|
Measurement: foundations of measurement; scales; meaningfulness. Data Analysis: basic statistics; distributions; measures of average, variability, error, and confidence; quantiles; measures of correlation; sampling theory; confidence intervals and confidence tests. Results Evaluation: evaluating results with reference to hypotheses. Evaluation of validity: internal and external validity; threats to validity; evaluating the validity of published research results. Formulation and testing of hypotheses: expressing hypotheses; selection of a test approach; design and execution of experiments, surveys, and case studies. Design of experiments and testing of hypotheses. Applications to performance analysis, cost/time estimation, as well as software metrics.
|