Research Methods Flashcards
1
Q
How are aims developed
A
From theories based on many hours of research from other sources
2
Q
What are aims
A
A general statement that describes the purpose of an investigation
3
Q
Give an example of an aim for energy drinks making someone more talkative
A
To investigate whether drinking energy drinks makes people more talkative
4
Q
What is a hypothesis
A
A statement made at the start of a study and describes the relation between variables as stated by the theory
5
Q
What are the 2 different types of hypothesis
A
Directional and non-directional
6
Q
What is a directional hypothesis
A
Researcher clearly states the difference that should be anticipated between 2 conditions
7
Q
Give an example of a direction hypothesis using energy drinks and talkativeness
A
People who drink energy drinks will become more talkative
8
Q
What is a non directional hypothesis
A
It states that the independent variable will have an effect on the dependent variable but the direction of the effect is not specified
9
Q
Give an example of non-directional hypothesis using energy drinks and talkativeness
A
People who drink energy drinks differ in talkativeness compared to those who don’t
10
Q
When are directional hypothesis used
A
When theories or previous research suggest a likely outcome and there is no contradictory research
11
Q
When are non directional hypothesis used
A
When there is a lack of research or contradictory findings on the research topic
12
Q
What is the independent variable
A
The thing the researcher changes or manipulates
13
Q
What does the researcher measure in an experiment
A
The impact changing the IV has on the dependant variable
14
Q
What should happen to all other variables that may effect the dependant variable
A
They should remain constant
15
Q
Why do extraneous variables need to stay constant
A
So the researcher is certain the IV alone is affecting the DV
16
Q
What do different experiments does a researchers usually run
A
A control group when IV isn’t manipulated and an experimental group where the IV is changed
17
Q
Why is a control group important
A
To draw conclusions about the effect of manipulating the IV
18
Q
Why do we need to operationalise variables
A
To make them testable
19
Q
What does operationalising variables mean
A
Making it testable by adding in time or quantity such as test participants talkativeness after 300ml of caffeine- the 300ml is operationalising the variables
20
Q
What is the key to an experiment
A
IV is manipulated to see how it effect DV, any other variables that interfere with the IV should be controlled or removed
21
Q
What are extraneous variables
A
Anything that is not the independent variable that has the potential to affect the results. Should be controlled where possible. Four types: situational variables, participant variables, investigator effects, demand characteristics
22
Q
What are nuisance variables
A
Straightforward variables to control like age or room lighting that don’t vary systematically with the IV
23
Q
What is the difference between extraneous and cofounding variables
A
Extraneous make it harder to detect a result but don’t confound study findings, but, cofounding variables vary systematically with the IV and may cause confusion over what variable is effecting the results
24
Q
What are cofounding variables
A
Unmeasured variable that influences the relationship between an independent and dependent variable. Could be an extraneous variable that has not been controlled.
25
What is participant reactivity
An extraneous variable in experimental research which is difficult to control
26
What are demand characteristics
Clues which may help participants interpret what’s going on, they may help participant to work out the study aim and therefore effect the results
27
How may a person act if there are demand characteristics
They may over perform to try and please the experimenter (please-U effect) or may perform to sabotage the experiment (screw-U effect), either way there behaviour is no longer natural
28
What is investigator effects
An unwanted influence of the investigator on the research outcome, it can include expectancy effects and unconscious cues or from the research design like participants, equipment or procedure used
29
What is a good example of investigator effects
Leading questions
30
What is randomisation
The use of chance methods to reduce the researchers unconscious bias when designing an investigation and control investigator effects
31
How does randomisation work
Anything such as order of participants or order of numbers or words in an experiment or different conditions should be selected randomly and in a random order
32
Why is it important to standardise procedures
To ensure All participants should be subject to the same environment, info and experience
33
How does standardisation work
There is an exact list of what will happen in the study, including standardised instructions read to each participants
34
What is experimental design
The way in which participants are used in experiments, how they are arranged in different experimental conditions
35
What is independent groups
When 2 separate groups of participants experience 2 different conditions of the experiment, if there are 2 levels of IV each group of participant only experiences 1 IV and the performance of the 2 groups is compared
36
What is repeated measures
All participants experience both experimental conditions and 2 mean scores from both conditions are compared
37
What is matched pairs
Participants are paired together on a variable related to the experiment amd then allocated to different experimental conditions
eg. Participants may be matched by IQ
38
What is matched pairs an attempt at doing
Controlling cofounding variables of participant variables
39
What are limitations with independent groups
Participants variables may effect the results, if experimenter finds a difference between the 2 groups it may be down to participant variables not the IV change. Also, it is less economical than repeated measure as double participants needed, increases time And money spent
40
How do experiments deal with participant variables in independent groups
Random allocation
41
What is a strength of independent groups
Order effects are not a problem so participants less likely to guess aims of study
42
What is a limitation of repeated measures
Participants have to do 2 tasks and it becomes obvious what the IV is which may cause participants to act unnaturally. Order effects also arises as doing 2 tasks may create boredom or fatigue so that may influence results of second tasks or participants performance may improve through practice also effecting results. Order acts as cofounding variable
43
How do experimenters deal with issues of repeated measures
Counterbalancing- some participants start with one condition and others start with the other condition
44
What is a strength of repeated measures
Participant variables are controlled and more economical as fewer participants needed
45
What is a strength of matched pairs
Participants only take part in single condition so order effects and demand characteristics less of a problem
46
What is a limitation of matched pairs
Participants will never be exactly matched, there will always be important differences and it can be time consuming and expensive so less economical
47
What are lab experiments
Conducted in highly controlled environments, not necessarily a lab
48
Strength of lab experiments
High control of cofounding variables and extraneous variables so effect on DV Is likely from IV so high internal validity. Replication is easier and replication is vital to ensure results are valid and not a once off finding
49
What is a limitation of lab experiments
Lack generalisability as may be artificial and not like everyday life, people behave differently in unfamiliar contexts so has low external validity and may give rise to unnatural behaviour from demand characteristics. Also low mundane realism as lab experiments don’t represent everyday experiences
50
What is a field experiment
IV is manipulated in natural more everyday environment, researcher goes to participant
51
Strengths of field experiments
High mundane realism as more natural environment so field experiments may produce more valid and authentic behaviour, especially is participants unaware there being studied so high external validity
52
What are limitation of field experiments
Loss of control over cofounding and extraneous variables, so cause and effect between IV and DV more difficult to establish and replication is difficult. Also, ethical issues of participants are unaware they can’t consent and may be an invasion of privacy
53
What are natural experiments
Researcher measures effect of IV on DV but has no control over the IV. Something else caused IV to vary such as before and after a natural disaster, natural IV doesn’t always refer to the setting of the experiment
54
Strengths of natural experiments
They provide opportunities for research that may not otherwise be done for practical or ethical reasons like Romanian orphans studies, they also have high external validity as involve study of real world problems as they happen
55
Limitation of natural experiments
Naturally occurring events happen rarely so reduce research opportunity. Participants may not be randomly allocated to experimental conditions so less sure of effect of IV on DV, this research may be done in a lab so lack realism and demand characteristics may be an issue
56
What is a quasi experiment
The IV is an existing difference between people such as age or gender, nothing manipulated the variable it just exists and the IV can’t be changed. DV may be naturally occurring or devised by experimenter and measured in lab or field
57
Strengths of quasi experiments
Often carried out in controlled conditions so can be replicated and had high control
58
Limitation of quasi experiments
Can’t randomly allocate participants so may be cofounding variables and IV not deliberately changed so can’t claim IV caused an observed change
59
What is population
A large group of people that a researcher is interested in, often called a target population
60
Why are not all of the target population sampled
For practical and economical reasons
61
Why is it important the small group of the target population is representative
So generalisations can be made
62
How are samples selected
Using a sampling technique that aims to produce a representative sample
63
What is random sampling
Form of sampling where all members have equal chance of selection, obtain a complete list of all participants in the target population and all names assigned numbers, then used lottery method to randomly generate numbers and then will be the sample
64
What is systematic sampling
When every nth member of a target population is selected, u can use a sampling frame to do this. Order population in alphabetical order and every 5th person is selected or order may be randomly generated to reduce bias
65
What is stratified sampling
Composition reflects certain strata within target population. Researcher identifies different strata and then representative sample sizes for each strata is calculated. Within each strata participants are then selected randomly using lottery method
66
What is opportunity sampling
Select who is available and willing to participate in there study. They may ask who is around them at the time for example in the street
67
What is volunteer sampling
Participants select themselves, advert for this may be placed in a newspaper
68
Strength of random sampling
Unbiased so cofounding and extraneous variables divided between each group giving high internal validity
69
Limitations of random sampling
Time consuming, complete list of target population hard to obtain, may still end up with unrepresentative sample and some selected participants may refuse to take part which then turns random sampling to volunteer sampling
70
Strength of systematic sampling
It’s objective as once the system for the selection is established researcher has no influence over who’s picked
71
Limitation of systematic sampling
Time consuming and participants may refuse to take part
72
Strength of stratified sampling
Method produces a representative sample which reflects target population so generalisations are possible
73
Limitation of stratified sampling
Time consuming and strata don’t represent all ways people differ so not completely representative
74
opportunity sampling strengths
It is convenient and much cheaper and less time consuming as list of target population isn’t needed
75
Limitations of opportunity sampling
Researcher bias may effect results and bias from taking data from just one area so can’t be generalised to whole target population
76
Volunteer sampling strength
It is easy and requires limited input from researcher so less time consuming and volunteers will be more engaged
77
Limitation of volunteer sampling
Volunteer bias as asking volunteers selects a certain profile so findings can’t be generalised to target population
78
What are ethical issues
Arises when conflict exists between researchers need to get valuable info and participants rights
79
What is informed consent
Participants should know what there getting into, it involves making participants aware of the aims, procedures and their rights- including right to withdraw- and what there data is used for. Participants can then decide if they want to continue. But for a research getting informed consent may make their study meaningless due to demand characteristics
80
What is deception
Deliberately misleading or withholding info from participants, if a participant isn’t given adequate info they can’t give informed consent. There are occasions deceptions is ok if it doesn’t cause participant distress
81
What is protection from harm
Participants shouldn’t be placed at more risk than their everyday lives and must be protected from physical and psychological harm-being embarrassed or put under stress. Participants must constantly be reminded they have the right to withdraw
82
What is privacy and confidentiality
Participants have right to control info about themselves- privacy and they have a right to have their personal data protected- confidentiality
83
What is the BPS code of conduct
It includes ethical guidelines and researchers have a professional duty to follow them. They attempt to make sure all participants are treated with respect and consideration during research. They are implemented by ethics committees and are a cost benefit approach to determine if a research proposal is ethically acceptable. It isn’t a legal requirement to follow them but they may lose job if they don’t
84
How do researchers deal with informed consent
Participants should be issued with a consent letter detailing relevant information and the sign it. If participants are under 16 parental consent is required
85
How do researchers deal with deception
At end of study participants are debriefed and participants are told true aims of the study
86
How do researchers deal with protection from harm
Participants should be told they have a right to withdraw and withhold information. Participants should be assured their behaviour was normal and if participants subject to stress or embarrassment researcher should provide counselling
87
How do researchers deal with confidentiality
Researchers must protect any personal details by anonymity. Researchers often used numbers of initials and in debriefing participants reminded their data is protected and won’t be shared with other researchers
88
What are the three types of consent
Presumptive consent, prior general consent and retrospective consent
89
What’s presumptive consent
Similar group of people are asked if they would give consent and if answer is yes then consent is presumed
90
What is prior general consent
Participants give permission to take part in many studies including ones involving deception
91
What’s retrospective consent
Participants asked for consent after the study during debriefing
92
What is a pilot study
A small scale trail run of an actual investigation
93
What does a pilot study involve
Handful of participants to check the procedure and experiment runs smoothly, they can be used for experimental studies, interviews, questionnaires and self reporting studies
94
Why is a pilot study useful in observational studies
Provides a way of checking coding system before real investigation and may be important in training observers
95
Why are pilot studies useful
Allow researchers to identify potential issues and modify the design or procedure saving time and money in the long run
96
What is a single blind procedure
Participants not told which experimental condition they are in and any info that may create expectations isn’t revealed due to demand characteristics
97
What is double blind procedure
Neither participant or researcher is aware of the aims of the investigation
98
Where are double blind procedures useful
In drug trails comparing placebo to the real drug
99
What is the difference between control and experimental group
Control is a baseline study to compare the experimental groups results to. If significant change observed between the 2 we can suggest the IV effects the DV.
100
What is an important non-experimental method of gaining data
Observation
101
What are observations
Allow researchers to observe behaviour within a natural or controlled setting, it allows flexibility to study more complex interactions between variables. Observations are often used in experiments to assess dependant variable
102
What is a naturalistic observation
Takes place where target behaviour would occur, all aspects of environment are free to vary
103
What is a controlled observation
Some control over variables including manipulating variables and control of cofounding and extraneous variables
104
What are covert observations
Observations where participants are unaware they are the focus of the study and their behaviour is observed in secret. Such behaviour must be public and happening anyway in order to be ethical
105
What are overt observations
Participants know their behaviour is being observed and have given informed consent
106
What is participant observation
The observer may become part of the group they are studying
107
What is non participant observations
Researcher remains separate from the participants
108
What is a strength of observations
Capture how people naturally behave, so gives special insight
109
Limitation of observations
Observer bias- may be effected by their expectations
110
What is a strength of naturalistic observations
High external validity as findings generalised to everyday life as behaviour is studied in same environment where it naturally occurs
111
Limitation of naturalistic observations
Lack of control makes replication of the investigation difficult and maybe many cofounding and extraneous variables making it hard to judge behaviour
112
What is a strength and a limitation of controlled observations
They may produce findings that can’t be applied to everyday life but they have good control over cofounding and extraneous variables
113
Strength and limitation of covert observations
No demand characteristics as don’t know there being observed which gives high internal validity but ethics is a problem as no informed consent
114
Strength and limitation of overt observations
They are ethically acceptable but participants know there being observed which may effect their behaviour
115
Strength and limitation of participant observation
Research can experience situation as participant does giving them more insight so good external validity but may identify too strongly with the group and lose objectivity - referred to as going native
116
Strength and limitation of non-participant observations
Allow researchers to maintain objective psychological distance but may lose valuable insight as they are too far removed from people and behaviour being studied
117
What is unstructured observation
Researcher writes down everything they see and produces a lot of detail, may be appropriate in small scale observations
118
What is a structured observation
Researcher makes behavioural categories which are the focus of the investigation and makes note when these behaviours observed
119
What are behavioural categories
Target behaviours must be broken down into a set of behavioural categories (behaviour checklist), these target behaviours must be precisely defined and made observable and measurable
120
What is continuous recording
Every element of the Behaviour is recorded and is a key feature of unstructured observations
121
What is event sampling
Involves counting the number of times a particular behaviour occurs in a target individual or group
122
What is time sampling
Involves recording behaviour within a pre-established time frame
123
Strength and weakness of structured observation
Recording data is easier and likely to produce quantitive data, so comparing data is easier, but there is less detailed observations produced
124
Strength and limitation of unstructured observations
Produce qualitative data which is harder to analyse but they benefit from more depth detail. But greater risk of researcher bias as there are no behavioural categories, researcher only records certain behaviours which may not be most important
125
What is important of behavioural categories
That they are clear and unambiguous, they must be observable, measurable and self-evident so shouldn’t require further interpretation, categories should be exclusive and not overlap
126
When is event sampling useful
If event happens infrequently and could be missed by time sampling but specific event is often to complex and important details are overlooked by event sampling
127
When is time sampling effective
Reducing number of observations that have to be made but this can lead to under representation of whole observation
128
How do researchers avoid researcher bias
To make data objective and unbiased observations should have 2 or more researchers and then this data is compared for consistency
129
What is inter rater reliability
When agreement between researchers is measured
130
How should inter rater reliability be carried out
Observers must use the same behavioural categories, observers must observe the behaviour at the same time maybe using a pilot study, observers compared data and discuss any differences, observers should analyse the data from the study and inter observer reliability calculated by correlating each pair of observations and overall figure is produced
131
What are questionnaires
A self reporting technique involving a list of pre set questions to which a participant responds, used to assess thoughts and feelings, they can also be used in experiments to assess the dependant variable
132
What are open questions
Have a wide range of answers and produces qualitative data which can be hard to analyse
133
What are closed questions
Offers a fixed range of responses and produces quantitive data which is easy to analyse but lacks depth and detail
134
What are the 3 types of interviews
Structured, unstructured, semi-structured
135
What are structured interviews
Pre determined set of questions that are asked in fixed order
136
What is an unstructured interview
More like a conversation, no set questions, just a general aim that a certain topic will be discussed, interviewee is encouraged to expand answers
137
Semi-structured interviews
Pre set list of questions but interviewer can asked follow up questions based on previous answers
138
What is strengths of questionnaires
Cost effective as get large amounts of data quickly and completed without researcher present, data from them is easy to analyse especially is questions are closed, data can be statistically analysed and comparisons made using graphs and charts
139
What are limitations of questionnaires
Response may not be truthful, called social desirability bias which is a type of demand characteristic, they can produce response bias as limited answers given and questions may be miss read
140
Strength and weakness of structured interview
Easy to replicate and difference between interviewers reduced, but limited richness in data collected as interviewer can’t deviate
141
Strength and weakness of unstructured interviews
More flexibility and interviewer can get more insight, but may lead to interviewer bias and analysis of data isn’t easy, also risk interviewees may lie for social desirability
142
What are 3 ways of designing questions in a questionnaire
Likert scales, rating scales and fixed-choice options
143
What is a likert scale
Respondent indicates their agreement with a statement from strongly agree to strongly disagree usually on a 5 point scale
144
What is a rating scale
Responding represents a value that shows their feelings to a certain topic
145
What is fixed choice option
Items include a list of possible options and respondents tick options that apply to them
146
What is an interview schedule
List of questions the interviewer intends to cover, they should be standardised to reduce interviewer bias. The interviewer will take notes during the interview or record it and analyse it later
147
Where may group interviews be appropriate
In case of clinical setting
148
How should one on one interviews take place
In a quiet room away from people so interviewee is more likely to open up, they should ask a few general questions first to make sure the interviewee is relaxed
149
What is jargon
A technical term only familiar to those in a specialised field or area and not understood by ordinary people
150
How should questions in an interview not be worded
They should avoid using emotive language and leading questions as it can bias the answers given
151
What are problems with double barrel questions in interviews and questionnaires
Respondent may agree with the first half but not the second half
152
What does correlation show
The strength and direction of an association between 2 or more co-variables
153
How are correlations plotted
On a scattergram, one co-variable represented on x-axis and other on the y-axis
154
What is a positive correlation
A positive correlation means as the x axis value increases they y axis value also increases
155
What is a negative correlation
As the y axis decreases the x axis increases
156
What is zero correlation
There is no pattern between the two observed variables
157
In an experiment what does the researcher control and manipulate
IV in order to measure its effect on the dependant variable
158
How is correlation different from an experiment
There is no manipulation of one variable and so cause and effect between one co-variable and another can’t be measured
159
What are strengths of correlations
Useful preliminary research tool, they provide a quantifiable measure of how 2 variables are related, correlations are quick and easy to carry out, no need for controlled environment and can be done using secondary data so it’s economical
160
What are limitations of correlations
Lack of experimental manipulation and control within a correlation means it doesn’t tell us why variables are related, also third variable problem where a cofounding variable may be causing the correlation, correlations can be misinterpreted- positive correlation interpreted as definite facts when it may not be true due to third variable problems
161
What is qualitative data
Data in words such as written description of thoughts and feelings and opinions of participant, interviews or notes from counselling sessions are qualitative data, can be collected by interview or unstructured observation
162
What is quantitive data
Expressed numerically from individual scores, data can be statistically analysed and easily converted into graphs
163
Is qualitative or quantitative data better
Both have their advantages and qualitative data can also be converted into quantitive data
164
What is primary data
Original data that has been collected for the purpose of the investigation by researcher, its first hand data and gathered by questionnaire, interview or observation
165
What is secondary data
Data collected by someone other than the person conducting research, data already exists as researcher starts their experiment, this data can be subject to statistics testing so it’s significance is known, this data includes journal articles, books or websites or info held by the government
166
What is a strength of qualitative data
Offer lots of detail and allows participants to fully explain their thoughts so had high external validity and gives meaningful insight
167
Limitations of qualitative data
Difficult to analyse and comparisons are hard to make so conclusions rely on subjective interpretations
168
Strength and weakness of quantitive date
Simple to analyse and easy comparisons and more objective so less open to bias, but data much narrower in detail
169
Strength of primary data
It is obtained from participants themselves for a particular investigation so the target the specific info needed
170
Weakness of primary data
But it requires time and effort as a whole experiment must be planned and organised
171
Secondary data strength and weakness
It is cheap and requires minimal effort as no need to conduct primary data but there may be lower quality and accuracy and the info may be outdated or incomplete and this may challenge the validity of conclusions made by the researcher
172
What is meta analysis
Combining findings from number of studies in certain topic to produce an overall conclusion
173
Descriptive statistics
Use of graphs tables and summary stats to identify trends and analyse data sets
174
What is descriptive statistics
Includes measure of central tendency, the numbers are averages which give us the most typical value in a data set
175
What are the 3 descriptive statistics
Mean median mode
176
What is the mean
Calculated by adding all the scores in a data set and diving by total number of items
177
What is median
The middle value when data scores are arranged from lowest to highest.
178
Mean strength and weakness
It is representative as it includes all the numbers but it is easily distorted by extreme values
179
Median strength and limitation
Extreme scores don’t effect it and easy to calculate, but less sensitive than mean so important extreme values are ignored
180
What is mode
Most frequently occurring number within a data set
181
Strength and limitation of mode
It is easy to calculate but not representative of the whole data set
182
When would you use mode
Asking a class their favourite dessert as you could only find a model group to work out the most popular
183
What is measures of dispersion
Based on spread of scores, how far scores vary from one and other
184
What are the 2 measures of dispersion
Range and standard deviation
185
What is range
Range is calculated by subtracting the lowest from highest value and adding 1
186
Why do you add 1 when calculating range
It is a mathematical correlation that allows that raw scores are often rounded up or down when data was recorded
187
Strength and limitation of range
It is easy to calculate but it only takes into account the 2 most extreme values and this may be unrepresentative of the data set as a whole
188
What is standard deviation
This single value tells us how far scores deviate from the mean, the larger standard deviation the larger the dispersion within a data set
189
What does a large standard deviation in an experiment suggest
Not all participants effected by the IV in the same way as the data is widely spread or that there are a few anonymous results
190
What does low standard deviation mean
Data is all close to the mean so participants responded to IV in a similar way
191
Strength and weakness of standard deviation
Much more precise way of measuring dispersion but it can be distorted by single extreme values
192
What are the 4 ways to represent data
Summary in table, bar chart, histogram, scattergram
193
What is summarising data in table
A summary table doesn’t have the raw scores from the researcher but contains values after being converted into descriptive statistics. In summary tables a summary paragraph should also be there comparing the results in the table
194
What are bar charts
Bar charts are a graph which can plot the mean values in different data sets. They are used when data is divided into categories (discrete data). In bar charts each separate bar doesn’t touch
195
What is discrete data
Data divided into categories
196
What is a histogram
Bars touch each other so data is continuous rather than discrete. X axis has equal sized intervals and y axis shows frequency within each interval
197
What is a scattergram
This graph doesn’t show differences but associations between co-variables and each point responds to both co-variables- one on x axis and one on y axis
198
What is normal distribution
When you measure something like height a bell shape curve should form that is symmetrical and this is normal distribution- a cluster of values at the mean and less frequent extreme values on either side
199
Within normal distribution where would mean median and mode lie
In the centre with the highest cluster
200
Why does normal distribution never touch 0 on x axis
As extreme scores are always theoretical possible
201
What is skewed distribution
Not all data sets form a symmetrical pattern, distributions may lean to one side or the other
202
What is a positive skew
Most of the distribution is to the left, for example in a hard test if most people got low scores and a few got high scores we would see a positive skew
203
How can different measures of central tendency’s effect positive skew
Mode would be the highest point of the peak, median would be closer to the left but more right of the mode, and mean would be closer to the right as it is effected by extreme values
204
What is a negative skew
Bulk of scores are concentrated on the right hand side so the mean is pulled to the left, median in the middle and mode on the right
205
How do you calculate percentage from two data sets
Final value/total value x100=%
206
How do you convert a percentage to a decimal
Divide the percentage by 100 and it becomes a decimal
207
What does decimal places mean
The number of digits to the right of the decimal point
208
How do you convert a decimal to a fraction
If there are 2 decimal place then you divide by 100 to get a fraction and it there are 3 decimal place you divide by 1000 to get a fraction
209
How can you make a large fraction smaller
Finding the highest common factor, which is the biggest number that divides evenly into both parts of the fraction
210
How do we express values as ratios
Each value either side of a colon, 3:1, ratio should always be simplified by finding highest common factor
211
What are estimates
You round numbers up or down to a certain significant figure in order to find the rough value
212
What is 432,765 to 2 significant figures
430,000
213
When do we use significant figures
When there are long numbers we may round it off to make an estimate
214
What is standard form
It is short hand to express very large numbers or very small numbers
215
What is standard form formula
Number between 1-10 x 10 to the power of...
216
What is the number between 1 and 10 Called in standard form and what is the power if 10 called
Mantissa and power of 10 is called exponent
217
What is order of magnitude calculations
Another kind of estimate using standard form and comparing exponents, so you can say how many times bigger or smaller a number is to another
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What does this sign mean >
Strict inequality-greater than
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What does this sign( < )means
Strict inequality-less than
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What does this sign mean >>
Inequality-much greater than
221
What does this sign (
Inequality-much less than.
222
What does this sign mean ∝
Proportional to
223
what does this mean ≈
Approximately equal-weak approximation
224
What is the concept of significance
If we find a difference in the mean value of two data sets how do we know if it is significant or not, the difference may be no more than chance so to find this out we use statistical testing
225
What is the sign test
It determines if sets of data have a significant difference. 1.look at the differences not associations 2.must use repeated measures design
3.must organise data into categories known as nominal data
226
What is nominal data
Organised data into categories
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What is probability
Refers to likelihood that a certain event will occur
228
What is the null hypothesis
States there is no difference in the data sets, if we find a statistically significant difference we can reject the null hypothesis
229
What is the accepted level of probability
0.05(5%) after this there is a significant difference between 2 data sets and rejects null hypothesis
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When may a stricter significance level be used like 0.01(1%)
In case of human cost like new drug trails or on a one off investigation
231
Why do psychologists only suggest rather than prove when finding statistically significant differences within data
They can never find statistical certainties so in the absence of proof and certainty they decided 5% is sufficient
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What is the calculate value
When statistical test done research is left with a number known as calculated value
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What must be done with the calculate value
Compare it to the critical value to determine if it’s significant or not
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What is a critical value table
A table with all the critical values
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What information do you need to use a table of critical values
1. Significance level (0.05)
2. number of participants in investigation
3. whether hypothesis is directional(one tailed) to non-directional (two tailed)
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How do you complete the sign test
1. convert data to nominal data by working out which scores went up and which went down (subtract control from experimental scores)
2. add up the plus signs and add up the minus signs
3. we take the less frequent sign and call it S
4. Then look at the critical value table and if S is equal to or less than critical value there is a statistically significant difference
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What is peer review
Before a piece of research can become public it must be peer reviewed, it involves all aspects of written investigation being scrutinised by a small group of 2 or 3 experts in a certain field, these experts should be objective and unknown by author/researcher
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What are the main aims of peer review
1. allocate research funding-can be done to decide whether to fund them or not such as in medical research
2. validate quality and relevance of research-all elements assessed for quality and accuracy
3. suggest amendments or improvements-reviewers suggest minor improvements to improve the report
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Why are peer reviews important
In establishing validity and accuracy of the research
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What is anonymity in evaluation of peer reviews
The peer must remain anonymous through to be able to give a more honest opinion, but a minority of reviewers may use this to criticise rival researchers
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What is publication bias in evaluation of peer review
It’s a natural tendency for editors to publish significant findings to increase credibility of their publication and publish positive results which could mean research not meeting this criteria is ignored which creates a false impression of currant state of psychology if researchers are being selective
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What is burying groundbreaking research in evaluation of peer review
Peer review may suppress opposition, reviewers are very critical if it opposes their own view, established scientists are likely to be reviewers and then will often pass over new and innovative research so peer reviews may slow down the rate of change
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What is meant by implication of economy in psychology
How does what we learn from our findings of psychological research influence, affect, benefit or devalue our financial prosperity
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How does attachment research into role of the father have economical implications
Research found both parents cable of looking after the child and providing to all its needs which allowed flexible working arrangements within the family. Eg, it’s norm now that if mother is the highest payed she will go back to work or couples share childcare responsibilities which means modern parents better equipped to maximise their income and contribute more effectively to the economy
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How has development of treatments for mental disorders had economic implications
Absence from work costs a lot of money and it was found that 1/3 of absences were caused by depression, stress and anxiety, treatments for mental disorders mean these people can return to work and promotes a healthy workforce. Many treatments are psychotherapeutic drugs like SSRIs or anti anxiety drugs or systematic desensitisation or CBT. This means people with mental disorders can manage their condition effectively and return to work so the economy benefits from psychological research into mental disorders
