Research Methods 3

Question 1

What is meant by the term quantitative data?

Answer 1

This is data that is expressed numerically. 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.
The data is open to being analysed statistically and can be easily converted into graphs, charts

Question 2

Quantitative Data AO3

Answer 2

:) Quantitative data is simpler to analyse which allows comparisons to be drawn between groups of data and patterns and trends to be established. This means that it may be easier to make conclusions about behaviour give context here: what behaviour are they looking at in the scenario?). Whereas qualitative data is wordy and more difficult to statistically summarise and therefore, comparisons within data are hard to identify.

:( Quantitative data lacks depth and meaning to behaviour especially when it is complex as it prevents participants from being able to develop their thoughts, feelings and opinions on a given subject (contextualise: what subject or behaviour is being investigated in the scenario?). Therefore, quantitative data may lack vital detail which reduces the internal validity of the data. Whereas qualitative data is rich in detail, and which can provide a greater understanding of human behaviour.

Question 3

What is meant by the term qualitative data?

Answer 3

Qualitative data is expressed in words/ is descriptive data 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.

Question 4

Qualitative Data AO3

Answer 4

:) Qualitative data provides rich detail and depth, which allows participants to develop their thoughts and feelings on a given subject. This provides a greater understanding of the behaviour being studied (contextualise: what is the behaviour being studied in the scenario?). Whereas quantitative data lacks depth and meaning as the data is only numerical.

:( Qualitative data is harder to analyse as it is difficult to summarise statistically to establish patterns trends. This opens the data up to potential researcher bias as the analysis is based upon their own subjective interpretations of the data (contextualise: what is the data? What are they investigating?). Whereas quantitative data can be analysed statistically to provide patterns and trends which may make it easier to make objective conclusions about behaviour.

Question 5

Levels of Measurement

Answer 5

• based on DV

Nominal Level Data (discrete/separate data)
* data in form of categories
* e.g. hair colour, number of F/M

Ordinal Level Data (discrete)
* ordred/ranked
* does not have fixed intervals between each unit
* based on subjective opinions
* e.g. memory/IQ test
* lack of precision/ not used as part of stats test

Interval Level Data (continuous)
* standardised/ universal measure
* data based on objective measure
* interval based

Question 6

What is meant by the term primary data?

Answer 6

Primary data is gathered directly/first hand from the participants themselves, and is specific to the aim of the study. Data which is gathered by conducting an experiment, questionnaire, interview or observation would be classed as primary data.

Question 7

Primary Data AO3

Answer 7

:) Primary data is collected first hand from the participant specifically for the aim of the research which allows researchers to specifically target the information that they require and organise and experiment in a way that suits them and their aim (Contextualise: what is the aim of their research?). This increases the overall internal validity of the data. Whereas secondary data might not meet the direct needs of the researcher suggesting it may be less useful.

:( Primary data is conducted by the researcher themselves which involves time and effort to obtain the data as well as analyse the findings (contextualise: what is it that they will be analysing? E.g., what topic are they researching?). Whereas secondary data is easily accessed and requires minimal effort to obtain reducing the time and cost taken to complete the research.

Question 8

What is meant by the term secondary data?

Answer 8

Secondary data has previously been collected by a third party, not specifically for the aim of the study, and then used by the researcher. E.g. pre-existing data such as Government statistics.

Question 9

Secondary Data AO3

Answer 9

:) Secondary data is easily accessed and requires minimal effort to obtain. The researcher might find that information that he/she wants to collect already exists (context: to investigate? Refer to the scenario) therefore is no need to collect primary data. Whereas primary data is conducted by the researcher themselves which requires effort and time to obtain the data as well as analyse the findings.

:( Secondary data may be poor quality or have inaccuracies. It may appear to be valuable at first but could be outdated or incomplete and might not meet the direct needs of the researcher (context: who is investigating? Refer to the aim from the scenario). Whereas primary data is collected first hand from participants and specifically for the aim of the research which increases the overall internal validity of the research.

Question 10

What is meant by the term meta-analysis?

Answer 10

A meta-analysis is a form of research method that uses secondary data 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

Question 11

Meta Analysis AO3

Answer 11

:) Meta-analysis gather data from several studies which allows us to view data with much more confidence and increases the generalisability of the findings across much larger populations.

:( Meta-analysis may be prone to publication bias as the researcher may not select all relevant studies, choosing to leave out those studies with negative or non-significant results. Therefore, the data from the meta-analysis will be biased because it only represents some of the relevant data and incorrect conclusions are drawn.

Question 12

What are the two ways of analysing qualitative data?

Answer 12

Content and thematic analysis

Question 13

WHAT IS CONTENT ANALYSIS?

Answer 13

This is a method of analysing qualitative data by changing large amounts of qualitative data into quantitative. This is done by identifying meaningful codes that can be counted enabling us to present the data in a graph

Question 14

WHY IS IT APPROPRIATE TO USE A CONTENT ANALYSIS?

Answer 14

The data (name what the data is from the scenario given e.g. video recordings) being analysed is qualitative data.

Question 15

WHAT IS MEANT BY CODING?

Answer 15

Coding is the initial process of a content analysis where qualitative data is placed into meaningful categories.

Question 16

HOW IS A CONTENT ANALYSIS CARRIED OUT?
EXPLAIN HOW YOU WOULD ANALYSE QUALITATIVE DATA

Answer 16

• Read /view the video or transcript (link to whatever qualitative data it refers to in the scenario)
• Identify/create coding (categories) provide an example of a relevant category
• 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
• Present the quantitative data in a graph/table

Question 17

WHAT IS A THEMATIC ANALYSIS?

Answer 17

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.

Question 18

HOW IS A THEMATIC ANALYSIS CARRIED OUT?

Answer 18

• 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)
• Read & re-read transcript (familiarisation)
• Identify coding (categories) – looking for words which cropped up repeatedly.
• Combine these codes to reduce the number of codes into three or four themes that are linked to (contextualise e.g. what is the topic being studied?/ Provide an example of a potential theme)
• Present the data in qualitative format not quantitative

Question 19

Thematic Analysis AO3

Answer 19

:) It is easy to assess the reliability of the findings and conclusions because other researchers can access the materials and use the coding system, to ensure findings are consistent (inter-rater reliability).

:( Potential researcher bias as the content that confirms the researcher’s hypothesis is more likely to be identified and recorded compared to the content that contradicts their aims and expectations. This lowers the internal validity of the analysis.
Counter: However, many modern analysts (researchers) are aware of their own biases and often refer to these in their own report.

Question 20

Ways to assess reliability of content analysis (test re-test)

Answer 20

Test re-test
1. 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.
2. Then the same researcher repeats the content analysis on the same qualitative data e.g. interview, tallying every time the coding category occurs.
3. Compare the results from each content analysis
4. Then correlate the results from each content analysis using stats test.
5. A strong positive correlation of above +0.8 shows high reliability

Question 21

Ways to assess reliability of content analysis (Inter-RATER reliability )

Answer 21

Inter-RATER reliability
1. The two raters would read through the qualitative data separately and create coding categories together. INCLUDE EXAMPLE OF CATEGORY HERE
2. Two raters read exactly the same content (contextualise e.g. what is the content?) but record/tally the occurrences of the categories separately.
3. They compare the tallies from both raters
4. Which are then correlated using an appropriate stats test.
5. A strong positive correlation shows high reliability (+0.8).

Question 22

Improving reliability of content analysis

Answer 22

operationalising

Question 23

Assessing the validity of Content Analysis

Answer 23

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.

Concurrent validity:
A way of assessing validity by comparing the results of a new 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.

Question 24

Improving the validity of a content analysis

Answer 24

• Ensure coding categories are operationalised.
• Researchers are trained in how to use the coding categories

Question 25

What is meant by measures of central tendency?

Answer 25

The general term for any measure of the average value in a set of data. For example, the mean.

Question 26

Measures of central tendency

Answer 26

Mode:
Most common or popular number in set of scores and there can be more than one mode in data set
USED WITH NOMINAL DATA
-Easy to calculate Less prone to distortion by extreme (freak) values as it does not take all data in to account
-Does not take account of all scores so may be less accurate

Median:
middle score in a list of ranked-ordered scores
USED WITH ORDINAL DATA
-Easy to calculate not affected by extreme (freak) values
-Not as sensitive as mean as does not use all scores meaning less useful results

Mean
All scores added up and divided by the total number of scores
USED WITH INTERVAL DATA
-Most accurate and sensitive measure of central tendency as uses all data sets
-Affected by extreme (freak) scores as takes all scores into account which can result in misleading interpretation of results.

Question 27

What is meant by measures of dispersion?

Answer 27

This is based on the spread of scores: how far score vary from the mean or range. For example, the range or standard deviation

Question 28

Measures of Dispersion

Answer 28

Range:
spread of data
Calculated by subtracting the lowest value from the highest value
USED FOR ORDINAL DATA
-Easy to and quick to calculate as it only uses 2 pieces of the data to calculate
-Can be distorted by extreme (freak) scores, as it only takes in to account highest and lowest score

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
The smaller the calculated number, the data is clustered around the mean so more consistency and less individual differences.
USED FOR INTERVAL DATA
-Most precise/sensitive measure of dispersion as uses all scores in calculation
-More complicated and time consuming

Question 29

Interpreting tables

Answer 29

Mean running time for A (123s) higher than mean for B (117s). suggests when ppts listen to music more likely to run faster.

SD for A (9.97) lower than SD for B (14.5). suggests mean running time in A less spread around mean. less individual differences than B

Question 30

Normal distribution

Answer 30

• The curve is always symmetrical.
• The curve extends outward but never touches 0.
• The mean, median and mode all occupy around the same mid-point on the curve.

Question 31

Positive Skew

Answer 31

• 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).

Question 32

Negative Skew

Answer 32

-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).

Question 33

Plotting distributions

Answer 33

always plot the MODE first as this shows where MOST of the distribution will be, so it shows you where the ‘bell’ curve will be. Then plot the MEDIAN and then the MEAN.

Always label
frequency = y axis

Question 34

BAR CHARTS

Answer 34

• display DISCRETE/CATEGORICAL data.
• Used when data is divided into categories
• Used to compare conditions.
• THE BARS NEVER TOUCH
• score = y axis
• categories = x axis

Question 35

Histograms

Answer 35

• display continuous data
• individual scores/ frequency
• bars touch
• frequency = y axis
• score = x axis
• if 0 frequency leave gap

Question 36

Scattergraph

Answer 36

• display relationship between 2 co variables
• represents correlation
• each plot = 1 ppt but 2 scores
• 2 same scores = x^2

Question 37

Inferential/Statistical Testing

Answer 37

The appropriate statistical test is ________________________ This is because the study is a test of difference/correlation between ________________ and _______________________ (*They used an _______________ experimental design why – link to scenario) and the level of measurement (data) is _______________ because (link)

Question 38

Interpreting a Statistical Test

Answer 38

1) is it one or two tailed?
2) how many ppts?
3) what sig level used?
4) what is observed/calc value?
5) what is critical value from table
6) Interpret whether calc value should be higher/lower than critical
- calc sig= accept alternative hypothesis, reject null

Question 39

Sign Test uses

Answer 39

• testing difference
• with nominal data
• repeated/matched pairs

Question 40

How to complete sign test

Answer 40

1. convert data to nominal. subtract water score from energy drink. draw sign of difference row and record of difference is +,-,=
2. add up +,-
   minus number of = from number of ppts
3. take number of less frequent sign (+,-) which equals s (calc val)
4. complete stats test as usual

Question 41

Define what is meant by a Type I Error

Answer 41

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. So they wrongly accept ALTERNATIVE hypothesis and wrongly reject the null.

Question 42

Define what is meant by a Type II Error

Answer 42

A Type II error is when the researcher has used a stringent p value. They think that their results are not significant when they could be significant. So they wrongly accept the NULL hypothesis and wrongly reject the alternate

Question 43

What is the difference between Type 1 and 2 errors?

Answer 43

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

Question 44

Why do psychologists use the 5% significance level?

Answer 44

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

Question 45

How to check for a type 1 error

Answer 45

compare the calculated value to a critical value from a more stringent p value. If the results are still significant then the researcher has not made a type 1 error. If the results are now not significant, then there is a chance of a type 1 error.

Question 46

How to check for a type 2 error

Answer 46

compare the calculated value to a critical value from a more lenient p value (p0.05). If the results are still not significant then the researcher has not made a type 2 error. If the results are now significant, then there is a chance of a type 2 error.

Question 47

Checking for type 1/2 error writing frame

Answer 47

The researcher can be confident that they did not make a type 1 error because when using a more stringent p value of <0.01, for a one tailed test, where N= 30, the calculated value of 0.52 is greater than the critical value of 0.425 and is STILL significant. Therefore the researcher’s did NOT wrongfully accept the ALTERNATIVE HYPOTHESIS and can be more than 99% sure their correlation is significant and less than 1% chance that the results are due to error.

Question 48

Designing a Study

Answer 48

Writing consent forms:
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.

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

Writing a debrief:
Written in past tense
* 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

Question 49

Reporting Psychological Investigations

Answer 49

Section 1: Abstract
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.
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.

Section 2: Introduction
What goes 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.
What is the purpose of an introduction? Gives background on relevant theories and studies to explain how aims and hypothesis developed.

Section 3: Method
What is the purpose of an introduction? This section gives a detailed description of what the researcher did - this should provide enough detail for replication of the study.
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.

Section 4: Results
What is the purpose of the results section? To present the overall summary of the findings to the reader rather than reviewing the raw data.
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.

Section 5: Discussion
What is the purpose of the discussion section? This section will discuss the findings and suggest possible uses and future areas of research.
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 follow up studies that could be conducted.

Question 50

Referencing

Answer 50

Purpose - To give details of any other articles or books that are mentioned in the research. Prevent plagiarism

Referencing an article = Author name - date - title of article, journal title, volume, issue number, page numbers.

Referencing a book = Author’s last name, followed by first initial (date). Title of book. place of publication: publisher

Question 51

What is meant by the term peer review?

Answer 51

Peer review is the process by which psychological research papers, before publication, are subjected to independent scrutiny by other psychologists working in a similar field who consider the research in terms of its validity, significance and originality

Question 52

The peer review process

Answer 52

• 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.

Question 53

The peer review purpose

Answer 53

• 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 others increases the likelihood that weaknesses 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 prevent the dissemination of irrelevant findings, unwarranted claims, unacceptable interpretations, personal views and deliberate fraud. (retains integrity)
• Determines whether research should receive funding

Question 54

PROBLEMS associated with the peer review system/ EVALUATE/ DISCUSS the role of peer review

Answer 54

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 –
   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.

Question 55

Features of Science

Answer 55

1. Theory Construction: A theory is an explanation for describing a phenomenon (event). Which is based on observations about the world. Theories help us to understand and predict things around us.
   Theory construction allows us to make a prediction about behaviour and then create a hypothesis and test it empirically. We can then use this to support/refine our original theory and progress through the scientific cycle of enquiry.
2. Hypothesis Testing: 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.
3. Empirical Methods: Information is gained through direct observation or experiment rather than opinion.
4. Paradigm: What is a paradigm?
   Where scientific disciplines have a shared set of assumptions and methods
   Psychology lacks a universally accepted paradigm and is best seen as a ‘pre-science’. Psychologists argue that psychology has a number of different paradigms e.g behaviourism, cognitive approach etc.
   Paradigm shift = when there is a revolutionary change in scientific assumptions where the old paradigm is replaced with a new one. An example of a paradigm shift could be the move away from behavioural psychology to cognitive psychology which happened in the early 1960’s.
5. Replicability: Repeat the research using the same methods/procedure to check for similar findings 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. 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. This increases confidence in results
6. Objectivity: Where research is not affected by the expectations of the researcher. Using factual measurements and measurable data or controlled condition to reduce subjectivity.
7. Falsification: The ability to be able to prove a theory wrong. This means a testable hypothesis should include an alternative hypothesis and a NULL hypothesis.

Question 56

Features of science AO3

Answer 56

One limitation of conducting objective research when establishing Psychology as a science is that it can lead to a reductionist viewpoint. This is often a problem as we are simplifying behaviour down into simple basic units, for example simplifying OCD to simple basic units such as a mutated SERT gene which has been identified by objective methods such as gene mapping. This neglecting a holistic approach which will take into account a variety of factors to explain behaviour such as culture and socio-economic background. Therefore, when conducting objective research we fail to gain a full understanding of human behaviour in context.

A strength of using replicable (change to another feature you have outlined in AO1) research in Psychology can lead to practical applications. If a researcher uses replicable procedures for example when Skinner investigated reinforcement with rats, the rats were placed in a controlled environment. This means the research can be replicated under the same conditions which increases the credibility of the research. This can help to develop practical applications such as token economy systems for people suffering with Schizophrenia to help manage their symptoms. Therefore showing features of a science is an important part of applied Psychology.

One limitation when considering if Psychology follows all features of a science is that some approaches/theories cannot be falsified. For example, Freud in the Psychodynamic approach created the idea of 5 psychosexual stages that children must progress through to have a ‘normal development’. However, this theory cannot be falsified as there is no possible way to test if this idea is true or false due to the unscientific nature of studying the unconscious. Therefore not all areas of Psychology can be considered a science due to their unscientific methods, lowering the credibility of Psychology as a science.