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292 INDEX<br />

matrices 201–211, 239, 259, 272;<br />

see also cross-tabulations<br />

Maxwell, A.E. 27–7<br />

meaning:<br />

as basis for qualitative <strong>data</strong> 11–12;<br />

bits of <strong>data</strong> as units of 121–17, 125,<br />

127;<br />

of a category 108;<br />

communication of see communication;<br />

and number 3, 12, 18, 25–5, 29, 49,<br />

273;<br />

and science 27<br />

measurement 11, 18–29<br />

memos 92–98, 105, 127, 127–2, 210, 239,<br />

247, 262, 272;<br />

on computer 94, 280;<br />

on paper 93<br />

Merrill, L. 69–8, 71, 73, 91<br />

methodology of qualitative <strong>data</strong> <strong>analysis</strong> 4–<br />

8, 273–7;<br />

for individual processes see process<br />

Miles, M. 5, 7, 51, 145, 186, 200, 230<br />

natural sciences see science<br />

networks, network approach 5, 274<br />

neuron networks 274<br />

Noguchi, Hideyo 228<br />

nominal variables 22–2, 45, 46, 152<br />

number(s):<br />

as basis for quantitative <strong>data</strong> 11, 29;<br />

and meaning 3, 12, 18, 25–5, 29, 49,<br />

273;<br />

use of, in qualitative <strong>analysis</strong> 27–8, 49,<br />

188–80, 207, 231, 268, 273<br />

objectivity 35, 228, 236, 268<br />

observation, observational research 14–15,<br />

104, 105, 116, 184, 232, 233;<br />

participant 4, 14, 38, 103<br />

O’Hanlon, Redmond 26<br />

ordinal variables 23, 24, 45, 152<br />

participant observation 4, 14, 38, 103<br />

pattern coding 5<br />

patterns in <strong>data</strong> 5, 28, 48, 50, 202, 203,<br />

205, 208, 210, 263, 273;<br />

see also connections<br />

Patton, M.Q. 5, 7, 14, 249, 268, 270<br />

Penrose, R. 274<br />

Peter, L. 86, 99<br />

Pfaffenberger, B. 274, 275<br />

policy <strong>analysis</strong>, evaluation xiv, 68, 87, 103,<br />

110, 244, 248, 257, 258<br />

positivist social science 36<br />

Praverand, P. 64<br />

pre-structured <strong>data</strong> 14<br />

prediction and qualitative <strong>analysis</strong> 30<br />

prejudice see bias<br />

probabilities 239;<br />

see also inference<br />

psycho<strong>analysis</strong> 36;<br />

and fairy stories 33–4<br />

qualitative <strong>data</strong>:<br />

collection see qualitative research,<br />

techniques and methods;<br />

diversity of 12–12;<br />

gaps in, revealed by use of diagrams 200,<br />

202;<br />

irrelevant 85, 259;<br />

nature of 9–29;<br />

patterns in see patterns;<br />

quality of 75–5, 231–5, 263;<br />

reduction and summarizing of 249–5,<br />

263, 267<br />

see also diagrams;<br />

reflecting on, to find focus for <strong>analysis</strong><br />

65–6;<br />

relationship to quantitative see<br />

quantitative <strong>data</strong>;<br />

unstructured nature of 14–16<br />

qualitative <strong>data</strong> <strong>analysis</strong>:<br />

acquisition of skills 6;<br />

finding a focus for 64–75, 105, 247;<br />

independent assessment and advice 242–<br />

5, 244, 258;<br />

methodology and processes see<br />

methodology;<br />

nature of 30–1, 54–4, 271–5<br />

paradoxes of 273;<br />

relationship to quantitative see<br />

quantitative <strong>data</strong>;<br />

traditional 4, 93, 200, 275;<br />

see also classification;

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