Design types and Data types

Objective Quantitative- a numerical set of data that is not based on opinion, such as measured heart- rate, time, or number of responses

Objective= Factual

Quantitative= Numerical

-              Physiological Responses

-              Behaviour counts

-              Scores on standardised test

Subjective Quantitative- a numerical set of data based on opinion, such as a rating scale

Subjective = Opinionated / provided by subject

Quantitative= Numerical

-              Responses on a checklist

-              Rating scales

-              Scores on a personality test

-              Questionnaires

Qualitative- non- numerical data, such as spoken or written accounts or case notes

Rich, written or verbal data

Uses either focus groups or Delphi technique

Most commonly uses content analysis

Content analysis

-              Used to organise the data gathered from focus groups

-              Organise data – become familiar with it

-              Identify core themes- groups of comments that are similar in nature

-              Code themes- develop a name that identifies each theme

-              Keep track of themes- note reoccurring themes were they an initial comment or responsive comments, look at agreements, disagreements, contradiction, different ways of saying the same thing

-              Analysis- summaries using frequency tables, with illustrative quotes

Statistical Analysis

-              Statics are calculation usually used on quantitative data to show any patterns or relationships in the result, basically to tell us what the results mean

Descriptive statistics

-              Shows patterns or trends in the data – mean, median, mode, distributions

Inferential statistics

-              Gives info on the presence and strength of relationships between variables

-              Measures the confidence with which we can say that a real effect has been observed and that our hypothesis has been supported