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The Most Significant Change Technique (MSC) is a monitoring and evaluation (M&E) method used for the monitoring and evaluating of complex development interventions. It was developed by Rick Davies as part of his PhD field work with the Christian Commission for Development in Bangladesh (CCDB) in 1994. [ 1 ]
[citation needed] If the observed number of positives is substantially greater than what should be expected, this suggests that there are likely to be some true positives among the significant results. For example, if 1000 independent tests are performed, each at level α = 0.05, we expect 0.05 × 1000 = 50 significant tests to occur when all ...
The design of a study defines the study type (descriptive, correlational, semi-experimental, experimental, review, meta-analytic) and sub-type (e.g., descriptive-longitudinal case study), research problem, hypotheses, independent and dependent variables, experimental design, and, if applicable, data collection methods and a statistical analysis ...
Extraordinary research – When enough significant anomalies have accrued against a current paradigm, the scientific discipline is thrown into a state of crisis. To address the crisis, scientists push the boundaries of normal science in what Kuhn calls “extraordinary research”, which is characterized by its exploratory nature. [ 6 ]
One of the most important requirements of experimental research designs is the necessity of eliminating the effects of spurious, intervening, and antecedent variables. In the most basic model, cause (X) leads to effect (Y). But there could be a third variable (Z) that influences (Y), and X might not be the true cause at all.
Survey methodology is "the study of survey methods". [1] As a field of applied statistics concentrating on human-research surveys, survey methodology studies the sampling of individual units from a population and associated techniques of survey data collection, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys.
The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...
Although there is no single ideal animal model of a human, for each problem of interest there is an animal upon which it can be most conveniently studied. For example, the study of spatial memory has benefitted greatly from experimentation and observation of food caching birds. [28] To study auditory learning and memory, songbirds can be used.