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Spencer, Neil H.; Lay, Margaret; Kevan de Lopez, Lindsey – International Journal of Social Research Methodology, 2017
When undertaking quantitative hypothesis testing, social researchers need to decide whether the data with which they are working is suitable for parametric analyses to be used. When considering the relevant assumptions they can examine graphs and summary statistics but the decision making process is subjective and must also take into account the…
Descriptors: Evaluation Methods, Decision Making, Hypothesis Testing, Social Science Research
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Ryan, Wendy L.; St. Iago-McRae, Ezry – Bioscene: Journal of College Biology Teaching, 2016
Experimentation is the foundation of science and an important process for students to understand and experience. However, it can be difficult to teach some aspects of experimentation within the time and resource constraints of an academic semester. Interactive models can be a useful tool in bridging this gap. This freely accessible simulation…
Descriptors: Research Design, Simulation, Animals, Animal Behavior
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Schoemann, Alexander M.; Miller, Patrick; Pornprasertmanit, Sunthud; Wu, Wei – International Journal of Behavioral Development, 2014
Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design…
Descriptors: Monte Carlo Methods, Simulation, Sample Size, Research Design
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Glick, Margaret B.; Chermack, Thomas J.; Luckel, Henry; Gauck, Brian Q. – European Journal of Training and Development, 2012
Purpose: The purpose of this paper is to assess the effects of scenario planning on participant mental model styles. Design/methodology/approach: The scenario planning literature is consistent with claims that scenario planning can change individual mental models. These claims are supported by anecdotal evidence and stories from the practical…
Descriptors: Intervention, Pretests Posttests, Effect Size, Strategic Planning
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Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2009
A common mistake in analysis of cluster randomized experiments is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects.…
Descriptors: Data Analysis, Statistical Significance, Statistics, Experiments
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Huberty, Carl J.; Holmes, Susan E. – Educational and Psychological Measurement, 1983
An alternative analysis of the two-group single response variable design is proposed. It involves the classification of experimental units to populations represented by the two groups. Three real data sets are provided to illustrate the utility of the classification analysis. A table of sample sizes required for the analysis is presented.…
Descriptors: Classification, Data Analysis, Hypothesis Testing, Research Design