quantative research: sampling, data collection & measurement

quantative research: sampling, data collection & measurement

1. sampling

   • predetermined
   • planned statistical techniques to select sample
   • meaningful answers
   • sample size must be large enough to have statistical power

2. probability sampling methods

   • more likely to be representative of the population
   • associated with quant. research
   • when all individuals have a 0 chance of being selected

3. simple random sampling

   • each member of the population has = chance of being selected
   • selected one at a time
   • independant of each other
   • cannot be selected again

4. systematic sampling

   • dividng sampling frame into a no. of intervals
   • random starting point
   • selecting one element from each intrval in a systematic way
   • i.e. every 10th person
   • can be biased

5. stratified random sampling

   • divide into 2 groups
   • calculate no. of participant needed in each group, so the no. reflect their portion in the population
   • randomly selected participants
   • i.e. 20% of pop. is dutch, 20% of the cases need to be dutch

6. cluster sampling

   • population divided in groups of clusters
   • a certain number of clusters are randomly chosen

7. sample representative of the whole source population?

   • is it adequate in size?
   • accurate in characteristics?
   • it complete?

8. sampling error and sample distribution

   • sampling error- discrepency between sample mean & true population mean
     • this needs to be close
   • sampling distribution theory- estimate how representative a sample is in relation to the target population

9. quantitative data collection

   • primary and secondary data sources
   • study design and research Q will influence data collection method
   • methods
     • records- ddata from existing sources
     • questionnaires
     • case studies
     • video tape observations
     • surveys and questionnaires
       • quant. data collection
       • describe trends, behaviours, attitudes and opinions
       • establish association or relationship between variables
       • need; sample of participants to complete no. of standard q's
       • need; large no. of participants
       • need; set of standard q's- comparisons can be made
       • need; statistical analysis can be conducted, described and compared
       • results can be generalised to the population
     • Physiological Measures
       • called clinical data
       • statistical data relating to the measurement of the body
       • potential problems with physiological/clinical data collection
         • physiological variation in some tests
         • variation in measuring instrument
         • observer variation- human error
         • standardised criteria & interpretation
         • bias from interactions