Paper 1 Flashcards
(182 cards)
1
Q
Three parts of paper 1
A
Multiple choice, Research methods, Calculations
2
Q
What is a research aim
A
What the researcher is investigating
3
Q
What is a research question
A
A question regarding what is being studied
4
Q
What are the two types of sampling
A
Event sampling
Time sampling
5
Q
What is event sampling
A
Recording every time an event occurs in a specific time frams
6
Q
What is time sampling
A
Recording what can be observed after a given time interval
7
Q
Strengths of event sampling
A
More accurate as all behaviours are recorded
Infrequent behaviours are still likely to be recorded
8
Q
Weaknesses of event sampling
A
Requires a lot of focus over an extended period of time
May miss things
9
Q
Strengths of time sampling
A
Can see changes in behaviour over the time period
Increased focus
Allows time for recording data
10
Q
Weaknesses of time sampling
A
May miss infrequent behaviors
May not be representative of the entire time period
11
Q
Types of time sampling
A
One-Zero
Instantaneous
Predominant
12
Q
What is One-Zero sampling
A
Recording behaviours that do occur as a 1 and those that dont as a 0. Doesnt matter how many times the behaviours occur
13
Q
What is Instantaniuos sampling
A
Records if behaviours occur in a specific instant
14
Q
What is Predominant sampling
A
Observes the whole interval and makes note of most common activity
15
Q
5 key points of an observation
A
Who you observe
What you look for
When you observe them
Where the observations take place
How you observe them
16
Q
Who (observations)
A
Sampling technique
Sample size
Is sample representative
17
Q
What (observations)
A
Structured - set behaviours to look for
Unstructured - No pre set behaviours
18
Q
What is a coding frame
A
A table used to record data during a structured observation. Has a set range of categories that the individual is looking for. All categories must be observable
Tally each time the behaviour is shown
19
Q
Strengths of structured observations
A
Creates objective data
Easy to conduct
20
Q
Weaknesses of structured observations
A
Coding frame may not include all displayed behaviours
21
Q
Strengths of unstructured observations
A
Gets more detail
Unexpected behaviours are still recorded
22
Q
Weaknesses of unstructured observations
A
Data collected is more subjective
Takes time and effort for the data to be recorded
23
Q
Where (observations)
A
Naturalistic
Controlled
24
Q
What is a Naturalistic observation
A
Carried out in the participants usual environment
25
What is a Controlled observation
Carried out in a lab setting manipulated by the researcher
26
Strengths of naturalistic observations
High ecological validity
More likely to act as they usually would in that environment
27
Weaknesses of Naturalistic observations
Could be extraneous variables from the environment
Could be hard to see and record all data
28
Strengths of controlled observations
Higher levels of controls over variables
Easy to set up environment for observation
29
Weaknesses of controlled observations
Low ecological validity
People may alter behaviour due to unnatural conditions
30
Naturalistic Ethics
Observations do not need consent when in public locations that strangers are likely to be looking at them anyway
31
When (observation)
Time of day
Day of week
Time of year
Length of observation
32
How (Observation)
Participant
Non-Participant
33
What is Participant observation
When the observer is present in the location of the participants
34
What is Non-Participant observation
When the observer is not present in the location of the participants
35
Strengths of Participant observation
View is less likely to be obstructed
Can gather more information from being close to the participants
36
Weaknesses of participant observation
Time consuming to set up
Could be dangerous
Could lose objectivity if rapport is built with participants
37
Strengths of non participant observation
Less risk of bias
Less time to set up
Less safety concerns
38
Weaknesses of non participant observation
Less control
View is likely to be obstructed in some way
39
How (Observation)
Covert
Overt
40
What is covert observation
Participants are unaware they are being watched
41
What is overt observation
Participants are aware they are being watched
42
Strengths of covert observation
Participants may be more natural in behaviour
Less effort from the researchers
43
Weaknesses of convert observation
Breaks ethical guidelines
Might be hard to record data
44
Strengths of overt observations
Abides by ethical guidelines
Easier to observe and take notes
45
Weaknesses of overt observations
Participants may change their behaviours
Takes time and effort to obtain consent
46
Validity in Observations
Observer Bias
Observer Effects
47
What is observer bias
Observer may focus on some things more than others due to expectations
48
What are observer effects
When the participant changed their behaviour as a result of being watched.
49
What are experiments looking for
Cause and effect of an IV on a DV
Studying the influence of one on the other
50
What do correlations do
Explain how two covariables interact with each other.
Study the relationship between the variables
51
Types of correlation
Positive (Increase Increase)
Negative (Increase Decrease
None (No relation)
52
What is operationalising (correlation)
Ensuring both variables are ordinal or interval data so can be plotted on a scatter graph
53
Correlational Hypothesis
1 tailed
2 tailed
Null
54
What is a 1 tailed hypothesis
Significant specified correlation between X and Y
55
What is a 2 tailed hypothesis
Significant unspecified correlation between X and Y
56
What is a Null hypothesis
No significant correlation between X and Y
57
What is a correlation coefficient
Number between -1 and 1 which shows direction and strength of a correlation
58
Strengths of correlation studies
Can reveal new information
Can be used when variables cannot be manipulated
Can be a good starting point to lead to further investigation
59
Weaknesses of correlation studies
Do not tell us about cause and effect
Cannot collect qualititative data
60
Two types of self-report
Interviews
Questionnaires
61
Qualities of interview
Direct verbal questioning
Can vary in structure (structured, unstructured, semi-structured)
62
Qualities of questionaires
Written method of gaining data
Participant or researcher led
Not always requiring researcher present
63
Types of question
Open question
Closed question
64
What is an open question
Requires more than a one word answer. Ask about emotions or opinions. Require space below them to provide an answer
65
What is a closed question
Give participants a set quantity of options from which to answer with. Can easily be transferred to quantitative dat a
66
Strengths of closed questions
Easy to analyse
Quick to compare
67
Weaknesses of closed questions
May be open to interpretation
Do not provide insight into why
Standard response set
68
What us a standard response set
The tendency for a participant to answer the questions without truly considering them
69
Strengths of open questions
gives participants freedom within their answers
Detailed information
70
Weaknesses of open questions
Harder to analyse
Hard to compare
May have a lot of irrelevant data
71
What is a rating scale
A form of closed question that requires the participant to give a number to indicate strength and attitude toward something
72
Strength of rating scale
Quantitative data
Gives more detail than yes/no
73
Weakness of rating scales
Different interpretations of the same number
Only a set number of responses
No data on why
74
How doy ou reduce a standard response set?
Have some positively and negatively framed messages
75
What is a likert scale?
Closed question that requires a mark in a box to indicate agreement to a statement
76
What is a semantic differential
Closed questions that require the participant to place their feelings between two polar opposite terms
77
What is a structured interview
Interviewer asks the same questions to all the participants in the same order
78
What is a semi-structured interview
Interviewer will have a set of prepared questions but can change depending on the answers of the individual
79
What is an unstructured interview
Interviewer has topics to discuss but no set questions or order. More conversational
80
Strengths of structured interviews
High internal reliability
Easy to analyse and compare data
81
Weaknesses of structured interviews
Restrictive as cannot ask follow up questions
May miss out on some useful information
Superficial
82
Strengths of semi-structured interviews
More trustworthy
Higher ecological validity
Both qualitative and quantitative data
83
Weaknesses of semi-structured interviews
Reliability may not be high as participants have varying experiences
Harder to compare participants
84
Strengths of unstructured interviews
High ecological validity
Lots of detailed qualitative data
85
Weaknesses of unstructured interviews
Low internal reliability
Broad range of topics covered
86
Strengths of questionnaires
Large quantities of data
Large samples
Confidentail
87
Weaknesses of questionnaires
Researchers must be careful with questions asked
Lacks ecological validity
May lie in the questionnaire
88
What is response rate
Rate of fully complete questionnaires handed in
89
Strengths of interviews
Different structures to support different research aims
Can get both quantitative and qualitative data
90
Weaknesses of interviews
Unreliable if semi-structured
May lack ecological validity
Time consuming
91
Reliability (observations)
Split half
Test-Retest
92
What is Split half reliability
when the questions are split in half and analysed separately. If they gives similar results internal reliability is good
93
What is test-retest reliability
When a questionnaire is repeated with the same group to see if there is a consistent effect
94
Three levels of data
Nominal
Ordinal
Interval/Ratio
95
What is nominal
The lowest level of data - a headcount of who does one thing compared to another
96
What is Ordinal data
Individual scores achieved in relation to one another
97
What is Interval data
Individual scores using a calibrated instrument of measuring
97
What is an experiment
Research method that has an independant, dependant and control variables
98
Conditions of an experiement
Experimental condition
Control condition
99
What is an Experimental condition
The group of participants who experience a manipulation of the independent variable
100
What is a control condition
The group of participants who do not experience a manipulation of an independent variable
101
Aim of experiments
To establish cause and effect. Finding out what effect the iv has on the DV
102
Types of experiment
Lab experiment
Field experiment
Quasi experiment
103
What is a Lab experiment
An experiment that takes place in a controlled setting
104
What is a field experiment
An experiment that takes place in a naturalistic setting
105
What is a quasi-experiment
An experiment that looks an an IV that isnt manipulated by the researcher
106
Strengths of Lab experiments
Controlled settings reduce the effects of extraneous variables
Increases internal reliability as has high level of controls
107
Weaknesses of Lab experiments
Low ecological validity
More effort to conduct
People may act strange in a controlled setting
108
Strengths of field experiments
Higher ecological validity
High construct validity
109
Weaknesses of field experiments
Higher chance of extraneous variables influencing results
Participants may have differing experiences, lowering internal reliability
110
Strengths of quasi experiments
High ecological validity
Helps study variables we cant manipulate
111
Weaknesses of quasi experiments
Difficult to conduct
Cannot control some of the participant variables
112
What is an Extraneous variable
Factors that can influence your dependant variable that is not the independent variable. They lower construct validity
113
Examples of Extraneous variables
Situational
Environmental
Participant
Order effects
Demand characteristics
Social Desirability bias
114
Experimental designs
Independent measures
Repeated measures
Matched participants
115
What is the independent measures design?
When different people are used in each condition of the experiment
116
What is repeated measures design?
When the same people are used in each condition of the experiment
117
What is a matched participant design
When similar people (matched on specific traits) are used in each condition of the experiment
118
Strengths of repeated measures design
Removes the presence of participant variables
Easier to obtain sample
119
Weaknesses of repeated measures design
Easier for the participant to work out what the experiment is looking for (Demand characteristics)
Order effects
120
Strengths of independent measures design
Participants are unaware of which condition they are in (lower demand characteristics)
No order effectsW
121
Weaknesses of independent measures design
More effort to collect participants
May be influenced by participant variables
122
What is an order effect
When participants do better / worse in the second condition due to practise / fatigue
123
Strengths of matched participants
Reduces participant variables
No order effects
Low chance of demand characteristics
124
Weaknesses of matched participants
Effort to pretest the participants in order to match them
Cannot perfectly match them
125
What is a demand characteristic
When participants try to work out the aim of the study and then change behaviour
126
What is researcher bias
When a researcher influences the participants behaviour or responses
127
What is a single blind procedure
Participants are not aware of what condition they are in
128
What is a double blind procedure
Both participants and experimenters are unaware of who is in each condition
129
Two types of experimental hypothesis
Alternative
Null
130
What is a null hypothesis
There will be no significant difference between in tge DV between the groups
131
What is an alternate hypothesis
There will be a significant difference in the DV between the groups
132
What is a one tailed hypothesis
The direction of influence is directly mentioned
133
What is a 2 tailed hypothesis
No direction of influence is spoken about
134
What is operationalising a variable
Deciding the metric of measurement
135
What is the target population of a sample
The group the experimenters wish to apply the findings to
136
What is a generalisable sample
Diverse enough to be applied to the broader public
137
What is a large sample size
Sample contains enough people to establish a consistent effect
138
Sampling methods
Self selecting
Opportunity
Snowball
Random
139
What is self selecting sampling
Participants volunteer to take part in the study
140
What is opportunity sampling
Participants are obtained at the time and place of the research
141
What is snowball sampling
Participants suggest other people to take part
142
What is random sampling
Every member of the target population has an equal chance of being selected
143
Strengths of self-selecting sampling
Easy to obtain
Already given consent - more likely to continue to the end of the study
No researcher bias as they volunteer
144
Weakness of self-selecting sampling
Unrepresentative - unemployed, keen on psych etc.
Expensive if money incentive
Could lead to a small sample
145
Strengths of oppurtunity sampling
Easy to obtain at the time
Good way of ensuring the target population is obtained
146
Weaknesses of oppurtunity sampling
Unrepresentative depending on where it is done
Researcher bias (approach a certain type of person)
147
Strengths of random sampling
Everyone has equal chance of selection
Representative
148
Weakness of random sampling
More outliers
Hard to do
Selected people may not want to take part
149
Strengths of snowball sampling
Easy to obtain
150
Weaknesses of snowball sampling
Not able to generalise - people pick other s with similar traits
151
Types of data
Primary
Secondary
Quantitative
Qualitative
152
What is primary data
Directly obtained by the researcher
153
What is secondary data
Obtained using another source
154
What is quantitative data
Represented by numbers
155
What is qualitative data
Represented by words
156
Strengths of quantitative data
Easy to make comparison
No researcher bias
Easy to summarise
157
Weaknesses of quantitative data
May not be representative
Doesnt tell us why participants behave in a certain way
158
Strengths of qualitative data
More detail about participant experiences
Richer data
159
Weaknesses of qualitative data
Harder to compare
Cannot represent easily
Can be interpreted in various ways
160
What is raw data
Data collected before analysis
161
What are descriptive statistics
Ways to summarise the findings of a study
162
What are measures of central tendency
averages of results
163
what are Measures of dispersion
Measures of how the data is spread
164
What are inferential statistics
Statistical tests to find out significance of results
165
What are the measures of central tendency
Mean - add + divide
Median - line up
Mode - most common
166
Strengths of mean
Involves all data so more representative
167
Weaknesses of mean
Outliers may skew results
Can give decimals which may not make sense
168
Strengths of median
Discounts outliers
169
Weaknesses of median
does not include all data
May be a decimal figure
170
Strengths of mode
Easy to calculate
Always whole value
Can be done with qualitative data
171
Weaknesses of mode
May be no mode or multiple modes
Doesnt include all data
172
What are the measures of dispersion
Range
Variance
SD
173
What is the range
Tells you the spread between maximum and minimum values
174
What is the variance
Tells you the spread of each value from the mean
175
What is the standard deviation
Tells you the spread of data in relation to the mean
176
Strengths of range
Easy to calculate
Shows spread between max and min
177
Weaknesses of range
Doesn' t show if spread is even
Can be skewed by outliers
178
Strengths of variance
Takes all data into account
Less likely to be skewed by outliers
179
Weaknesses of variance
More time consuming
Not the same units as original measure
180
Strengths of SD
Same units as measure
Easy to calculate if variance is done
181
Weaknesses of SD
Takes outliers into account
