if the standard significance level / probability is ABOVE 0.05?

A

Probability of results occurring due to chance is higher that 5%. The Alternate hypotheses is rejected and the Null is accepted.

217
Q

What would you do if the standard significance level / probability is BELOW OR EQUAL TO 0.05?

A

Probability of results occurring due to chance is less than or equal that 5%. The Alternate hypotheses is accepted and the Null is rejected.

218
Q

What is meant by a Type 1 Error?

A

An error that occurs when a researcher says a study is significant (P<0.05) and accepts the alternate hypotheses BUT in reality the research is not significant.
Should have accepted NULL and rejected ALTERNATE.

219
Q

Give a scenario where a Type 1 Error has occurred?

A

A pregnancy test showing a positive result when the woman isn’t actually pregnant. ‘False positive result.’

220
Q

What is meant by a Type 2 Error?

A

An error that occurs when a researcher says a study is not significant (P>0.05) and accepts the null hypotheses BUT in reality the research is significant.
Should have accepted ALTERNATE and rejected NULL.

221
Q

Give a scenario where a Type 2 Error has occurred?

A

A pregnancy test showing a negative result when the woman actually is pregnant. ‘False negative result.’

222
Q

Why might Type 2 Errors occur?

A

Too strict accepted level e.g. only accepting if the results are 0.01.

223
Q

What is meant by levels of data?

A

Types of data being ordered and ranked depending on a range of factors - each level is more sophisticated than the previous.

224
Q

What are the 4 levels of data, starting at the lowest level?

A
  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
225
Q

What is nominal data?

A

Lowest level of data.
Categories split into subgroups and arranged as a frequency.

226
Q

What are the strengths of nominal data?

A

+Some data can ONLY be recorded as nominal

227
Q

What are the weaknesses of nominal data?

A

-Nominal numbers are just labels - no numerical value.
-Vague as you don’t know nothing about data other than the numbers.

228
Q

What is ordinal data?

A

Second level of data.
Data placed in a specific order which is then ranked.

229
Q

What are the strengths of ordinal data?

A

+Allows to judge the magnitudes such as worst and best.

230
Q

What are the weaknesses of ordinal data?

A

-Can only see the ranking and not the differences in proximity between rankings.

231
Q

What is interval data?

A

Third level of data.
Data expressed by a standard measure / unit which has equal intervals.
Can contain minus numbers.

232
Q

What are the strengths of interval / ratio data?

A

+Allows to judge magnitudes such as who is best and worst.
+Can make meaningful comparisons between individual pieces of data.

233
Q

What are the weaknesses of interval / ratio data?

A

-Highest level of data and has NO WEAKNESSES.

234
Q

What is ratio data?

A

Highest level of data.
Data expressed as a score, but has an absolute 0 (cannot contain minus numbers).
Doesn’t have standard equal intervals.

235
Q

Which measure of central tendancy do you use for each level of data?

A
  1. Nominal = Mode
  2. Ordinal = Median
  3. Interval / Ratio = Mean
236
Q

What is statistical testing?

A

A way of determining and testing which hypotheses should be accepted or rejected.

237
Q

What is the sign test?

A

Type of statistical test which tests for differences in specific data.
Type of non-parametric test.

238
Q

What are the 3 things needed for the sign test?

A
  1. Nominal data
  2. Research studying differences 3. Must be related - repeated measures or matched pairs.
239
Q

What are the strengths of the sign test?

A

+Easy method
+Doesn’t require normal distributions
+Can test BOTH hypotheses.

240
Q

What are the weaknesses of the sign test?

A

-If an observation is equal, or shows no change, the data is ignored.
-Important data overlooked.
-Non-parametric test means reduced statistical power compared to other tests.

241
Q

What are parametric tests?

A

Powerful test which is highly likely to detect differences and correlations.

242
Q

What is the criteria for parametric tests? (5)

A

Data must not be skewed.
Data must have normal distribution.
Data must be interval / ratio.
Data must have no outliers.
Data must have similar standard deviations.

243
Q

Which test would you use for unrelated nominal test?

A

Chi-Squared Test.

244
Q

Which test would you use for unrelated ordinal test?

A

Mann Whitney U Test.

245
Q

Which test would you use for unrelated interval test?

A

Unrelated T-test.

246
Q

Which test would you use for related nominal test?

A

Sign Test

247
Q

Which test would you use for related ordinal test?

A

Wilcoxen Sign Test

248
Q

Which test would you use for related interval test?

A

Related T-test.

249
Q

Which test would you use for a correlating nominal test?

A

Chi-squared test.

250
Q

Which test would you use for a correlating ordinal test?

A

Spearmann’s Rho Test

251
Q

Which test would you use for a correlating interval test?

A

Pearson’s Correlation Coefficient.

252
Q

What is meant by related test?

A

Matched Pairs or Repeated Measures designs.

253
Q

What is meant by unrelated test?

A

Independant Groups Designs.

254
Q

Which tests must be greater than or equal to the critical value in order to be significant? (5)

A

-Chi-Squared Test
-Unrelated T-Test
-Related T-Test
-Spearman’s Rho
-Pearson’s Correlation
All the tests containing the letter ‘R’

255
Q

Which tests must be less than or equal to the critical value in order to be significant? (3)

A

-Mann Whitney U-Test.
-Sign Test
-Wilcoxen Sign Test.

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