RM Flashcards
(126 cards)
1
Q
Pilot studies
A
Small scale investigation before real investigation which identifies potential issues with the procedure so they can be modified
Saves money and time in the long run
2
Q
Single blind procedure
A
Researchers don’t tell participants the aims of the study or if they’re in the experiment or control condition
3
Q
Why do you do a single blind procedure
A
To prevent demand characteristics
4
Q
Double blind procedure
A
Neither the participant nor researcher are aware of the conditions and aims
5
Q
Why do you do a double blind procedure
A
Prevents demand characteristics
Prevents investigator bias
6
Q
Observational technique-Naturallistic
A
Observing and recording behavior in an setting where it would usually take place
7
Q
Strength of naturalistic observation
A
High ecological validity
8
Q
Weakness of naturalistic observation
A
Difficult to replicate
No control of confounding/extraneous variables
9
Q
Controlled observations
A
Observing and recording behavior in a structured environment like a lab
10
Q
Strength of controlled observations
A
Easy to replicate
Control of confounding/extraneous variables
11
Q
Weakness of controlled observation
A
Low ecological validity
Demand characteristics
12
Q
Overt observation
A
Behavior is observed and recorded with the participants knowledge
13
Q
Strength of overt observation
A
Ethically acceptable
14
Q
Weakness of overt observation
A
Demand characteristics
15
Q
Covert observation
A
Behavior is observed and recorded without the participant being aware
16
Q
Strength of covert observation
A
No demand characteristics
17
Q
Weakness of covert observation
A
Ethically questionable
18
Q
Participant observation
A
The researcher is part of the group being observed
19
Q
Strength of participant observation
A
More insightful to the reason behind behaviors
20
Q
Weakness of participant observations
A
May loose objectivity of research
21
Q
Non participant observations
A
The researcher observed from a distance
22
Q
Strength of non participant observations
A
More objective
23
Q
Weakness of non participant observations
A
Lose valuable insight to the reason behind behaviors
24
Q
Observer bias
A
An observer reports are biased by what behaviors they expect to see
25
How do you overcome observer bias
Inter observer reliability
26
How do you calculate inter observer reliability
Total number of agreement
------------------------------------------ x100
Total number of observations
Correlation coefficient of 0.8
27
Observational design-unstructured
Continuous recording where the researcher writes everything they observe
28
Strength of unstructured observation
More richness and depth of detail
29
Weakness of unstructured observation
Qualitative data is difficult to record and analyse
Observer bias
30
Observational design-Structured
Researcher quantifies what they are observing using predetermined behavioral categories and sampling methods
31
Strength of structured interview
Quantitative data is easy to analyse
Less risk of observer bias
32
Weakness of structured interview
Not as much richness or depth of detail
Difficult to achieve high inter observer reliability
33
Behavioral categories
Target behavior being observed is broken down into smaller, more precise target behaviors which are observable and measurable
34
Observational methods-time sampling
Recording behavior within a certain pre established time frame
35
Strength of time sampling
Less time consuming
More accurate identification of behaviors
36
Weakness of time sampling
The data may be unrepresentative of the whole observation
37
Observational methods-event sampling
Continuous observation of a certain behavior
38
Strength of event sampling
Good for infrequent behaviors
More representative
39
Weakness of event sampling
Time consuming
40
What is a correlation
A mathematical technique which measures the relationship between two covariables
Variables are measured, not manipulated
Only relationship, no cause and effect
41
Negative correlation
As one variable increases the other variable decreases
Correlation coefficient between -1 and 0
42
Positive correlation
As one variable increases, the other variable increases
Correlation coefficient 0 to 1
43
No correlation
No relationship between the covariables
Correlation coefficient of 0
44
Curvilinear relationship
As one variable increases, the other decreases to a point after which one variable continues to increase and the other decreases
Yerkes and Dodson
45
Strength of correlations
Quick and economical
Can use secondary data
Can be used as a starting point for other research and experiments
46
Weakness of correlations
Difficult to establish cause and effect
Misused and misinterpreted by media
3rd variable which researchers are unaware of which is causing the relationship between the two covariables
47
Types of data-qualitative
Non-numerical data which is displayed in words
48
Strength of qualitative data
More richness/detail of data
Allows for elaboration
More meaningful insight
49
Weakness of qualitative data
Difficult to analyse and compare with other data
Researcher bias due to subjectivity
50
Types of data-quantitative data
Numerical data not displayed in words
51
Strength of quantitative data
Easy to statistically analyse
Easy to compare data
52
Weakness of quantitative data
Lacks depth of detail
Participants can't elaborate opinion
No meaningful insight
53
Type of data-primary
Information is obtained first hand by researcher
54
Strength of primary data
Targets the exact information that the researcher needs to fit aims
55
Weakness of primary data
Expensive
Time and effort
56
Secondary data
Information and data collected from someone else's research
57
Strength of secondary data
Cheap
Easy to collect
58
Weakness of secondary data
Data could be outdated or incomplete
Unreliable data
59
Types of data-meta analysis
Researcher combines the results of multiple studies and uses the data to gain an overall view of the subject
60
Strength of meta analysis
Generalizable since there is a large pool of reliable data
61
Weakness of meta analysis
Publication bias - researcher intentionally doesn't include research that contradicts their aims
Not representative
62
What are descriptive statistics
Mean
Median
Mode
Range
Standard deviation
63
What are mean median and mode
Measures of central tendency
64
What are range and significant difference
Measures of dispersion
65
Strength and weakness of mean
Uses all the values, very sensitive
Influenced by outliers so can be unrepresentative
66
What data uses the mean
Interval data
67
Strength and weakness of the median
Not affected by extreme outliers
Doesn't use all the data, not as sensitive
68
What data uses the median
Ordinal data
69
Strength and weakness of the mode
Not affected by extreme values
Not useful when there are several modes
70
What data uses the mode
Nominal
71
Strength and weakness of the range
It's easy to calculate
Affected by extreme outliers
Not representative of the whole data
Not data sensitive
72
What is standard deviation
The dispersion of data around the mean
73
Strength and weakness of standard deviation
All data values are accounted for
Difficult to calculate
Effected by extreme values
74
When do you use a data table
Descriptive statistics
75
When do you use bar charts
Discrete data
76
How do you draw a bar chart
Bars don't touch
Frequency of categories Y
Categories X
77
When do you use a histogram
Continuous data
78
How do you draw a histogram
Bars touch
Frequency of categories Y
Equal sized intervals of categories X
79
When do you use a line graph
Continuous data
80
How do you draw a line graph
Points are connected to show change in value
DV Y
IV X
81
When do you use a scatter gram
Correlation between two covariables
82
Right skewed/pos distribution
Highest frequency on the left from mode to median to mean
83
Left skewed/neg distribution
Highest frequency on the right going from mode to median to mean
84
What is a peer review
The assessment of scientific works by experts in the same field to ensure high quality before publishing
85
Why do you peer review
To know if the research is worthwhile funding
To validate relevance and quality of research
To prevent fraudulent or inaccurate research being released
To suggest improvements
86
Issues with peer review
Publication bias
Difficulty finding an expert for specific and poorly researched topics
Fraudulent research could be long lasting- MMR vaccine leads to autism
87
Publication bias
Preferring to publish positive, headlining results over negative ones
88
What are case studies
A detailed study into an individuals life including all of their past and present behavior in great qualitative detail
89
Strength of case studies
Detailed with great insight
Forms basis for future research
Infer normal behavior from unusual cases
Permits otherwise unethical investigations
90
Weakness of case studies
Not generalizable to a wider population
Researcher bias
Time consuming
Difficult to replicate
91
Content analysis
92
Levels of measurement- Nominal data
Categories
Discrete data
Blood type
93
Levels of measurement- ordinal data
Rankings
No equal intervals
Subjective
Happiness on a scale of 1-10
94
Levels of measurement- interval data
Numerical scale
Equal intervals
Objective
Cm, Mm, Ft
95
The order of a scientific report
Abstract
Introduction
Method
Results
Discussion
Referencing
96
Abstract
150-200 word summary of details
Allows researcher to know if study needs further examination
97
Introduction
Information on past research, relevant theories and concepts
Broad to specific
Aims and hypothesis
98
Method
What the researchers did in the study , design, sample, materials, ethics
Allows replicability
99
Results
Findings of the study are given in descriptive statistics
Thematic/content analysis
100
Thematic analysis
101
Discussion
What the findings tell us
Limitations and improvements
Applications to society
102
Referencing
Reference all resources and studies used
103
Book reference
Author,(date),*title of book*,place of publication, publisher
104
Journal reference
Author,(date),journal name,*volume*,issue number, page range
105
Type 1 error
False pos
Incorrectly reject a true null hypothesis to accept the experimental hypothesis, claiming a sig diff when there isn't one
106
Type 2 error
False neg
Failure to reject a null hypothesis when the experimental hypothesis should be accepted, claiming no sig diff when there is one
107
What are the 5 features of a science
-Paradigm/shifts
-Theory construction/hypothesis testing
-Falsifiability
-Replicability
-Objectivity/Empirical testing
108
Objectivity is when
-All possible biases from the researcher are minimized so they don't influence or distiort the research process
109
Empirical method
-Evidence is collected through making direct observations/through direct experience
-
110
Replicability is
-The extent to which scientific methods and their results can be repeated by other researchers across other contexts and circumstances
111
What does falsifiability do for the scientific nature of research
-Its the principle that states a theory cannot be considered scientific unless it allows itself to be proven untrue
112
Who argued for the falsifiability theory?
Popper
-Successful theories that have been proven time and time again just haven't been proven false yet
-Sciences that can't be proven wrong are pseudosciences like freud
-Theories that survived more falsifying are the strongest
113
What is a theory
A set of general principles and laws which can be used to explain specific behaviors
114
What is theory construction
Gathering evidence through direct observations during investigations
115
What is deduction
Deriving new hypothesis from already existing theory
116
Assessing internal validity
Face validity
Concurrent validity
117
What is face validity
Whether the study is measuring what it's supposed to at face value
118
Concurrent validity
Comparing the results of a questionnaire with a previously established one on the same topic
119
How do you improve validity in experimental research
-Single blind procedure
-Double blind procedure
120
How do you improve validity in questionnaires
-Aware of anonymity
-lie scale
121
How do you improve the validity of observations
-Covert observation
122
How do you improve the reliability of questionnaires
-treat retest method
-check for correlation coefficient of 0.8
-questions can't be too complex or ambiguous
123
How do you improve reliability in interviews
-Structured interview
-Same interviewer
124
How to improve reliability in experiments
-Lab experiments
-repeat procedures
125
How to assess internal reliability
Split half method
126
How to assess external reliability
Test retest
Inter observer reliability
