Types of data

• Quantitative data is numerical data that can be statistically analysed and converted easily into a graphical format.
• A weakness of meta-analysis is bias, as the researchers are selecting data from previous research, and they may have chosen to omit certain findings from their data is they showed no significant result or we in conclusive. Therefore, the findings and conclusions from the meta-analysis will be biased as they do not accurately represent all of the relevant data on the topic.
• Experiments, structured observations, correlations and closed/rating-scale questions from questionnaires all produce quantitative data.
• A strength of quantitative data is that it is easy to analyse statistically.
• A strength of quantitive data is it easy to analyse statistically. When large amounts of numerical data are generated it is relatively easy to conduct descriptive statistics or inferential tests of significance which allow for comparisons and trends to be identified between groups. Therefore it is more objective as established mathematical procedures are in place.
• Since established mathematical procedures are in place for this type of analysis, it makes quantitative data more objective.
• A disadvantage of quantitative data is its lack of representativeness.
• A disadvantage of quantitive data is it lack of representativeness. Since this type of data is often generated from closed questions, the responses gained are narrow in their scope towards explaining complex human experiences, opinions and feelings. Compared to qualitative data it can often lack meaning and context - therefore it may not be a true representation of real life and lack validity
• Qualitative data is non-numerical, language-based data expressed in words which is collected through semi-structured or unstructured interviews and open questions in a questionnaire.
• Qualitative data allows researchers to develop an insight into the unique nature of human experiences, opinions and feelings.
• A strength of obtaining qualitative data is the rich detail obtained by the researcher.
• Within qualitative data participants can develop their responses freely this provides the investigator with meaningful insights into the human condition.
• A limitation of qualitative data is that it can be subjective as it relies on the opinons of the researcher
• Due to the rich, and often lengthy, detail of participants' responses, interpretations of this type of data can often rely on the opinions and judgements of the researcher.
• This means that any preconceptions that the researcher holds may act to bias any conclusions drawn.
• Primary data refers to data that has been collected for a specific reason and reported by the original researcher.
• An advantage of meta analysis is the results are combined from many studies, rather than just one, so the conclusions drawn will be based on a larger sample, which provides greater confidence for generalisation, increasing the validity of the patterns and trends identified.
• A strength of secondary data is the information already exists in the public domain, it is much less time-consuming and expensive to collect. Making the collection and use of secondary data much easier when compared with primary data.
• This can include a qualitative review of previous research or a statistical, quantitative analysis to test for significance of effect size.
• Designing and carrying out a psychological study can take a long period of time and considerable effort, which can lead to expenses due to the time investment needed on behalf of the researcher and any equipment that needs to be purchased.
• Secondary data is information that was collected by other researchers for a purpose other than the investigation in which it is currently being used, and is therefore already existing data.
• Since the researcher is selecting data from research which has already taken place, they may choose to omit certain findings from their investigation, particularly if the previous findings showed no significant results or were inconclusive.
• An example of a meta-analysis from developmental psychology is the work conducted by van lizendoorn et al., investigating cross-cultural variations in attachment.
• A limitation of using secondary data involves concerns over accuracy, as the data was not gathered to meet the specific aim of the research, it stands to reason that there may be significant variability in the quality of the data.
• Examples of secondary data include Government reports like the census or statistics about mental health from the NHS.
• Secondary data is sometimes referred to as desk research because the significance of the data is already known.
• Meta-analysis refers to a process whereby investigators combine findings from multiple studies (secondary data) on a specific phenomenon to make an overall analysis of trends and patterns arising across research.
• Primary data is data that the participant reports directly to the researcher (often via an interview/questionnaire) or is witnessed first-hand (via an observation/experiment).
• Primary data is sometimes referred to as field research.
• A strength of primary data is its authenticity, because it is collected with the sole purpose of being for a specific investigation.
• Since the data collection is designed to suit the aims of the research, this enables the researcher to exert a high level of control.
• This is advantageous as there is a greater probability that the data generated will fit the aims of the investigation, reducing any wasted time on behalf of the researcher and ensuring that the information prepared for analysis.
• A weakness of meta-analysis

  bias