RM: Stats Flashcards
What is meant by the term quantitative data (2)
Data that is expressed numerically (1)
This type of data can be gained from individual scores in experiments or from self reports methods and the use of closed questions(1)
What is meant by the term qualitative data (2)
Data expressed in words/descriptive data(1)
Written descriptions of thoughts feelings and opinions of ppts or answers from open questions in a questionnaire(1)
AO3 strengths of using quantitative data
Quantitative data is a more simple way 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. Whereas qualitative data is wordy and more difficult to statistically summarise and therefore comparisons within data are hard to identify
AO3 weaknesses of using quantitative data
Quantitative data lacks depth and understanding and meaning to behaviour especially when it is complex as it as it prevents participants from being able to develop their thoughts, feelings and opinions on a given subject. 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
AO3 strengths of using qualitative data
Qualitative data provides rich detail and depth, which allows participant to develop their thoughts and feelings on a given subject. This provides a greater understanding of the behaviour being studied. Whereas, quantitative data lacks depth and meaning as the data is only numerical.
AO3 weaknesses for qualitative data
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. Whereas quantitative data can be analysed statistically to provide patterns and trends which may make it easier to make objective conclusions about behaviour.
Level of measurement
Nominal - Categorical data
Ordinal - ordered/ranked highest to lowest
Interval - standardised/universal measurement. Objective measures. Numerical scales
What is meant by primary data (2)
primary data is gathered directly/first hand from the participants, and is specific to the aim of the
study.
Strengths and weakness of primary data
Strength: 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. This increases the over all internal validity of the data. Whereas secondary data might not meet the direct needs of the researcher suggesting it may be less useful
Weakness: primary data is conducted by the researcher them selves which involves time and effort to obtain the data as well as analyse the findings. Whereas secondary data is easily accessed and requires minimal effort to obtain reducing the time and cost taken to complete the research.
What is meant by secondary data(2)
Secondary data has previously been collected by a third party (another researcher or an official body), not specifically for the aim of the study, and then used by the researcher
Strengths and weaknesses for secondary data
Strength: 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 therefore is no need to collect primary data. Whereas primary data is conducted by the researcher them selves which requires effort and time to obtain the data as well as analyse the findings
Weakness: secondary data may be poor quality or have inaccuracies. It may appear to be valuable at first but could be out dated or incomplete and might not meet the direct needs of the researcher. 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.
What is meant by the term meta analysis (2)
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.(1)
Strengths and weaknesses of using meta analysis
Strength: meta analysis gather data from a number of studies which allow us to view data with much more confidence and increases the generalisability of the findings across much larger populations
Weakness: 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 meta analysis will be biased because it only represents some of the relevant data and incorrect conclusions.
What are the two ways to analyse qualitative data
Content analysis: convert qualitative data into quantitative through coding
Thematic analysis: keep as qualitative
What is content analysis (2)
A method of analysis in 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 data in a graph(2)
Why is it appropriate to use content analysis (1)
The data being analysed is qualitative data
What is meant by coding (1)
Coding is the initial process of a content analysis where qualitative data is placed into meaningful categories.
How is a content analysis carried out/ explain how you would analyse qualitative data (4)
- Read. View video or transcript
- Identify/create coding categories (example)
- Re-read the diaries/questionnaire or repeatedly listen to recording and tally every time each code appears
- Present quantitative data in a graph/table
What is thematic analysis (2)
Method of analysing qualitative data by identifying clear themes(1) enabling us to present the data in a qualitative format(1) e.g.interview,diaries, conversation
How is thematic analysis carried out (2-4)
- Watch video or listen to recordings to creat a transcript
- Read and re read transcript
- Identify coding themes - looking for words that keep being repeated
- Combine these codes to reduce the number of codes into 3 or 4 themes that are linked
- Present the data in qualitative format not quantitative
Ways to asses reliability for content analysis
Test re test - repeat content analysis tallying every time coding category occurs. Correlate the results
Inter rater reliability- two raters would read through the qualitative data separately and create coding categories together. Two raters read exactly the same content but record the occupancies separately. Then compare and correlate using stats test. Strong positive shows high reliability.
Operationalise the coding categories
What is meant by central tendency (2)
The general term for any measure of the average value in a set of data.(1) For example, the mean (1)
How can we evaluate the measures of central tendency
If its easy to calculate
Takes in to account all the data (less accurate if anomalies/extreme values)
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.
What does the standard deviation tell us
A high SD means scores are more spread around the mean so more variation, less consistency and more individual differences
A low SD 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
Writing frame for interpreting tables
The mean for condition A _______ is _____ which is higher/lower than the mean for condition B ______
which is_____.
Therefore… what does this suggest about effect on the DV? Link to the scenario.
The Standard deviations for condition A _____ is ______ which is higher/lower than the standard deviations for condition B _____ which is _____.
Therefore… what does this suggest about the consistency/spread of scores and individual differences? Link to the scenario.
Normal distribution
The curve is always symmetrical
Curve extends outwards but never touches 0
Mean median mode occupy around the same mid point
Skewed distribution
Not symmetrical
Positive skew- most of data on left of graph. Long tail on right side of the peak of data (hard test so most people scored low)
Negative skew - most data on right of the graph. Long tail is on left side of the peak of data. (Easy test so most people score high)
Writing frame for what is appropriate stats test
The appropriate statistical test is ________________________ This is because the study is a test of difference/association between ________________ and _______________________ (*They used an _______________ experimental design why – link to scenario) and the level of measurement (data) is _______________ because (link to scenario).
Writing frame for are the results significant
The critical value is _____ due to the P value being _____, a ___-tailed hypothesis and ____ppts/ df = ___ .
As a ___________ was used the calculated/observed Value (_____) must be _______ than the CV (____) to be significant. In this case it _______. Therefore, the results are ____________ and we reject the _________ hypothesis and accept the __________.
So, there is/no significant difference/association between __________________________
Define what is meant by type 1 error (2)
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.
Define what is meant by a type 2 error (2)
A Type II 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 null hypothesis and wrongly reject the alternate/experimental.
Why do psychologists use the 5% significance level
It strikes a balance between the rick of making a type 1 and type 2 error (1)
It’s a conventional significance level (1)
Sections of a scientific report
Abstract
Introduction
Method results
Discussion
Referencing
Abstract
Purpose? Allows the reader to gain overview of the study and help them decide if they want to read on
Includes Aim, hypothesis, method, results, conclusions
Introduction
Purpose? Gives background on relevant theories
Describes previous research. Outline how this will add to that research. Aims and hypotheses of research
Method
Purpose? Give detailed description of what the researcher did
Include sampling, procedure, equipment, ethics , design (SPEED)
Results
Purpose? Overall findings rather than raw data
Tables graphs stats tests
Discussion
Purpose? Discuss findings and suggest possible uses and future areas of research
Includes Summary of results, compare with other results, limitations and modifications, implications and future research
References
Purpose - give details of any other articles or oaks that are mentioned in the research
Authors name - date - title of article, journal title,volume, issue number, page number
Authors last name, first initial (date). Title of book. Place of publication: publisher
What is meant by the term peer review (2)
The process by which psychological research papers before publication, are subjected to independent scrutiny by other psychologists working in Similar field (1) who consider the research in terms of its validity, significance and originality (1)
Purpose
- to ensure quality and relevance of research, eg methodology, data analysis etc
- to ensure accuracy/validity/reliability of findings
- 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
What is a paradigm shift
Shared set of assumptions and methods
AO3 for features of science
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 a s mutated SERT gene which has been identified by objective methods such as gene mapping. This neglects a holistic approach which will take into account a variety of factors to explain behaviour such a s culture and sociology economic background. Therefore, when conducting objective research we fail to gain a full understanding of human behaviour in context.
A strength of using replicable research in psychology can lead to practical applications. If a researcher uses replicable procedures for example skinner investigated reinforcement with rats, the rats were placed in a controlled environment. This means the research can be replicated under the same conditions who itch increases the credibility of the research. This can help to develop practical applications. Therefore showing features of science is an important part of applied psychology.
Some approaches cannot be falsified.
