Data handling and analysis

Data handling and analysis

1. Quantitative data

   • Numerical data
     • Quantity
   • Closed questions in questionnaires collect this type of data
   • Tally of behavioural categories is quantitative
   • Easy to analyse using descriptive statistics and statistical tests
   • Such data may over simplify reality. For example, a questionnaire with closed questions may force people to tick answers that don't represent thier feelings.
     • Therefore conclusions may be meaningless.

2. Qualitative data

   • Words, feelings, opinions.
     • "Quality"
   • Open questions in questionnaires may collect this type of data
   • Provides detailed information which can give deeper insights into thoughts and behaviour
     • Answers are not restricted by previous expectations
   • Complexity makes it more difficult to analyse and draw conclusions.
   • In an observational study researchers can describe what they see, this being qualitative

3. Primary data

   • Information observed or collected directly from first-hand experience.
   • This involves designing the study, gaining ethical approval, piloting the study, recruiting and testing Pps and analysing the data then drawing conclusions.
   • The researcher has a lot of control over the data.
   • It is a very lengthy and expensive process.

4. Secondary data

   • Information collected for a purpose other than the current one. Usually data collected by someone else.
     • Previously published data.
   • A correlational study often uses secondary data.
   • Review studies use secondary data, conducting a meta-analysis.
   • It is simpler and cheaper to access someone else's data.

5. Descriptive statistics

   • Measures of central tendency
     • Mean - Add up all numbers and divide by N.
       • Easily distorted by extreme values.
       • Most sensitive because it takes into account the exact distance between all the data values.
     • Median - order all numbers and select mid point.
       • Not affected by extreme scores.
       • Exact values are not reflected in the median
     • Mode - Most common value or group.
       • Unaffected by extreme values.
       • Not a useful way of describing data when there are several modes.
   • Measures of dispersion
     • Range - Subtract lowest from highest and add 1.
       • Easy to calculate
       • Affected by extreme values.
     • Standard deviation - Shows the amount of variation in a data set. It assess the spread of data around the mean. Average distance between each number and the mean.
       • A precise measurement of dispersion because exact values are taken into account.
       • It may hide some of the characteristics of the data set such as extreme scores.

6. Levels of measurement

   • Nominal: Data in categories e.g yes/no, boy/girl.
   • Ordinal: Data that is ordered e.g. ranking and rating.
   • Interval: Data measured using units of equal intervals. Precise measurements.