statistics Flashcards
1
Q
What are the types of data and what can they be broken down into
A
Quantitative - numerical - levels of measurement
- > ordinal, nominal & interval
Qualitative - language
Primary -
Collected specifically for researcher
Secondary
Collected by someone other than the person who is conducting the research -> meta analysis
2
Q
What is meant by the term quantitative data (2)
A
This is data that is expressed numerically (1).
This type of data can be gained from individual scores in experiments, such as the number of words recalled or the number of seconds it takes to complete a task or from self report methods and the use of closed questions (2)
The data is open to being analysed statistically and can be easily converted into graphs, charts etc.
3
Q
What is meant by the term qualitative data (2)
A
Qualitative data is expressed in words/ is descriptive data (1)
and may take the form a written description of the thoughts, feelings and opinions of participants such as from a notes recorded within an interview, a diary entry or answers from open questions in a questionnaire (2)
Qualitative methods are concerned with the interpretation of language.
4
Q
What is discrete data
A
Information/findings that can be categorised into groups, the data can only appear in one category. It can’t be sub-divided i.e. it needs to be whole numbers e.g. 25/30 on test.
5
Q
What is continuous data
A
Data that can be measured using scientific tools e.g. height, weight, time.
6
Q
What are the 3 types of quantitative data
A
Nominal - discrete
Ordinal - discrete
Interval - continuous
7
Q
What is nominal data
A
Data in the form of categories
For example: you can count how many boys and girls are in your year group - male and female are the categories and you take a count of how many in each group
Other examples: hair colour, people’s favourite football team.
8
Q
What is ordinal data
A
Ordinal data is ordered/ranked in some way e.g. from highest to lowest
e.g. 19, 2nd, 3rd
Ordinal data does not have equal/fixed intervals between each unit
E.g. if you were asked to rate your enjoyment of Psychology on a scale of 1-10, what is the difference in the amount of enjoyment between 6 and 7?
Data based on subjective opinions are an example of ordinal level data.
E.g. rate how much you enjoy psychology out of 10 (1 being ‘I do not like psychology, 10 being “ love psychology. If two people say ‘8’ they may have different opinions of what an 8 is.
Another example of ordinal data would be the amount of items recalled in a a memory test or score on an IQ test.
For these reasons, ordinal data is often known as ‘unsafe’ data due to its lack of precision and is not used as part of statistical testing. Instead raw scores are converted to ranks (15, 2”, 3”°) and it is the ranks, not the scores, that used in the calculation for the statistical test.
9
Q
What are the key features of ordinal data
A
Ordered / ranked
Does not have equal/ fixed intervals
Subjective opinions
10
Q
What is interval data
A
Data is a STANDARDISED/UNIVERSAL/OFFICIAL measurement.
Data based on objective (factual) measures e.g. time in seconds, height in centre metres
Interval is based on numerical scales that include units of equal, precisely defined size.
11
Q
What is meant by the term secondary data (2)
A
Secondary data has previously been collected by a third party (1)
(another researcher or an official body), not specifically for the aim of the study, and then used by the researcher (2).
E.g. preexisting data such as Government statistics.
12
Q
What is meant by the term meta-analysis (2)
A
A meta-analysis is a form of research method that uses secondary data (1) as it gains data from a large number of studies, which have investigated the same research questions and methods of research. It then combines this information from all the studies to make conclusions about behaviour (2)
13
Q
Breakdown of analysing data
A
Quantitative -> inferential statistics -> descriptive statistics
Descriptive statistics -> central tendencies -> mean, median, mode
Descriptive statistics -> measures of dispersion -> range, standard deviation
Qualitative -> content analysis -> thematic analysis
Content analysis -> coding
Thematic analysis -> emergent themes
14
Q
What are the two ways of analysing data
A
Content analysis
Thematic analysis
15
Q
What does content analysis observe
A
Usually makes observations indirectly through books, films, advertisements, interview transcripts and photographs.
16
Q
What is content analysis (2)
A
This is a method of analysing qualitative data by changing large amounts of qualitative data into quantitative (1)
This is done by identifying meaningful codes that can be counted enabling us to present the data in a graph (2)
17
Q
Why is it appropriate to use content analysis (1)
A
The data (name what the data is from the scenario given e.g. video recordings) being analysed is qualitative data. (1)
18
Q
What is meant by coding (1)
A
Coding is the initial process of a content analysis where qualitative data is placed into meaningful categories.
19
Q
How is content analysis carried out/ explain how you would analyse qualitative data (4)
A
Read /view the video or transcript (link to whatever qualitative data it refers to in the scenario) (1)
Identify/create coding (categories) provide an example of a relevant category (1)
Re-read the diaries/ questionnaire or repeatedly listen to sections of the recording (choose appropriate one in relation to the scenario) and tally every time each code appears (1)
Present the quantitative data in a graph/table (1)
20
Q
What is thematic analysis (2)
A
This is a method of analysing qualitative data by identifying emergent (keep cropping up) themes enabling us to present the data in a qualitative format.
E.g. Interview recordings, presentation/conversation, diary entries, newspapers, texts, social media, radio and tv ads.
21
Q
How is a thematic analysis carried out (2-4)
A
If the data in the scenario is not already a transcript: watch the video or listen to recordings to create a transcript of (contextualise e.g. refer to specific data in scenario such as interview about aggressive behaviour) * (1)
Read & re-read transcript (familiarisation)
Identify coding (categories) - looking for words which cropped up repeatedly. (1)
Combine these codes to reduce the number of codes into three or four themes that are linked to (contextualis e.g. what is the topic being studied?/ Provide an example of a potential theme) (1)
Present the data in qualitative format not quantitative. (1)
22
Q
Ways to assess reliability of content analysis
A
Test re-test
Inter-rated reliability
23
Q
test re-test
A
- The researcher completes the content analysis by creating a series of coding categories, (provide an example category that links to scenario) and tallying every time it occurs within the qualitative data.
- Then the same researcher repeats the content analysis on the same qualitative data e.g. interview, tallying every time the coding category occurs.
- Compare the results from each content analysis
- Then correlate the results from each content analysis using stats test.
- A strong positive correlation of above +0.8 shows high reliability
24
Q
Inter-rather reliability
A
- The two raters would read through the qualitative data seperately and create coding categories together. INCLUDEEXAMPLE OF CATEGORY HERE
- Two raters read exactly the same content (contextualise e.g. what is the content? but record/tally the occurrences of the categories separately.
- They(compare the tallies from both raters
- Which are then correlated using an appropriate stats test.
- A strong positive correlation shows high reliability (+0.8).
25
Define operationalising in terms of content analysis
Operationalising means to be specific and clear when defining coding categories (1 mark to make the codes more measurable (1 mark)
26
Why is operationalising important in terms of content analysis
If coding categories are vague (not operationalised) then it would not be possible to repeat the research to check for consistent results.
Operationalising increases reliability as if the coding categories are operationalised the other researchers can repeat the research in the same way to check for consistent results.
27
How do you assess the validity of content analysis
Face validity
Concurrent validity
28
How do you conduct face validity
The quickest most superficial way of assessing for validity. This involves an independent psychologist in the same field seeing if a coding category (contextualise: give an example looks like it measures what it claims to measure (contextualise: refer to scenario, what are they measuring?) at first sight/face value. If they say YES the content analysis is valid.
29
How do you conduct concurrent validity
A way of assessing validity by comparing the results of a new yu content analysis (contextualise here: what is the content analysis investigating?) with the results from another similar pre-existing content analysis which has already been established for its validity. If the results from both are similar then we can assume the test is valid. The correlation of two sets of coding recordings/ results gained from an appropriate stats test should exceed +0.8.
30
How do you improve the validity of a content analysis
Ensure coding categories are operationalised.
Researchers are trained in how to use the coding categories
31
Break down analysing quantitate data
Descriptive statistics -> measures of central tendency -> mean, median, mode
Descriptive statistics-> measures of dispersion -> range, standard deviation
32
What is meant by measures of central tendency (2)
The general term for any measure of the average value in a set of data. For example, the mean.
33
Describe the mode
Most common or popular number in set of scores and there can be more than one mode in data set
USED WITH NOMINAL
34
What is the mode used with
Nominal data
35
Describe median
Central/middle score in a list of ranked-ordered scores
If there are two central scores, add together and divide by 2.
USED WITH ORDINAL DATA
36
What is the median used with
Ordinal data
37
What is the mean used with
Used with internal data
38
Describe mean
All scores added up and divided by the total number of scores (mathematical average)
OUSED WITH INTERVAL DATA
39
What is meant by measures of dispersion (2)
This is based on the spread of scores: how far score vary from the mean or range. For example, the range or standard deviation.
40
What are the two types of dispersion
Range
Standard deviation
41
What is the range used for
Ordinal data
42
What is the standard deviation used for
Interval data
43
Describe the range
The range is the spread of data from the smallest to the largest.
Calculated by subtracting the lowest value from the highest value and adding 1
USED FOR ORDINAL DATA
44
Describe the standard deviation
Measure of spread around the mean.
The higher the SD the more the data is spread around the mean.
The larger the calculated number, the data is spread around the mean, less consistency and more individual differences (suggesting that not all participants were affected by the IV in the same way).
The smaller the calculated number, the data is clustered around the mean so more consistency and less individual differences.
USED FOR INTERVAL DATA
45
What does the standard deviation tell us
A HIGH SD means scores are more spread around the an so more variation in scores
The scores are less consistent and there are more individual differences in the results
A LOW standard deviation (closer to 0) means scores are less spread around the mean so there are less variation in scores
The scores are more consistent and there are less Individual differences in the results.
46
What does the mean tell us
Provides a good indication of the average/typical score participants gain
Generally the higher the mean that is gained then the greater the score/effect (although this is not always the case! Do double check in the scenario what a high score will mean)
47
What is the writing frame for the sd/ mean questions
STATE WHICH IS HIGHER/LOWER, STATE WHAT THIS SUGGESTS.
The mean for condition A (context) is
which is higher/lower than the mean for condition B (context)
which is
Therefore... what does this suggest about the effect on the DV? Link to the scenario. (MUST INCLUDE)
The Standard deviations for condition A (context) is
which is higher/lower than the standard deviations for condition B (context)
which is
Therefore... what does this suggest about the spread of SCORES (context DV) and individual differences? Link to the scenario. (MUST INCLUDE)
48
What are the two types of skewed distribution
Positive skew
Negative skew
49
What are the features of a normal distribution & give an example
The curve is always symmetrical
The curve extends outwards but never touches 0
The mean, median and mode all occupy around the same mid- point on the curve
This may be likely to be seen in a height distribution
Most people would occupy around the same mid-point, with few people at the extreme ends
50
What is a skewed distribution
This is a spread of data that is not symmetrical - the data clusters at one end.
51
Using an example, explain the difference between a positive and negative skew (3)
Positive Skew - most of the data is concentrated on the left of the graph, the long tail is on the right side of the peak of data.
This could be seen in a hard test (as most people score low).
Negative Skew - most of the data is concentrated on the right of the graph, the long tail is on the left side of the peak of data.
This could be seen in an easy test (as most people score high).
52
What are the three types of graphical representation
Bar charts
Histograms
Scattergraphs
53
What data do bar charts have and do the bars touch
Discrete/ categorical data
Bars do not touch
54
What data do histograms have and do they touch
Continuous data
Bars do touch
55
What data do Scattergraphs have
Relationship between 2 co-variables
56
What does wash plot represent on a Scattergraph
One ppt but 2 scores
57
State the characteristics of a bar chart
Used to display DISCRETE/CATEGORICAL data
Used when data is divided into categories. These categories will appear as words rather than numbers.
The categories will occupy the horizontal x axis
The frequency or amount (e.g. mean number of words recalled) of each category is plotted on the vertical y axis
Used to compare conditions.
THE BARS NEVER TOUCH (each other or the y axis) to show that we are dealing with separate conditions (discrete data)
58
State the characteristics of a histogram
Used to display CONTINUOUS data (data which is NOT DISCRETE/ in separate categories) OR data where each participant has an individual
score.
Histograms represent FREQUENCIES
The scores, which are made up of equal szied intervals e.g. 0-10, 11-20, etc, will always be represented on the horizontal × axis - this will also then create equal widths in the bars
The frequency (just means number of) of the number of people that had a certain mark within each interval will always be represented on the vertical y axis
If there was a zero frequency for one of the intervals, the interval would remain but without a bar.
THE BARS SHOULD ALWAYS BE TOUCHING each other and the vertical y axis which shows the data is continuous rather than separate categories.
Worked example:
59
State the characteristics of a scattergraph
Used to display a RELATIONSHIP between two co-variables
Scattergrams represent correlations
Each plot on the graph represents ONE ppt but TWO scores (one score from each co-variable)
One co-variable will go along the vertical y axis and the other will go along the horizontal x axis. It does not matter which way round you do this.
60
What is inferential/ statistical testing
The no ric table
61
What is the no ric saying
No Ric Students Come College When Miss Says Ric U Part-timer
62
What is the writing frame for inferential/statistical testing (7)
For a difference & an association
The appropriate statistical test is
This is because the study is a test of difference/association between
(*They used an ______ experimental design, why - link to scenario)
and the level of measurement (data) is because (link to scenario).
The appropriate statistical test is ______
This is because the study is an association between _____ and ____
The researchers are looking at a correlation between _____ and _____
The level of measurement is ____
Because (contextualise the DV of the experiment)
63
What are the things to look for when being asked to interpret a statistical test
One tailed or two tailed hypothesis
Number of ppts or degree of freedom (df)
Level of significance
Identify the observed/ calculated value
The critical value - from the table
Interpret the findings using the statement, writing frame
64
What are the statistical tests that go under - calculated value must be equal to or less than the critical value
Sign test
Mann-Whitney
Wilcoxon’s
65
What are the statistical tests that go under - calculated value must be equal to or more than the critical value
Chi squared
Spearmen’s rho
Unrelated t-test
Related t-test
Pearson’s rho
66
What is the writing frame for interpreting a statistical test
The critical value is ____ due to the p value being ______ , a ___ - tailed hypothesis and where N/df = ______
The calculated/ observer value (____) must be _____ than the CV (_____) to be significant. In this case the results are _____ and we reject the _____ hypothesis and accept _____
So, there is/ no significant difference/ association between _______
67
What is a sign test used for
Testing difference (experiment)
With nominal data
When the experimenter used repeated measures
68
What’re are the steps for a sign test
1- make the pluses, the equal & the minuses
2 - if any equals take them away from the number of ppts
3 - take the least frequent sign - calculated value
Use ppts, the calculated value & significant and complete the statement results
69
Define what is meant by a type 1 error
A Type I error is when the researcher has used a lenient P value.
The researcher thinks the results are significant when they are actually due to chance/error. So they wrongly accept ALTERNATIVE/ EXPERIMENTAL hypothesis and wrongly reject the null.
70
Define what is meant by a type 2 error (2)
A Type Il error is when the researcher has used a stringent p value. They think that their results are not significant (due to chance/error) when they could be significant.
So they wrongly accept the NULypothesis and wrongly reject the alternate / experimental:
71
What is the difference between type 1 and type 2 error
The difference is that in a type 1 error the null hypothesis is rejected when it is TRUE whereas in a type 2 error the null hypothesis is accepted when it is FALSE
72
Why do psychologists use the 5% significance level
Psychologists use a P<0.05 as it strikes a balance between the risk of making the type 1 and 2 error.
It's a conventional significance level
73
How do I check for a type 1 error
Go to a more a more strict significance level and check the calculated value against the critical value.
If the results are still significant then it is NOT a type 1 error. You must then comment on the % of confidence you now have in your results e.g. if still significant at p<0.01 then they are MORE THAN 99% sure there is a sig.
Difference/correlation and LESS THAN 1% is due to chance/error.
If the results are NOT significant then there is a risk that a type 1 error has been made.
74
How do I check for a type 2 error
Go to a more lenient significance level and check the calculated value against the critical value.
If the results are still not significant then NO type 2 error has been made.
If the results are NOW significant at the more lenient level then there is a risk that a type 2 error has been made.
You must then comment on the % of confidence you now have in your results e.g. if still significant at p<0.01 then they are MORE THAN 99% sure there is a sig. difference/correlation and LESS THAN 1% is due to chance/error.
75
Things to consider for the experiment (design a study 12)
IV and DV
Extraneous variables and how they
will be controlled
Sampling methods and who your participants will be
Potential ethical issues
Experimental design: Independent groups, repeated measures, matched pairs?
Controls related to your design, e.g. if you choose to do a repeated measures you MUST include counterbalancing as a control or a time delay between your tasks
Materials you will need
Step by Step guide of what the participants are going to do, including how long they will do it for.
Will there be two different tasks for different groups?
Appropriate descriptive
76
Things to consider for the observation (design a study 12)
Type of observation?
Controlled or Natural, Overt, Covert, participant or non-participant?
Operationalised behavioural categories
How will you sample the behaviour? Time or event sampling?
Will you record the observation on a video recorder?
Will you have more than one observer to increase inter-observer reliability?
77
Things to consider for the self-report (interview or questionnaire) (design a study 12)
Who will your participants be?
If it's a questionnaire, how will you distribute it? Will you be present when pts are completing it?
What types of questions will you use and why?
Give an example of one of the questions. If there is a rating scale make sure you state what a high and low number means.
If an interview, how will you record the data? Will you write it down or film the interview?
Will the interview be structured or unstructured?
78
Writing a consent
MUST be written in future tense e.g. if you choose to take part, you will...
Thank the participants for considering taking part
The aim of the research including an outline of the task and how much of their time it will take (TIME AND TASK!) be specific.
Explain the ethical issues which have been accounted for especially the right to
withdraw & confidentiality
Remind them they can ask any questions
Include space where they can sign to show they consent.
79
Writing standardised instructions
MUST be written in future tense e.g. you will be required to...
Formal but polite
You will be required to do this....step by step of what they will do...
How long they will take to complete the task
What they should do when they have finished
Do they have any questions?
Ask if the participant have any questions
80
Writing a debrief
Thank the participants for taking part in the research
Include the aim of the research (true nature of the study)
Explain why it was important to deceive them (if that's the case)
If it was an independent groups design - the ppts must be told of the condition that they did not take part in.
Explain the relevant ethical issues which have been accounted for (right to withdraw
data, their data will be kept confidential)
Reassure them their behaviour is normal, offer after care (if needed)
Ask participants if they have questions
81
What are the 5 sections of a scientific report
1. Abstract
2. Introduction
3. Method results
4. Discussion
5. Referencing
82
What is the purpose of an abstract
This allows the reader e.g. a student or another psychologist to gain an overview of the study and help them decide if they want to read on.
83
What goes in an abstract
A summary of the study covering the aims, hypotheses, method, results and conclusions. It is the first part of the Psychology report. Abstracts are reported in a single paragraph of 150-250 words.
84
What does in an introduction
It begins by describing previous research in the area is described. Links are made with previous research or it is made clear how the current research will add to the previous research. The introduction ends with the researcher stating the aims and hypotheses of the research.
85
What is the purpose of an introduction
Gives background on relevant theories and studies to explain how aims and hypothesis developed
86
What is the purpose of a method
This section gives a detailed description of what the researcher did - this should provide enough detail for replication of the study.
87
What goes in a method section
S- Sampling method, how many took part and information about Ppts, ages, occupations, gender etc.
P - Procedure - written like a recipe with the exact order of events including any standardised instructions.
E - Equipment details of any materials and apparatus used.
E - Ethics - significant ethical issues may be mentioned as well as how they were dealt with.
D- Design e.g./ repeated measures' or 'covert observation'. Design decisions should be justified.
88
What is the purpose of the results section
To present the overal summary of the findines to the reader rather than reviewing the raw data.
89
What goes in a results section
Descriptive statistics - tables and graphs showing frequencies and measures of central tendency and dispersion.
inferential statistics - stat tests are reported and calculated values and significance levels are detailed.
For any qualitative research - categories and themes are described along with examples.
90
What is the purpose of a discussion section
This section will discuss the findings and Last possible uses and future areas of research
91
What goes in a discussion section
Summary of results - written description of the statistical results focusing on whether the hypothesis was supported. The results from tables and graphs are discussed along with any atypical data.
Compare with other results - Explain whether the findings support the results of the
studies in the introduction
Limitations and modifications -evaluate the present research methods and procedures and explain how this could be improved if repeated
Implications & future research - explain how the findings could be used and any potential fo Cv up studies that could be conducted.
92
What is the purpose of references
To give details of any other articles or books that are mentioned in the research.
93
How do you reference an article
Author name - date - title of article, journal title, volume, issue number, page numbers.
94
How do you reference a book
Author's last name, followed by first initial (date). Title of book. place of publication: publisher
95
In 1992, a book about human relationships was published in London. The book was written by Steve Duck from the University of lowa. The title was 'Human Relationships'. The book was published by Sage.
A researcher needs to modify the above information to include Duck's book in the references section of a scientific report.
Write the full reference for this book as it should appear in the reference section of the researcher's report.
(2 marks)
Duck, S. (1992). Human Relationships. London:Sage
96
What is meant by peer review (2)
Peer review is the process by which psychological research papers, before publication, are subjected to independent scrutiny by other poychologists working in a similar field (1)
who consider the research in terms of its validity, significance, and originality. (2)
97
What is the purpose of peer review
Peer review acts as a 'gatekeeper' to filter out flawed or unscientific research.
98
What is the process of the peer review process
Psychological research papers, before publication, are subjected to independent scrutiny by other psychologists working in a similar field to decide if it should be published.
Work is considered in terms of its validity, significance and originality and possible improvements may be suggested.
Assessment of the appropropriateness of the methods and designs used.
The reviewer can: Accept the research as it is, accept the research if improvements are made, reject the research.
The review can be open (both researcher and reviewer named), single blind (only the researcher named and so reviewer is anonymous) or double blind (where both researcher and reviewer are anonymous.
The editor of the journal will make the final decision on whether to publish the research, based on the comments of the reviewer.
99
What is the purpose (role) in the scientific process of peer review
To ensure quality and relevance of research, eg methodology, data analysis etc and accuracy/validity and reliability of findings. This is because it is difficult for authors and researchers to spot every mistake in a piece of work. Showing the work to other increases the likelihood that weakness will be addressed
This process ensures that published research can be taken seriously because it has been independently scrutinised by fellow researchers
It helps to preveht the dissemination of irrelevant findings, unwarranted claims, unacceptable interpretations, personal views and deliberate fraud. (retains integrity)
Determines whether research should receive funding
100
Problems associated with the peer review system (6)
1. FRAUD. In a small number of cases, peer review has failed to identify fraudulent research before publication.
2. VALUES. Although psychologists try to be objective, it is generally accepted that it is impossible to separate from your personal, cultural or political views. Thus if research findings agree with the reviewers own beliefs then they are more likely to be accepted as objective research.
3. BIAS: There are a number of ways in which a review of research may be biased, e.g
Institution bias - the tendency to favour research which comes from prestigious universities. Gender bias
ー
the tendency to favour male researchers and bias towards positive findings.
4. ANONYMITY: It is usual practice that the peer' doing the reviewing remains anonymous throughout the process to produce a more honest appraisal. However, due to direct competition for limited research funding a minority of reviewers may use their anonymity as a way of criticising rival reviewers. Therefore some journals use open reviewing where the names of the reviewers are made public.
101
What are the 8 features of science
Theory construction
Hypothesis testing
Empirical methods
Paradigm
Paradigm shift
Replicability
Objectivity
Falsification
102
Define theory construction (4)
A theory is an explanation for describing a phenomenon
(event). Which is based on observations about the world. (1) Theories help us to
understand and predict things around us. (2)
Theory construction allows us to make a prediction about behaviour and then create hupighess a hypothesis and test it empiricaly. (3) We can then use this to support/refine our original theory and progress through the scientific cycle of enquiry. (4)
103
Define hypothesis testing (1)
All hypotheses should be testable & falsifiable, in other words being able to test if it is true or false. A testable hypothesis allows us to refine theories through acceptance or rejection of an experimental hypothesis or a null hypothesis. (1)
104
Define empirical methods (1)
Information is gained through direct observation or experiment rather than opinion. (1)
105
Define paradigm (1)
Where scientific disciplines have a shared set of assumptions and methods (1)
Psychology lacks a universally accepted paradigm (there are too many internal disagreements and conflicting approaches) and is best seen as a 'pre-science'. Psychologists argue that psychology has a number of different paradigms e.g behaviourism, cognitive approach etc.
106
Define paradigm shift (2)
when there is a revolutionary change in scientific assumptions where the old paradigm is replaced with a new one. (1)
An example of a paradigm shift could be the move away from behavioural psychology to cognitive psychology which happened in the early 1960's. (2)
107
Define replicability (5)
Repeat the research using the same methods/ procedure (1)
to check for similar findings (2)
Procedures must be operationalised and detailed in order to do this. This is an important aspect of science because repeating research allows us to check findings are externally valid. (3)
This may sound like reliability but rather than using the same sample, psychologists test a different group of people to see if similar behaviour is observed. This helps to generalise the theory to a wider population. (4)
This increases confidence in results (5)
108
Define objectivity (2)
Where research is not affected by the expectations of the researcher (1).
Using factual measurements and measurable data or controlled condition to reduce subjectivity. (2)
109
Define falsification (1)
The ability to be able to prove a theory wrong. (1)
This means a testable hypothesis should include an alternative hypothesis and a NULL hypothesis.
110
Implication of psychological research for the economy : psychology, mental health & the economy A01
Absence from work costs the economy over £15 billion a year.
A third of all absences are due to mild and moderate mental health conditions e.g. stress, depression
Psychological research into effective treatments can have a huge benefit for the economy.
E.g. research has found combining drug therapy with psychological therapies such as CBT is more effective for treating depression than drug therapy alone.
111
Implication of psychological research for the economy : psychology, mental health & the economy A03
Using a combination of therapies can then mean individuals can manage their condition effectively and return to work, saving the economy money.
This will in the long run reduce the strain on the NHS as less indivduals will be admitted for treatment, if the combined treatment is successful.
However, combined treatment is more expensive reducing the financial benefit for the economy - especially if a large number of people are needing treatment.
112
Implication of psychological research for the economy : psychology, attachment & the economy A01
Research into multiple attachments has shifted the importance of the mother on child rearing and development to more shared parenting, increasing the importance and involvement of the father in child rearing.
Research has found both parents are equally capable of providing the emotional support necessary for a child to have healthy psychological development.
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Implication of psychological research for the economy : psychology, attachment & the economy A03
This has effected the economy in a number of ways:
Fathers are now entitled to shared paternity leave which costs the economy as it is government funded. Also costs employers as they may have to hire someone else to take on that workload whist the father is on leave.
However, due to flexible working hours within the family it is the norm in lots of household that both parents earn money and maximise their income to contribute to the economy by working and paying taxes.
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Implication of psychological research for the economy : psychology, social influence research & the economy A01
Research into how people conform can be used to influence the economy.
For exampie, informational social infuence research has found that
individuals have the desire to be right and therefore, presenting the information/ statistics behind hotel guests towel washing/use and the water waste, significantly reduced the hotel guests towel consumption.
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Implication of psychological research for the economy : psychology, social influence research & the economy A03
This can benefit the economy as it can change individual's behaviour such as excess water use, this benefits the environment, which in turn benefits the economy because less money will be used to protect the environment from excess water use.
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Implication of psychological research for the economy : psychology, eyewitness testimony& the economy A01
Research into the influence of leading questions on eye witness testimony has an influence upon the economy.
Lofts and Palmer found that leading questions can alter someone's perception of an event, this lead to the development of the cognitive interview which does not use leading questions and has been found to improve the accuracy of an individual's eve witness testimony.
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Implication of psychological research for the economy : psychology, eyewitness testimony& the economy A03
This can benefit the economy because it means the police will spend less resources looking for the wrong suspects as EWT should be more accurate.
Also means that it will increase the likelihood of the correct person being convicted of the crime, therefore, not wasting the economy's money on inaccurate convictions.
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What is meant by primary data (2)
