Data handling and analysis

• Quantitative and qualitative data; the distinction between qualitative and quantitative data collection techniques.
• Primary and secondary data, including meta-analysis.
• Descriptive statistics: measures of central tendency – mean, median, mode; calculation of mean, median and mode; measures of dispersion; range and standard deviation; calculation of range; calculation of percentages; positive, negative and zero correlations.
• Presentation and display of quantitative data: graphs, tables, scattergrams, bar charts,
• Distributions: normal and skewed distributions; characteristics of normal and skewed
• Analysis and interpretation of correlation, including correlation coefficients.
• Levels of measurement: nominal, ordinal and interval.
• Content analysis and coding. Thematic analysis

Inferential testing

  • Introduction to statistical testing; the sign test: When to use the sign test; calculation of the sign test.
  • Probability and significance: use of statistical tables and critical values in interpretation of significance; Type I and Type II errors.
  • Factors affecting the choice of statistical test, including level of measurement and experimental design. When to use the following tests: Spearman’s rho, Pearson’s r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test and Chi-Squared test.