Ethical Issues and Sampling & Data Collection (Sampling Methods…
Ethical Issues and Sampling & Data Collection
Respect: Valuing dignity and worth of individuals.
participants give their permission to take part in study and be aware of aims. When including people under 16, parents/guardians must give consent too.
Right to withdraw-
Pp's aware they can withdraw from research at any time (regardless of payment).
Pp's in psyychological research right to expect info provided will be treated confidentially and anonymised.
Right to privacy-
Research shouldn't invade privacy.
Unless pp gives consent to being observed, only take part in public situations where pp normally be expected to be observed by strangers.
Competence: Valuing continuing development as psychologist and maintenance of high standards of work. Functioning optimally and within limits of own knowledge, skill, training, education and experience.
Responsibility: Valuing responsibities of being a psychologist- pp's, public and profession and science of psychology.
Protection of participants from harm-
Investigators protect pp's from physical/psychological harm during investigation. Risk of harm should be no greater than ordinary life.
Explaining true nature of study, providing further support if necessary. Pp's shouldn't leave the research situation feeling worried/distressed.
Integrity: Valuing honesty, accuracy, clarity and fairness in interactions and seeking to promote scientific and professional work as a psychologist.
Deceiving pp's should be avoided. If it's used, they should be fully debriefed at the end of the study.
The participants who take part in the study.
Whole group the researcher wants to generalise the results to.
Sampling method most commonly used. Consiting of taking sample of people who are available at the time the study is being carried out and fit criteria.
Strengths- Quicker, easier and more convenient to carry out than other methods because pp's all available in same location as researcher.
Weaknesses- Not representative of target population because you're only using small part of target population who might share characteristics.
(volunteer) pp's take part because they volunteered; usually in response to an advert.
Strengths- Relatively easy to carry out because pp's come to you so motivated to do so.
Seen as more ethical because pp's agree to take part, giving consent.
Weaknesses- Biased/unrepresentative sample because pp's want to do it, may be motivated people (share characteristics e.g. helpful/free time).
Sampling method defined as a sample where every member of the target population has an equal chance of being chosen. Involving identifying everyone in target pop and selecting number of pp's needed to give everyone in pop an equal chance.
Strengths- More representative of target pop because all pp's have equal chance of being selected, range of different pp's, samples less biased.
Weaknesses- Very difficult and time consuming to carry out because have to have access to names of all people in target population. Sample can be unrepresentative as people may refuse to take part.
pp's hard to find, when researchers need particular type of person, to get more pp's ask those you have to find pp's for you. E.g. studying students that take illegal drugs, ask pp fitting criteria and they tell their friends, etc.
Strengths- Relatively easy to carry out because researcher only has to access few pp's.
Allows access to pp's that may be difficult to access.
Weaknesses- Unrepresentative sample because pp's may share similar characteristics (interests/beliefs/behaviours).
Longitudinal and Snapshot studies
carried out over short period of time, hours/days. PP's different ages/from different groups studied simultaneously and behaviour compared.
Strengths- Easier to carry out only requires studying short period of time and results are compared. Low levels of researcher bias as don't have time to develop rapport with pp's. Rarely suffer attrition because pp's don't have as much opportunity to drop out.
Weaknesses- Doesn't show change in development over time because researcher's only studying pp's at one 'snapshot' in their lives.
Results lack validity because pp's not studied in much detail.
study of same group of pp's for extended period of time, e.g. months/years.
Strengths- Change in development over time studied because pp's are being studied for extended period of time.
Lots of in depth data collected because pp's being studied for extended period of time often developed a rapport with researcher.
Weaknesses- Suffer from researcher bias because rapport develops over time.
Lack population validity as longitudinal studies tend to be case studies, small samples.
Suffer from attrition because pp's drop out/leave study over time.
collected by researcher for study currently happening. Data designed to fit aims and hypothesis of the study. However, time consuming and expensive process.
information collected for a purpose other than current piece of research, e.g. gov stats. Quicker and less expensive, but may not fit needs of study properly.
Types of Data
descriptive, in-depth and rich data give an insight into pp's thoughts, feelings and beliefs.
Strengths- Collects rich data because researchers give detailed insight into why people do things, increases validity.
Highly valid as pp's able to elaborate on thoughts, feelings and beliefs.
Weaknesses- Difficult and time consuming to analyse and compare because data often rich in detail and each piece might be unique.
Influenced by researcher bias because researchers may misinterpret data, reducing validity.
data expressed numerically in some way focussing on numbers and frequencies.
Strengths- Quick and easy because consists of numerical data, often more reliable,
Allows researchers compare findings easily between groups because can compare means/percentages easily.
Weaknesses- Lacks detail because doesn't explain why people behave the way they do, reducing validity.
Lacks depth and richness because not giving insight into thought feelings or beliefs. Data lacks validity
Levels of Data
Wheh collecting quantitative data, 3 levels of measurement. Lower levels are less precise.
Nominal: Organised into separate categories. e.g. grouping people according to height- tall, medium, small. Intelligence as below average, average or above average.
Ordinal: Numerical value is used, based on ranks or ratings. Pp's scores put in order, e.g. from best to worst. Ordinal data is subjective based on own personal opinion's. (rating scale).
Interval: Ranked data but distance between values equal. e.g. score on objective test, temp, height. Objective. If items are of similar level of difficulty.