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Significance Evaluating Significance of Findings Ashita Patel Walden University RSCH 8210 1
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Significance Scenario 1: Sample Size Based on the nature of the research questions, available resources, and the objectives of a study, a researcher may choose to select a small or large sample size. A small sample size may not provide sufficient data resulting in the inability to detect a difference between groups. This may lead the study to be a false negative leading to a type II error. Utilizing a large sample size enables us to gather more information, thus decreasing our level of uncertainty. A small sample size results in a larger confidence interval versus a large sample size which reduces the margin of error. (Nayak, 2010). In this scenario, the sample size is sufficient and represents students in both traditional (n=65) and online (n=69) classroom settings. Meaningfulness Dr. Matt Jones refers to meaningfulness as utilizing the statistic and determining its applicability to the real world. Often times, highly statistically significant data may have a rather small effect in the real world, resulting in almost meaningless data. (Laureate Education, 2016f). In this scenario, the results emphasized students participating in online quantitative reasoning classes have higher levels of satisfaction. This emphasizes that educators must analyze and assess which method of teaching will produce knowledgeable and well-rounded practitioners. While the results indicate students in the online classrooms have higher levels of satisfaction, researchers must recognize that the modern generation is more prone to utilizing digital formats and technology. However, results of this study may differ if researchers assess a mathematical
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  • Summer '17
  • Madia Levin
  • Statistics, Statistical hypothesis testing, researcher, Statistical significance, Statistical power

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