Psychology-Research Methods-Quantitative and Qualitative Data

Meta-analysis

-a type of research that uses secondary data -where the data from large numbers of studies involving the sam research question and methods are combined and compared

Primary data evaluation (strengths)

-control-data collection can be designed so it fits the aim of the study -eg-> questionable and interview can be designed in such a way that they specifically target the information the researcher requires

Primary data

-data collected from first-hand experience -original data collected specifically for the purpose of the investigation by the researcher -data that comes directly from participant, the researcher ha I got designed the study, gained ethical approval, piloted the study, tested participants and analysed data -gathered by experiment, questionnaire, interview or observation

Secondary data evaluation (weaknesses)

-data may not exact,y fit the needs of the study -may vary in quality and accuracy, may be outdated or incomplete

Secondary data

-data that already exists before the researcher begins the study -data might have been collected by the rest her for a different study or by another researcher -may be located in journal articles, governments statistics or books

Open question definition

-does not havea fixed range of answers -participants are free to answer in any way they wish -eg-> you may ask participants how they felt during an investigation

Qualitative data

-expressed in words rather than numbers or statistics -may take the form of a written description of the thoughts, feelings and opinions of participants -may also take the form of a written account of what the researcher saw in an observation -eg->transcript from an interview extract from a diary notes recorded during a counselling session

Quantitative data

-expressed numerically eg->how much,how long,how many -data collection techniques usually gather data in the form of individual scores from participants -eg-> the number of words a person was able to recall in an experiment -can be analysed statistically -can be easily converted into graphs, charts ect -the dependent variable in an experiment is quantitative -closed questions in questionnaires collect quantitative data eg->how old you are,how many hours you work in a week -in an observation study a ta,,y of behavioural categories is quantitative

Closed question definition

-offers a fixed number of responses eg->yes or no -alternatively you may ask them to rate from 1-10

4 examples of when qualitative dat may be used

-interviews -questionnaires -observations without tally charts -diaries

Primary data evaluation (weaknesses)

-lengthy and expensive procedure -design g and carrying out the study takes a lot of time

Quantitative data evaluation (weaknesses)

-narrower in scope- less lie,lay to reflect real life -a questionnaire with closed questions may force people to tick answers that don't really reflect their feelings, so conclusions may be meaningless

Qualitative data evaluation (strengths)

-offers the researcher much more richness of detail than quanta time data -broader in scope and gives the participants more opportunity to develop their thoughts, feelings and opinions in the topic under investigation -tends to gave greater external validity than quantitative data

Qualitative data evaluation (weaknesses)

-often difficult to analyse -does not lend itself to being summarised statistically, so difficult to identify patterns and compare between groups/conditions

Meta-analysis evaluation (weakness)

-publication bias-reacher may leave out examples of research that do not support his/her hypothesis

4 examples of when quantitive data may be used

-questions with closed answers -psychological tests (eg->IQ) -experiments where participants are scored (even->memory test) -observations using tally charts

Quantitative data evaluation (strengths)

-relatively simple to analyse using descriptive statistics and statistical tests -easy to draw comparisons between groups/conditions -more objective and less open to bias

Meta-analysis evaluation (strength)

-results can be generalised across much larger populations

Secondary data evaluation (strengths)

-simple and cheap - less time and equipment involved -when examining. Secondary data a researcher Amy find that the desired information already exists, so there is not need to carry out primary data collection