Unit 1 Flashcards
(465 cards)
1
Q
Experimental Method: What are the key types of experiments in psychology?
A
Laboratory
Field
Quasi
2
Q
Role in psychology: What is the major role of experiments in psychology?
A
To show cause and effect by manipulating one variable
3
Q
Laboratory experiments: Where do laboratory experiments take place?
A
Under controlled conditions like a university room
4
Q
Laboratory experiments: What is an advantage of laboratory experiments?
A
Increased level of researcher control
5
Q
Laboratory experiments: What is a disadvantage of laboratory experiments?
A
Reduced ecological validity
DEMAND CHARACTERISTICS :(
6
Q
Field experiments: Where do field experiments take place?
A
In a participant’s natural surroundings
7
Q
Field experiments: What is an advantage of field experiments?
A
Increased ecological validity
8
Q
Field experiments: What is a disadvantage of field experiments?
A
Reduced level of control
Higher likelyhood of extraenuous variables :(
9
Q
True experiments: What are the characteristics of true experiments?
A
Control variables and random allocation of participants
10
Q
Quasi-Experiments: What is the main difference between quasi and true experiments?
A
Quasi-experiments lack control over experimental groups
IV naturally occurs in Quasi
11
Q
Lack of random allocation: When is random allocation not possible in experiments?
A
When a variable is inherent to the participant (e.g. gender)
12
Q
Quasi-Experiments: How are quasi-experiments defined?
A
Studies lacking random allocation but similar to true experiments in other ways
13
Q
Examples of quasi-experiments: Name some examples of quasi-experimental variables.
A
Personality types or presence of a psychological disorder
14
Q
Quasi vs lab: Where can quasi-experiments take place?
A
In a lab setting
In controlled or natural settings
15
Q
Observational Research: What is a characteristic of observational research in terms of sample size?
A
Uses just a more individuals
to counter increased extraenuous varibales
16
Q
Observational research: What is the focus of observational research?
Case Studies
A
One person or a few individuals
17
Q
Observational research: What is a benefit of observational research?
A
Allows for a wide range of behaviours and actions to be recorded
18
Q
Limitations of observational research: What is a major limitation of observational research?
A
- Difficulty in generalising findings to the larger population
- it is often difficult to set up and control
19
Q
Limitations of observation research cont.: Why might generalising from case studies be limited?
A
Cases are often very specific
20
Q
Naturalistic Observation: Where does naturalistic observation take place?
A
In the participant’s natural environment
21
Q
Naturalistic Observation: What is crucial for researchers in naturalistic observation?
A
To be inconspicuous and unobtrusive
22
Q
Naturalistic research: What is naturalistic observation?
A
Observing behaviour in its natural setting without being noticed
23
Q
Animal research: Is naturalistic observation limited to human research?
A
No - it is also used to study animals in their environments
24
Q
Spin
A
Do it
25
Advantages of naturalistic observation: What is the greatest benefit of naturalistic observation?
High ecological validity and accuracy of data
26
Disadvantages of naturalistic observation: What are some major downside of naturalistic observation?
* Difficulty in setting up and controlling
* ETHICS
* Often requires significant investments (time + money)
27
Disadvantages of naturalistic observation: What resources might naturalistic observation require?
Significant time - money - and luck
28
Structured & unstructured observation: How does structured observation differ from unstructured observation?
Structured uses a checklist (coding frame) for specific behaviours; unstructured records all action
29
Structured & unstructured observation: What type of data does structured observation typically generate?
Quantitative data (numbers)
30
Structured & unstructured observation: What type of data can unstructured observation generate?
Quantitative or qualitative data
31
Participant and Non-Participant Observation: What is participant observation?
Researcher joins in the situation being observed
32
Participant and Non-Participant Observation: What is non-participant observation?
Researcher watches from a distance without engaging
33
Non-participant observation: How is data typically collected in non-participant observation?
Through observation schedules and notes
34
Ethics: What ethical consideration arises in observational research?
People must be told they are being observed
35
Ethics: What is the observer effect?
When disclosure of observation alters behaviour
36
Participant observation: When might participant observation be necessary?
To observe effectively without biasing findings in social situations
37
Participant observation examples: Name two classic examples of participant observation. Rosenhan’s psychiatric ward study and Festinger’s religious cult study
38
Limitations: What is a limitation of participant observation?
Researcher's presence may alter behaviour
39
Limitations: What ethical concern exists with participant observation?
Assuming a fake identity to observe
40
Covert - Overt & Controlled Observation: What are the three types of observation you need to know?
Covert - overt - and controlled
41
Covert observation (under cover): What is a benefit of covert observation?
Reduces demand characteristics; natural behaviour
42
Covert observation (under cover): What is a key ethical issue with covert observation?
Lack of informed consent
43
Covert observation (under cover): What is a general rule for ethical covert observation in public places?
Permissible to observe where others might see - but recording usually needs consent
44
Overt observation (in the open): What is a benefit of overt observation?
More ethical as participants are aware
45
Overt observation (in the open): What is a potential drawback of overt observation?
Demand characteristics
46
Controlled observation: How does controlled observation differ from naturalistic observation?
Researcher sets up a situation with a standard procedure
47
Controlled observation: Is controlled observation an experiment?
No - there is no independent variable
48
Controlled observation: What is an example of a controlled observation?
Mary Ainsworth’s Strange Situation
49
Self-Report Techniques: What do self-report techniques involve?
Asking questions via questionnaires/surveys or interviews
50
Self-Report Techniques: What is the goal of self-report techniques?
To allow participants to report on their own thoughts or behaviour
51
Questionnaires: What is a questionnaire?
A list of questions
52
Questionnaires: What is a study using a questionnaire often called?
A survey
53
Questionnaires: What is a benefit of surveys using questionnaires?
Ability to access a lot of participants via various methods
54
Interviews: How do interviews differ from questionnaires?
Involve a trained researcher asking questions face-to-face
55
Interviews: What are the three main types of interviews?
Structured - semi-structured - and unstructured
56
Structured interviews: How are structured interviews conducted?
Researcher asks pre-determined questions and notes responses
57
Semi-structured interviews: How do semi-structured interviews proceed?
Begin with planned questions but allow follow-up questions
58
Unstructured interviews: What is the format of an unstructured interview?
More like an everyday conversation with unplanned questions
59
Social desirability bias: What is social desirability bias in interviews?
Participants altering responses to look good
60
Strengths and Limitations of Interviews: What type of data do interviews tend to generate?
Qualitative - in-depth - and detailed
61
Strengths and Limitations of Interviews: What is a potential strength of semi-structured interviews?
Can lead to serendipitous findings
62
Strengths and Limitations of Interviews: How can interviews have validity?
Rapport develops between researcher and interviewee
63
Strengths and Limitations of Interviews: What is a limitation related to the researcher in interviews?
Researcher bias (verbal or non-verbal)
64
Strengths and Limitations of Interviews: What are some other limitations of interviews?
Demand characteristics - social desirability - difficulty in analysis
65
Questionnaires: What is a questionnaire?
A list of questions answered by participants
66
Questionnaires: What is a benefit of questionnaires regarding sample size?
Allow researchers to get a very large sample size
67
Questionnaires: What is a potential drawback regarding data depth in questionnaires?
Often little depth to the data collected
68
Questionnaires: What is another potential drawback of questionnaires?
People may lie
69
Questionnaires: What are questionnaires used for in psychology research?
To gather data from participants through lists of questions
70
Questionnaires: How can questionnaires be administered?
Paper-and-pencil - electronically - or verbally
71
Questionnaires: What is a practical advantage of questionnaires?
Easy to administer and can be completed quickly
72
Questionnaires: What does the ease of administration allow for?
Collecting data from a large number of people
73
Questionnaires: How do questionnaires aid in generalisability?
By allowing data collection from larger and more diverse samples
74
Advantages of questionnaires: What is a key advantage of using questionnaires?
Ability to collect information from a large sample
75
Advantages of questionnaires: How does a larger sample improve research?
Better reflects population diversity - improving generalisability
76
Advantages of questionnaires: What can be assumed if a questionnaire sample is large and diverse?
Data can be generalised to the larger population with more certainty than case studies
77
Disadvantages of questionnaires: What is a trade-off when using questionnaires with large samples?
Less depth of information on each person
78
Disadvantages of questionnaires: What is another potential weakness of questionnaires regarding accuracy?
People may not always give accurate responses (lie - misremember - or show social desirability)
79
Strengths and Limitations of Questionnaires: What is a strength of questionnaires regarding reliability?
Easy to replicate
80
Strengths and Limitations of Questionnaires: What ethical advantage do questionnaires often have?
Ethical
81
Strengths and Limitations of Questionnaires: How efficient are questionnaires for data collection?
Gather lots of data quickly
82
Strengths and Limitations of Questionnaires: What type of data do closed questions in questionnaires generate?
Quantitative data that is easy to analyse
83
Strengths and Limitations of Questionnaires: What is a limitation of questionnaires regarding validity?
Lacks validity
84
Strengths and Limitations of Questionnaires: What participant effects can occur with questionnaires?
Demand characteristics and social desirability
85
Strengths and Limitations of Questionnaires: What is a challenge in writing effective questionnaire questions?
Difficult to avoid leading or unclear questions (requires pilot studies)
86
Correlation: What does correlation indicate between variables?
A relationship - but not necessarily cause and effect
87
Correlation: What is the relationship between ice cream consumption and crime an example of?
Correlation does not equal causation
88
Correlation: What does it mean when two variables are correlated?
As one variable changes - so does the other
89
Correlation: How is correlation measured?
By calculating a correlation coefficient
90
Correlation: What is a correlation coefficient (r)?
A number from -1 to +1 indicating the strength and direction of a relationship
91
The correlation coefficient: What does the number portion of the correlation coefficient indicate?
The strength of the relationship
92
The correlation coefficient: How does the closeness of the number to one relate to the relationship strength?
Stronger relationship and more predictable changes
93
The correlation coefficient: How does the closeness of the number to zero relate to the relationship strength?
Weaker relationship and less predictable changes
94
Sign of the correlation coefficient: What does the sign of the correlation coefficient indicate?
The direction of the relationship (positive or negative)
95
Sign of the correlation coefficient: What does a positive correlation mean?
Variables move in the same direction
96
Sign of the correlation coefficient: What does a negative correlation mean?
Variables move in opposite directions
97
Sign of the correlation coefficient: What does a correlation coefficient close to zero indicate?
No correlation or no relationship between the two variables
98
Correlational research: What is the usefulness of correlational research?
Helps discover the strength and direction of relationships
99
Correlational research: What is a limitation of correlational research regarding causality?
Does not establish cause and effect
100
Cause-and-effect relationships: Why doesn't correlation imply causation?
A third (confounding) variable might be involved
101
Cause-and-effect relationships: What error do people often make regarding correlation and causation?
Mistakenly claiming causation based on correlation
102
Correlation Coefficient and Evaluation: What does a correlation coefficient of +1 indicate?
A perfect positive correlation
103
Correlation Coefficient and Evaluation: What does a correlation coefficient of -1 indicate?
A perfect negative correlation
104
Correlation Coefficient and Evaluation: What does a correlation coefficient of 0 indicate?
No correlation
105
Spearman’s Rho: What is Spearman’s Rho used for?
Calculating correlation coefficients to measure association strength
106
Spearman’s Rho: What is necessary after calculating a correlation coefficient?
Consulting critical value tables for statistical significance
107
Spearman’s Rho: What do critical value tables indicate?
The calculated value must be greater than or equal to the critical value for significance
108
Confusions: Spearman's Rho: What is a common confusion regarding negative correlation coefficients?
Assuming a larger negative number is smaller than a positive critical value
109
Confusions: Spearman's Rho: What does the minus sign in a correlation coefficient denote?
The correlation is negative - not a numerical value to compare directly
110
Evaluation of correlational research: What is an advantage of correlational research?
Measures the strength of a relationship
111
Evaluation of correlational research: What is another advantage of correlational research?
A useful first step in research
112
Evaluation of correlational research: What is a key disadvantage of correlational research?
Cannot show cause - only a relationship
113
Evaluation of correlational research: What type of relationships might correlation not reflect?
Curvilinear relationships
114
Aims - Questions and Hypotheses: What three elements are specified in each research study?
A research question - an aim - and a hypothesis
115
Aims - Questions and Hypotheses: What is a research question?
An answerable question that the research aims to answer
116
Aims - Questions and Hypotheses: What is the aim of a research study?
What it is trying to achieve or the point of the study
117
Aims - Questions and Hypotheses: What is a hypothesis?
A specific prediction of what the research will find
118
Research question: What is the first step in a research project?
Devising a research question
119
Aim: What does stating the aim of a study involve?
Saying what the researcher is trying to achieve
120
Aim: What is the aim usually linked to?
A real-world purpose or reason for the study
121
Hypotheses: How does a hypothesis differ from an aim?
It makes a specific prediction in terms of variable changes
122
Hypotheses: What is a hypothesis usually based on?
Theories and past research findings
123
Experimental vs alternative: What is the main hypothesis in an experiment called?
Experimental hypothesis (H1)
124
Experimental vs alternative: What is the main hypothesis in a non-experimental study typically called?
Alternative hypothesis
125
Null hypothesis: What is a null hypothesis (H0)?
A statement of what will be found if the experimental/alternative hypothesis is not supported
126
Directional hypothesis: What does a directional (one-tailed) hypothesis predict?
The direction in which change is expected
127
Directional hypothesis: When is a directional hypothesis used?
When previous research suggests the direction of change
128
Directional hypothesis: What kind of language is used in a directional hypothesis?
Precise words like faster/slower - more/less
129
Non-directional hypothesis: What does a non-directional (two-tailed) hypothesis predict?
Change - but does not specify direction
130
Non-directional hypothesis: When is a non-directional hypothesis used?
When there is no previous research
131
Non-directional hypothesis: What kind of language is used in a non-directional hypothesis?
Non-specific words like effect - change - difference
132
Populations and Samples: What are the participants in a research study called?
The sample
133
Populations and Samples: From what wider group is the sample drawn?
The target population
134
Sampling: What does sampling mean in research?
Selecting a group of participants for the study
135
Populations: What is a sample always drawn from?
A broader population (target population)
136
Populations: What is an example of a target population?
All sixth-form school pupils in a country
137
Populations: What is an example of a sample from that population?
A selection of 50 sixth-form school pupils
138
Representation: What is a key aspect of sampling?
The sample should be representative of the target population
139
Representation: What does it mean for a sample to be representative?
It should have similar characteristics to the target population
140
Representation: Why is studying a representative sample important?
Allows the researcher to generalise findings to the target population
141
Sampling Techniques: How many ways are there to obtain a sample for research?
Multiple ways
142
Opportunity sampling: How are participants accessed in opportunity sampling?
Based on their convenient availability to the researcher
143
Opportunity sampling: Give examples of opportunity sampling. Research on friends - classmates - or students
144
Opportunity sampling: What is a major bias of opportunity sampling?
The most easily available participants may not be representative
145
Self-selected sampling: How do participants become involved in self-selected sampling?
They volunteer in response to an advert or call
146
Self-selected sampling: Give examples of self-selected sampling. Responding to a noticeboard advert or online survey
147
Self-selected sampling: What is a source of bias in self-selected sampling?
Certain personality types are more likely to volunteer
148
Random sampling: What is required for random sampling?
All members of the target population have an equal chance of selection
149
Random sampling: Does random sampling guarantee a representative sample?
No - but it minimises the chances of a biased sample
150
Random sampling: Give an example of random sampling. Putting names in a hat and drawing a sample
151
Evaluation of random sampling: What is a strength of random sampling with a large sample?
Probability suggests it should be representative
152
Evaluation of random sampling: What is a limitation of random sampling regarding participants?
They may not be willing or able to participate
153
Evaluation of random sampling: What is another limitation of random sampling regarding bias?
Sample could still be biased in terms of certain variables
154
Snowball sampling: How does snowball sampling work?
Current participants recruit other participants
155
Snowball sampling: When might researchers use snowball sampling?
When struggling to find participants organically
156
Snowball sampling: Does snowball sampling involve probability?
No
157
Experimental Design: What key decision must researchers make when designing an experiment?
Whether to use separate groups or have one group do all conditions
158
Basic design: How many experimental conditions does every experiment have at least?
Two (or one experimental and one control)
159
Basic design: What does having multiple conditions allow researchers to do?
Compare the effects of different values of the independent variable
160
Repeated measures: What happens in a repeated measures design?
Every participant completes every condition
161
Independent groups: What happens in an independent groups design?
Participants are split into groups - each doing one condition
162
Evaluation of repeated measures: What is a benefit of repeated measures design regarding participant variables?
Minimises them as the same people are studied
163
Evaluation of repeated measures: What are potential drawbacks of repeated measures design?
Participants may guess the hypothesis or show order effects
164
Evaluation of independent groups: What is a drawback of independent groups design regarding participant variables?
Suffers from them as different people are studied
165
Evaluation of independent groups: What are benefits of independent groups design?
Avoids order effects and makes the hypothesis harder to perceive
166
Matched pairs: How does a matched pairs design work?
Participants in different groups are matched on key characteristics
167
Matched pairs: What is the aim of matched pairs design?
To minimise participant variables while using different groups
168
Matched pairs: How are participants allocated to conditions in matched pairs design?
Randomly allocating one member of each pair to each condition
169
Variables: What is a key aspect of experimental research?
The control and measurement of variables
170
Key variables: What are the two key variables in any experiment?
The independent variable (IV) and the dependent variable (DV)
171
Key variables: What does the researcher do with the independent variable?
Changes or manipulates it
172
Key variables: What does the researcher do with the dependent variable?
Measures it
173
Key variables: What is the goal of an experiment regarding the IV and DV?
To find out if the IV has an effect on the DV
174
Example - memory technique: In the memory technique example - what is the IV?
The use of the memory technique or not
175
Example - memory technique: In the memory technique example - what is the DV?
Recall on a test of the facts
176
Controlling variables: What is necessary to test cause and effect between IV and DV?
Keeping other variables constant
177
Confounding variables: What is a confounding variable?
An outside variable that changes across conditions and can ruin the experiment
178
Confounding variables: In the memory technique example - what would be a confounding variable?
Giving one group more study time
179
Confounding variables: Why are confounding variables problematic?
They make it impossible to be sure if the IV affected the DV
180
Extraneous variables: What are extraneous variables?
Variables that can't be entirely eliminated (e.g. - noise - temperature)
181
Extraneous variables: What does the researcher try to do with extraneous variables?
Minimise their effects as much as possible
182
Extraneous variables: What type of error do remaining extraneous variables cause?
Random error - but they don't invalidate the experiment
183
Counterbalancing and Standardisation: What are two further aspects of experimental control?
Counterbalancing and standardisation
184
Conditions: What happens when a researcher uses a repeated measures design?
Participants complete two or more experimental conditions
185
Conditions: Why is the order of conditions important in repeated measures design?
Can lead to order effects (practice - boredom - fatigue)
186
Conditions: What are order effects?
When performance in a condition is influenced by the order in which it is completed
187
Counterbalancing: What technique is used to minimise order effects?
Counterbalancing
188
Counterbalancing: How does counterbalancing work?
Half do condition 1 then 2 - the other half do 2 then 1
189
Counterbalancing: Does counterbalancing eliminate order effects?
No - but it stops them from becoming a confounding variable
190
Standardisation: What does standardisation mean in research?
Using a standard procedure for all participants
191
Standardisation: Name some aspects that should be standardised in an experiment. Instructions - briefing/debriefing - location - time of day - materials
192
Standardisation: Why is standardisation necessary?
To avoid extraneous or confounding variables affecting results
193
Random allocation: What does random allocation refer to?
Allocating participants to experimental and control conditions randomly
194
Random allocation: Give an example of a random allocation method. Pulling names from a hat or tossing a coin
195
Random allocation: What is the purpose of random allocation in independent measures design?
To control for some participant variables (individual differences)
196
Randomisation: What is randomisation?
Deciding the order of tasks or data presentation randomly
197
Randomisation: What is the aim of randomisation?
To control for order effects
198
Randomisation: Give an example of where randomisation might be used. Order of pictures in an attractiveness rating study
199
Observational Design - Behavioural Categories & Sampling: What must a researcher consider when designing an observation study?
How to gain data from the situation
200
Observational Design - Behavioural Categories & Sampling: What are the main choices related to gaining data in observation?
Behavioural categories - event sampling - and time sampling
201
Prior planning: What does observation studies involve?
Prior planning to consider likely behaviours
202
Observation schedule & coding frames: What are different behaviours combined into for observers?
Categories (e.g. - aggression for punching and kicking)
203
Observation schedule & coding frames: Where are behavioural categories listed?
On an observation schedule
204
Observation schedule & coding frames: What do coding frames allow researchers to do?
Observe specific behaviours within a category and note severity or sub-categories
205
Event sampling: What does event sampling involve?
Recording an event every time it happens over a period
206
Event sampling: Give an example of event sampling. Recording instances of aggression in a playground over 20 minutes
207
Event sampling: What else might be recorded during event sampling?
What else was happening at the same time
208
Time sampling: What does time sampling involve?
Recording the most prominent behaviour at many different points in time
209
Time sampling: How can the points in time be selected for time sampling?
Randomly or systematically
210
Time sampling: Give an example of time sampling. Observing a child every two minutes and recording their activity
211
Limitations: What do behavioural categories and sampling techniques do for observation?
Simplify the process and make it more reliable
212
Limitations: What can be a drawback of simplifying observation?
Reduce the level of detail and validity
213
Questionnaire Construction: What is very important when designing a self-report study?
The wording of questions
214
Questionnaire Construction: What can badly worded questionnaires lead to?
Flawed data
215
Questionnaire Construction: What is one key consideration in questionnaire design?
The use of open and closed questions
216
Extraneous variables: What type of error do remaining extraneous variables cause?
- Random error - but they don't invalidate the experiment
217
Counterbalancing and Standardisation: What are two further aspects of experimental control?
- Counterbalancing and standardisation
218
Conditions: What happens when a researcher uses a repeated measures design?
- Participants complete two or more experimental conditions
219
Conditions: Why is the order of conditions important in repeated measures design?
- Can lead to order effects (practice - boredom - fatigue)
220
Conditions: What are order effects?
- When performance in a condition is influenced by the order in which it is completed
221
Counterbalancing: What technique is used to minimise order effects?
- Counterbalancing
222
Counterbalancing: How does counterbalancing work?
- Half do condition 1 then 2 - the other half do 2 then 1
223
Counterbalancing: Does counterbalancing eliminate order effects?
- No - but it stops them from becoming a confounding variable
224
Standardisation: What does standardisation mean in research?
- Using a standard procedure for all participants
225
Standardisation: Name some aspects that should be standardised in an experiment?
Instructions - briefing/debriefing - location - time of day - materials
226
Standardisation: Why is standardisation necessary?
- To avoid extraneous or confounding variables affecting results
227
Random allocation: What does random allocation refer to?
- Allocating participants to experimental and control conditions randomly
228
Random allocation: Give an example of a random allocation method?
Pulling names from a hat or tossing a coin
229
Random allocation: What is the purpose of random allocation in independent measures design?
- To control for some participant variables (individual differences)
230
Randomisation: What is randomisation?
- Deciding the order of tasks or data presentation randomly
231
Randomisation: What is the aim of randomisation?
- To control for order effects
232
Randomisation: Give an example of where randomisation might be used?
Order of pictures in an attractiveness rating study
233
Observational Design - Behavioural Categories & Sampling: What must a researcher consider when designing an observation study?
- How to gain data from the situation
234
Observational Design - Behavioural Categories & Sampling: What are the main choices related to gaining data in observation?
- Behavioural categories - event sampling - and time sampling
235
Prior planning: What does observation studies involve?
- Prior planning to consider likely behaviours
236
Observation schedule & coding frames: What are different behaviours combined into for observers?
- Categories (e?
237
Observation schedule & coding frames: Where are behavioural categories listed?
- On an observation schedule
238
Observation schedule & coding frames: What do coding frames allow researchers to do?
- Observe specific behaviours within a category and note severity or sub-categories
239
Event sampling: What does event sampling involve?
- Recording an event every time it happens over a period
240
Event sampling: Give an example of event sampling?
Recording instances of aggression in a playground over 20 minutes
241
Event sampling: What else might be recorded during event sampling?
- What else was happening at the same time
242
Time sampling: What does time sampling involve?
- Recording the most prominent behaviour at many different points in time
243
Time sampling: How can the points in time be selected for time sampling?
- Randomly or systematically
244
Time sampling: Give an example of time sampling?
Observing a child every two minutes and recording their activity
245
Limitations: What do behavioural categories and sampling techniques do for observation?
- Simplify the process and make it more reliable
246
Limitations: What can be a drawback of simplifying observation?
- Reduce the level of detail and validity
247
Questionnaire Construction: What is very important when designing a self-report study?
- The wording of questions
248
Questionnaire Construction: What can badly worded questionnaires lead to?
- Flawed data
249
Questionnaire Construction: What is one key consideration in questionnaire design?
- The use of open and closed questions
250
Importance of wording: Why is careful wording important in questionnaires?
The researcher isn't present to clarify questions
251
Wording flaws: Name some flaws in questionnaire wording?
Jargon - leading questions - vague questions - offensive questions
252
Closed questions: What are closed questions in questionnaires?
Questions with a selection of provided options
253
Closed questions: Give examples of closed question formats?
Yes-no - multiple choice - Likert scales
254
Open questions: What are open questions in questionnaires?
Questions where participants can write their own answers
255
Open questions: What is a benefit of open questions?
Richer detail in responses
256
Open questions: What is a drawback of open questions?
Harder to summarise and analyse
257
Combination: Can interviews use both open and closed questions?
Yes
258
Combination: How does the face-to-face format of interviews help with wording?
Allows the researcher to clarify questions
259
Follow-up questions: What might interviews include based on participant responses?
A series of possible follow-up questions
260
Nominal and Ordinal Data: Name the four main types of data?
Nominal - ordinal - interval - and ratio
261
Nominal and Ordinal Data: What does the type of data influence?
How it is statistically analysed
262
Nominal data: What is nominal data?
Data that fits into distinct categories
263
Nominal data: How is nominal data collected?
By counting the frequency of each category
264
Nominal data: Give a biological example of nominal data?
Hair colour (brown - black - red - etc?
265
Nominal data example: In a bystander effect study - what could be nominal data?
Whether individuals help or not help
266
Nominal data example: How is nominal data analysed in the bystander example?
Counting the frequency of helpers and non-helpers
267
Ordinal data: What is ordinal data?
Data that falls along a scale
268
Ordinal data: What does ordinal data relate measurements to?
The same variable
269
Ordinal data: Where is ordinal data often seen?
In surveys
270
Ordinal data example: What is a common example of ordinal data?
A Likert scale (e?
271
Ordinal data example: Give another example of ordinal data in psychology?
Rating depression symptoms on a 1-to-10 scale
272
Interval Data: What is interval data?
Measurement on a scale with equally sized and objective units
273
Interval data: How does interval data differ from ordinal data?
Units are equally sized and objective - not subjective
274
Interval data: Why can 1-to-10 scales for subjective measures be miscategorised?
They reflect personal opinions - making them ordinal
275
Objectivity: What is required for data to be interval?
Set units and intervals must be objective
276
Objectivity: Give examples of interval data?
Time (seconds) and temperature (Celsius)
277
Objectivity: Why are seconds considered interval data?
They are equally sized and objective
278
Objectivity: Why is temperature (Celsius) considered interval data?
Universal standard and standardised measuring equipment
279
Tests: How are different types of data analysed?
Using different statistical tests
280
Tests: Name statistical tests used for nominal data?
Sign test or Chi-squared test
281
Tests: Name statistical tests used for ordinal data?
Spearman’s rho - Wilcoxon test - or Mann-Whitney test
282
Tests: Name statistical tests used for interval data?
Pearson’s r test - unrelated t-test - or related t-test
283
Quantitative and Qualitative Data: What are the two main types of data?
Quantitative and qualitative data
284
Quantitative vs qualitative: What does quantitative data involve?
Numbers (e?
285
Quantitative vs qualitative: What is qualitative data?
Non-numerical data (e?
286
Experimental data: What type of data do experiments tend to gather?
Quantitative data
287
Experimental data: What does quantitative data allow for in analysis?
Calculating descriptive statistics
288
Non-experimental data: What types of data can non-experimental methods gather?
Either quantitative or qualitative
289
Non-experimental data: How do self-report methods gather different data types?
Open questions = qualitative; closed questions = quantitative
290
Combination of data: Can research studies gather both quantitative and qualitative data?
Yes
291
Combination of data: How can qualitative data be converted to quantitative data?
By categorising written answers and calculating percentages
292
Primary and Secondary Data: What type of data do experiments and other methods typically gather?
Primary data
293
Primary and Secondary Data: What other type of data do psychology researchers use?
Secondary data (from existing sources)
294
Primary data: Give examples of methods that gather primary data?
Observation - experiments - and self-report
295
Primary data: What does gathering primary data mean?
Obtaining data that did not previously exist
296
Secondary data: What is secondary data?
Data obtained from existing sources
297
Secondary data: Give examples of secondary data sources?
Government statistics - school exam results - public datasets
298
Secondary data: What are two other forms of secondary data?
Systematic reviews and meta-analyses
299
Systematic reviews: What is a systematic review?
Reviewing multiple existing studies to draw conclusions and identify gaps
300
Meta-analysis: What is a meta-analysis?
Calculating an overall finding based on multiple previous studies
301
Meta-analysis: How reliable is a meta-analysis result compared to a single study?
Usually more reliable
302
Measures of Central Tendency: What can statistics be used for regarding a population?
To describe it
303
Mode: What is the mode?
The most common value
304
Mode: Can there be more than one mode?
Yes
305
Median: What is the median?
The middle value when ordered by size
306
Median: How is the median calculated with two middle numbers?
The midpoint of those two values
307
Mean: What is the mean?
The sum of all values divided by the number of items
308
Mean: Write the equation for the mean?
x=nΣx
309
Measures of Dispersion: What do measures of dispersion show?
The spread of data
310
Measures of Dispersion: Name three measures of dispersion?
Variation - range - and standard deviation
311
Measures of dispersion: What do measures of dispersion provide an idea of?
How spread out a set of scores are
312
Measures of dispersion: Give an example of data sets with the same mean/median but different dispersion?
10 - 20 - 30 and 19 - 20 - 21
313
Variance - range & standard deviation: Name the three key measures of dispersion?
Range - variance - and standard deviation
314
Variance - range & standard deviation: How is the range calculated?
Highest score minus the lowest score
315
Variance - range & standard deviation: What does variance look at?
The difference between each data point and the mean
316
Variance - range & standard deviation: What does standard deviation show?
The typical amount scores differ from the mean
317
Calculating Variance & Standard Deviation: What does standard deviation provide a measure of?
The overall amount of variation in a data set
318
Calculating Variance & Standard Deviation: How can standard deviation be used?
To determine if a data value is close to or far from the mean
319
Variance: What needs to be calculated before standard deviation?
The variance
320
Variance: What is the variance?
The average of the squares of the deviations
321
Variance: How can each deviation be written?
x−x
322
Variance 2: Write the equation for variance (σ2)?
σ2=nΣ(x−x)2=nΣx2−(nΣx)2≡nSxx
323
Variance 2: What is Sxx?
Σ(x−x)2=Σx2−n(Σx)2 - a summary statistic
324
Standard deviation: Write the equation for standard deviation (σ)?
σ=nΣ(x−x)2=nΣx2−(nΣx)2≡nSxx
325
Frequency table: Write the equation for standard deviation from a frequency table (σ)?
σ=ΣfΣf(x−x)2=ΣfΣfx2−(ΣfΣfx)2≡ΣfSxx
326
Percentages: What are percentages a useful form of in psychology data handling?
Summarising self-report data and comparing scores
327
Standardised scores: What are percentages?
Standardised scores out of a hundred
328
Standardised scores: What does the number 100 represent in a percentage?
The whole or maximum
329
Standardised scores: What does the percentage represent?
The fraction of the whole or maximum
330
Calculation: How are percentages calculated from a fraction?
(Smaller number / Larger number) * 100
331
Uses of percentage: How can percentages be useful for self-report methods?
Summarising results - e?
332
Easy comparison: How do percentages aid comparison?
By standardising scores - e?
333
Fraction of ?
?
334
Percentage of ?
?
335
Presentation and Display of Quantitative Data: How is quantitative data typically displayed?
Using graphs and charts
336
Presentation and Display of Quantitative Data: Name common examples of quantitative data displays?
Tables - bar charts - scattergrams
337
Tables: When are tables typically used in research reports?
To display numerical findings (descriptive statistics)
338
Tables: What is an advantage of tables for readers?
Easier to find information than in written text
339
Tables: Can tables be used to summarise qualitative data?
Yes
340
Charts: What do charts offer in data presentation?
A more visual way to show data
341
Charts: What can charts help illustrate?
Smaller and larger differences between conditions
342
Bar chart: What is the most common type of graph in psychology research?
The bar chart
343
Bar chart: What does the x-axis usually show on a bar chart in psychology?
The independent variable (IV)
344
Bar chart: What does the y-axis usually show on a bar chart in psychology?
The dependent variable (DV) (mean score)
345
Bar chart: What does each bar on a bar chart represent?
One condition of the IV
346
Histograms and pie charts: How frequently are histograms and pie charts used compared to bar charts?
Less frequently
347
Histograms and pie charts: What does a histogram show on the x-axis?
A continuous variable (e?
348
Histograms and pie charts: What is a line graph similar in purpose to?
A histogram
349
Histograms and pie charts: What should a pie chart represent?
Fractions of a whole
350
Histograms and pie charts: When might a pie chart be used in research?
To describe sample characteristics
351
Scattergrams: What are scattergrams used for?
To show correlations - not experimental results
352
Line graphs: When do researchers use line graphs?
For continuous data
353
Line graphs: What is on the x-axis of a line graph?
Independent variable
354
Line graphs: What is on the y-axis of a line graph?
Dependent variable
355
Line graphs: How are data points shown on a line graph?
Plotted and connected with straight lines
356
Sections of a Scientific Report: Name the basic sections of a scientific report?
Title - abstract - introduction - aim/hypotheses - method - results - discussion - references - appendices
357
Sections of a Scientific Report: Why is this structure used?
Easier to read - research - and reference
358
Title: What should the title of a scientific article do?
Succinctly summarise what the study is about
359
Title: What variables should the title include?
The independent and dependent variable
360
Title: Give an example of a scientific article title?
“An investigation into the effects of caffeine on short-term memory recall”
361
Abstract: What is the abstract of a scientific article?
A summary of the article
362
Abstract: What is the purpose of the abstract?
To help scientists quickly identify the study's focus and relevance
363
Abstract: What should the abstract include?
Aim - hypotheses - brief summaries of method and results
364
Introduction: What is a common confusion regarding the abstract and introduction?
Students often mix them up
365
Introduction: What does the introduction provide?
A description of the background of the study
366
Introduction: Give examples of background information in a study on caffeine and memory?
What caffeine is - its effects - what short-term memory is - its variability
367
Introduction cont?
: What does the introduction provide the foundations for?
368
Introduction cont?
: What can the introduction include?
369
Introduction cont?
: Give examples of what might be referenced in the caffeine/memory study introduction?
370
Aim: Where is the aim of the study stated in the report?
In the aim section - after the introduction
371
Aim: What does the aim section explain?
Why the study is being done
372
Aim: Give an example of an aim?
“The investigation will examine the effects of caffeine on short-term memory recall?
373
Hypotheses: How does a hypothesis differ from the aim?
It is stated slightly differently
374
Hypotheses: What variables should the hypothesis include?
The independent and dependent variables
375
Hypotheses: What characteristic should a hypothesis have?
It should be testable
376
Hypotheses: Give an example of a hypothesis?
“Higher doses of caffeine will increase short-term memory recall”?
377
Method of a Scientific Report: What should the method section include?
Design - procedure - participants - and resources
378
Method: What does the method section lay out?
How the study was completed and techniques used
379
Method: How detailed should the method section be?
Detailed enough for other scientists to replicate the study
380
Method: Why are repeat studies crucial?
They help to validate the results of the initial study
381
Design 1: What are key points included in the design of the investigation?
Research method and materials used
382
Design 1: Give examples of research methods?
Laboratory experiment - natural experiment - questionnaires - observations
383
Design 1: Give examples of materials used?
Question sets - technology like fMRI or EEG
384
Design 2: What else should the research design detail?
The specific research design (independent groups etc?
385
Design 2: What issues related to the design should be addressed?
Limitations of the chosen design and how they were overcome
386
Design 2: What is important to detail regarding extraneous variables?
How they were controlled to limit their impact
387
Design 3: What ethical issues are important to address in the method?
Informed consent - deception - protection from harm - debriefing - confidentiality
388
Procedure: What is the procedure section?
A step-by-step outline of how the study happened
389
Procedure: What should the procedure section start with?
Addressing ethical issues
390
Procedure: What should be detailed regarding participant interaction?
How they were introduced and informed consent obtained
391
Procedure cont?
: Why is a standardised procedure important?
392
Procedure cont?
: What should be provided to participants in a standardised way?
393
Procedure cont?
: What else should be outlined in the procedure?
394
Procedure cont?
: What final detail should the procedure include?
395
Method of a Scientific Report (Cont?
): What should the method section include?
396
Participants: What should a description of participants include?
How many were used and their demographics
397
Participants: What demographic information might be included?
Gender - age - socioeconomic status - race (depending on the study)
398
Participants - sampling: What are various types of sampling methods?
Random - opportunity - volunteer - systematic - stratified
399
Participants - sampling: What should be described about the sampling method?
The type selected and the reason why
400
Conditions: What account should be provided regarding participant assignment?
How participants were assigned to study conditions
401
Conditions: Give examples of how participants might be divided into conditions?
By gender - age - or a combination
402
Resources: What is outlined in the resources section of the method?
Details of materials and equipment used
403
Resources: What should be included if the study involved interviews?
The list of questions used
404
Resources: What details should be provided for any equipment used?
A description - and including pictures can be beneficial
405
Results of a Scientific Report: What can the results of a study be?
Qualitative or quantitative
406
Qualitative or quantitative: What should be done if the results are quantitative?
Statistical tests should be conducted
407
Qualitative or quantitative: How should qualitative data be analysed?
Thematically (summarising) or content analysed (categorising)
408
Statistical analysis: What is the purpose of statistical analysis on results?
To describe patterns that support or negate the hypothesis
409
Statistical analysis: What are the two main types of statistical analysis?
Descriptive and inferential
410
Descriptive statistics: What do descriptive statistics refer to?
Measures of central tendency and dispersion
411
Descriptive statistics: How is descriptive data typically represented?
As tables - graphs - or charts for conciseness
412
Inferential statistics: What is the purpose of inferential statistical tests?
To show how significant the results are
413
Inferential statistics: Name some inferential statistical tests?
Spearman’s rho - Pearson’s r - Wilcoxon test - sign test - t-tests - Mann-Whitney test
414
Inferential statistics: What is important to remember about these tests?
Each has their own advantages and disadvantages
415
Why?
: What values should be stated in the results section?
416
Why?
: What final point should be discussed regarding statistical tests?
417
Why?
: Give an example of test selection based on design?
418
Discussion in a Scientific Report: What key things should the discussion section include?
Explanation of data - implications - limitations - relation to previous research - future research suggestions
419
Data: What does the results section do with data?
Quantifies it
420
Data: What should be done with the presented data in the discussion?
It should be analysed and explained
421
Data: How should the data be explained?
In the context of previous research - the current study - and future impacts
422
Impact of results: What do psychological studies often reflect?
Real-life situations
423
Impact of results: What should the discussion section argue?
The extent to which the results impact real life
424
Impact of results: Give an example of real-life implications?
Informing schools/exam boards about caffeine's effect on memory
425
Limitations: What is true of all research studies?
They will have certain limitations
426
Limitations: What might cause study limitations?
Logistics - finances - or the nature of the study
427
Limitations: What should be done with study limitations?
They should be discussed openly
428
Limitations: What can be provided for future scientists?
Modifications for improvement
429
Comparison: What does a scientific report start with?
The introduction describing background research
430
Comparison: What should researchers do in the discussion section regarding previous work?
Connect their study to it
431
Comparison: What should be done with the data from the current and previous studies?
Compare it - do the results support or negate?
432
Forward-looking: What is the discussion section like in relation to the introduction?
Sort of the reverse
433
Forward-looking: What does the discussion section look forward to?
Suggestions of what further research should be done
434
References and Appendices: Where do the references and appendices appear in a scientific report?
At the end
435
References: What must be referenced in a scientific report?
All sources used (books - studies - websites - etc?
436
References: Why is proper referencing crucial in science?
To acknowledge previous works and ideas
437
Formatting: What do references follow?
A strict format (usually journal-specific guidelines)
438
Formatting: What is a general rule for reference order?
Alphabetical order by the lead scientist’s surname
439
Appendices: What is the final section of a scientific report?
The appendices
440
Appendices: What might the appendices include?
Questionnaires - interview transcripts - apparatus diagrams
441
Appendices: What else is included in the appendices?
Raw data and statistical test calculations
442
Importance: Why are appendices important for peer review?
Allow verification of findings
443
Importance: What is the purpose of appendices besides peer review?
To provide materials for repeat studies without cluttering the report
444
Peer-Reviewing: What is peer-reviewing?
Other scientists providing feedback on a study before publication
445
Peer-Reviewing: What does peer-reviewing help provide for research?
A level of quality control
446
Peer-reviewed journal: Who reads a peer-reviewed journal article?
Several other scientists with expertise in the subject (usually anonymously)
447
Peer-reviewed journal: What do peer reviewers provide?
Feedback to the author and journal editor regarding the draft's quality
448
Peer-reviewed journal: What does the journal editor do with peer reviewer feedback?
Compiles it and decides on publication (as is - with revisions - or rejected)
449
Peer-review feedback: What do peer reviewers look for regarding the research rationale?
A strong justification for the study
450
Peer-review feedback: What do peer reviewers check regarding the method?
A clear and ethical description of how the research was conducted
451
Peer-review feedback: What flaws do peer reviewers look for?
In the study's design - methods - and statistical analyses
452
Peer-review feedback: What do peer reviewers assess about the authors' conclusions?
Whether they are reasonable based on the observations
453
Peer-review feedback: What else do peer reviewers comment on?
The value of the research in advancing the discipline's knowledge
454
Use of peer-reviewing: How does peer-reviewing help prevent unnecessary duplication?
By ensuring each article provides new information
455
Use of peer-reviewing: What degree of control does peer review provide for psychological research?
Some degree of quality control
456
Use of peer-reviewing: What can happen to poorly conceived studies through peer review?
They can be weeded out
457
Use of peer-reviewing: How can even well-designed research benefit from peer review?
Through suggested revisions
458
Peer review for replication: What does peer review ensure regarding the research description?
That it is clear enough for other scientists to replicate it
459
Peer review for replication: What does replication allow other scientists to determine?
The reliability of the findings using different samples
460
Replication: What does each replication of a study provide?
More evidence to support the original findings
461
Replication: What can replications sometimes involve?
Additional measures that expand on the original finding
462
Replication: How do successful replications influence scientists' adoption of findings?
Make them more apt to adopt them
463
Replication: What effect do repeated failures to replicate have?
Cast doubt on the legitimacy of the original article
464
Replication example: What was the hypothetical medical study about?
A new drug aiding weight loss without diet change
465
Replication example: What would happen if other scientists couldn't replicate the drug study results?
The original study's claims would be questioned
