Nice

Research methods: Data analysis
G

Qualitative analysis of data
Recording experiences and meanings

Distinctions between quantitative and qualitative studies Reason and Rowan’s views Reicher and Potter’s St Paul’s riot study McAdams’ definition of psychobiography Weiskrantz’s study of DB Jourard’s cross-cultural studies Cumberbatch’s TV advertising study A bulimia sufferer’s diary

G

Interpretations of interviews, case studies, and observations
Some of the problems involved in drawing conclusions from non-experimental studies.

G

Content analysis
Studying the messages contained in media and communications.

G

Quantitative analysis: Descriptive statistics
What to do with all those numbers and percentages at the end of the study.

Measures of central tendency: Mean, median, and mode Levels of measurement Measures of dispersion: range, interquartile range, variation ratio, standard deviation Frequency polygon, histogram, and bar chart Types of data: nominal, ordinal, interval, ratio Statistical significance Tests of difference: Mann-Whitney U test, sign test, Wilcoxon test Scattergraphs, Spearman’s rho Test of association: chi-squared Questions to test experimental validity Varied definitions of ecological validity

G

Data presentation and statistical tests
When to use a chart or a graph. Which statistical test to choose and why.

G

Issues of experimental and ecological validity
Does your study test what you say it does? Has it any relevance to real life?

G

Writing up a practical
Presenting your results.

Style and approach Headings to use

Note: Cross references to “PIP” refer to the printed version of Psychology: An International Perspective by Michael W. Eysenck.

© 2004 Psychology Press Ltd

1

2 Research methods The data obtained from a study may or may not be in numerical or quantitative form, that is, in the form of numbers. If they are not in numerical form, then we can still carry out qualitative