types of data

primary data defintion

• field research

• data arrives first hand from participants

• for the purpose of investigations

how to collect primary data

gathered from questionnaires, interviews or observation

primary data strengths

• questionnaires, interviews or observations can be designed more specifically for the experiment to target certain information

• data is more authentic as they know the limitations and inaccuracies with their own experiment

primary data weaknesses

time, resources, money

secondary data definition

• desk research

• data collected by someone else before the psychologist starts their investigation

• and has already been subject to statistical testing and therefore the significance is known

how to collect secondary data

• data on websites, articles, journals or books

• or statistical data provided by the government eg census

secondary data strengths

• inexpensive, easily accessible

• no point  of doing the exact same experiment again 

secondary data weaknesses

• substantial variation in quality and accuracy of data (OUTDATED or INCOMPLETE)

• may not match experimenters needs (significantly REDUCES VALIDITY)

quantitative data definition

• can be counted

• usually gathers NUMERICAL data in an EXPERIMENT

quantitative data strengths

• can easily draw comparisons in groups

• more objective, less bias

quantitative data weaknesses

narrower in detail and meaning lacks ECOLOGICAL validity (fails to represent real life)

qualitative data definition

• expressed in words

• UNSTRUCTURED OBSERVATION(transcript from an interview or notes from counselling)

• concerned with INTERPRETATION of data

• ex thoughts, feelings, opinions

qualitative data strengths

rich in detail more bale to report thoughts, opinions, feelings provides greater EXTERNAL VALIDITY(extent of generalisability)

qualitative data weaknesses

• difficult to analysis cant often be summarised statistically so patterns are harder to find

• conclusions rely on subjective interpretations →subject to researcher bias (especially if there are preconception in what they are going to find)

definitions of meta analysis

research method that uses the combination of SECONDARY data from a large number of studies which involve the SAME RESEARCH QUESTIONS/METHODS OF RESEARCH

how meta analysis works for qualitative data

qualitative analysis → may simply discuss the findings/conclusion

how meta analysis works for quantitative data

• perform statistical analysis on the combined data like calculating the effect size(DV gives an overall statistical measure of difference of relationship between variables across a number of studies )

strengths of meta analysis

view data with more confidence as the larger sample size allows result to be generalised across a larger population

weaknesses of meta analysis

prone to publication bias (referred to as the FILE DRAW PROBLEM)

• can leave out relevant studies with negligible or negative effect on results

• since not all data is represented the conclusions are bias