Booklet 3: Types of Data:

Describe quantitative data

-numerica

-involves the measuring of something

-statistical analysis

-experiment based reasearch

describe qualitative data

-non numerical eg) text/speech

-finding how poeple think/feel

-colect in case studies, unstructured observations/interveiws

-subjective

(+) how is quant less subjective? how does this then lead to high internal validity

(+) quant data is less subjective than qual bcs the reasercher doennt need to interpret ppt responses. Thereofre it could have high internal validity bcs tehres less subjective opitions of the reasercher and so a higher chance theyre measuring wat they intend to measure

(-) quant data doesnt provide rich detail ine ppt experiences: why is tis a weakness?

(-)doesnt provide rich detail on why people do the behaviour,

unable to understand peoples opinions, beleifs, values.

correlaton not backed up (as you find this using qual data)

doesnt get reason/identfy anoalies or if teh iilness whant genetical rather environemntal

(+) qual data provides the reasercher with rich detail. Why is this a strength ?

(+) provides the reasercher with in depth responses. ppt can discuss teir personal thoughts/feelings regardinga a paticular phenomanon. Therfore it tends to have high external validity as teh finings would be representative of epoples eiws. This also means they would gin a greater understanding of human behaviour

describe primary data using examples

refers to teh original dtata collected towards a specific reaserchers aim and hasnt been published before eg) questinair to prove a hyppotheis s(new reaserch)

describe secondary data using examples

data collected towards another reaserchers aim which has been publshed before eg) using a gold standard questionaire

(=_ one strength

(-) one limitation of primary data

(+) more specific to your aim/ more valid as it has been specifically made to investigate the hypothesis

(-) expensive and time consuming to carry out

(+) strength

(-) limitation on secondary data

(+) reliable as been authenticated through pubblishing

(-) lach applicabilty to hypothesis espc if its new reaserch

(+) could lack temporal validty

(-) less valid as it might not it to the needs o fteh hypothesis exactly `

describe a meta analysis and disucss why this si a useful way of retreiving data

form of a reaserch method that uses secondary data. it is a process in which a number of studies are identified which have teh same aims/hypotheiss. The reuslt of tehrse are collated to form a joint conclusion

(=) strength of meta analysis

(+) allows for generalisabliity as a large sample is gaied (depending on how many studies your looking at) and increases external validity

limitation of meta anlysis

(-) prone to publication bias eg ) reasercher sleecting a few significant results nd leaving out teh ones that may not fit with findings/hypothesis→ less relavant

`(-) a weakness of qual data s …

less easy to present data on graph/table to analyse as it is subjective to interpretations eg

) if teh reasercher has preconceptions or an idea of what tehyre expecting

difficult to analyse→ have to convert qual to quant to analyse

less objective as you need to interpret and is more subjecting→ reasercher bias