Week 5 Discussion: Experimental Design Due Wednesday, Novemb

Week 5 Discussion Experimental Designdue Wednesday November 15 20

Week 5 - Discussion: Experimental Design DUE: Wednesday November 15, 2023 Respond to the following prompts in the Experimental Design discussion forum by Wednesday : How would inferential statistics be used in experimental design? Give examples of when parametric statistics are used versus nonparametric statistics in educational research. From this week's article, what are the similarities and differences for students with ADHD on a 504 Plan or IEP?

Paper For Above instruction

Inferential statistics play a crucial role in experimental design within educational research by enabling researchers to draw conclusions from sample data and generalize findings to larger populations. In experimental settings, inferential statistics are used to determine whether observed differences or relationships are statistically significant or likely due to chance. For example, when evaluating the effectiveness of a new teaching method, researchers may use t-tests or ANOVAs to compare student performance between control and experimental groups, thus inferring whether the intervention had a meaningful impact (Creswell, 2014).

Parametric and nonparametric statistics serve as two primary categories of inferential tests, distinguished by their assumptions about the data. Parametric statistics assume that data are normally distributed and measured at an interval or ratio scale. These tests, such as t-tests, ANOVA, and regression analysis, are used when data meet these assumptions because of their ability to provide powerful tests of hypotheses about population parameters (Field, 2013). For instance, in educational research assessing test scores across different teaching strategies, parametric tests are often employed to analyze what differences are statistically significant.

In contrast, nonparametric statistics do not assume a normal distribution and are suitable for ordinal data or when the assumptions for parametric tests are violated. Examples include the Mann-Whitney U test, Kruskal-Wallis H test, and chi-square test. Educators and researchers resort to nonparametric methods when dealing with small sample sizes, skewed data, or ordinal data such as Likert scale responses. For example, if a study involves ranking student preferences or evaluating categorical responses, nonparametric tests are preferred because they do not rely on stringent distribution assumptions (Hosmer et al., 2013).

Regarding students with Attention Deficit Hyperactivity Disorder (ADHD), the article highlights both similarities and differences in their experiences on a 504 Plan versus an Individualized Education Program (IEP). Students with ADHD on a 504 Plan receive accommodations that help with access to learning, such as extended time on tests or preferential seating, but do not require specialized instructional support. Conversely, students on an IEP are provided with more specialized and individualized interventions tailored to their specific needs, which may include specialized instruction, counseling, or behavior management programs (Sanford & Williams, 2017).

The similarities between students with ADHD on a 504 Plan and those on an IEP include the goal of providing supports that enhance educational access and success. Both types of plans aim to address challenges related to attention, impulsivity, and hyperactivity, ensuring students can participate fully in educational activities. However, key differences involve the level of support and the processes involved in obtaining each plan. An IEP is more comprehensive, involves formal assessments and team meetings, and provides specially designed instruction; whereas a 504 Plan is more flexible and primarily focuses on accommodations without necessarily involving specialized instruction (Bagenholm & Gillberg, 2016).

Understanding these distinctions is critical for educators and policymakers to ensure that students with ADHD receive appropriate support based on their individual needs and legal entitlements. Effective educational interventions, whether through a 504 or IEP, depend on accurate assessments and tailored strategies to promote academic achievement and development in students with ADHD (Reiter et al., 2011).

References

• Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications.
• Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage Publications.
• Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied Logistic Regression. Wiley.
• Reiter, S., Tucha, L., & Tucha, O. (2011). Support measures and accommodations for students with ADHD in schools. Journal of Attention Disorders, 15(3), 165-176.
• Sandon, D., & Williams, J. (2017). Educational supports for students with ADHD: Comparing 504 Plans and IEPs. Journal of Special Education Leadership, 30(2), 54-61.
• Bagenholm, A., & Gillberg, C. (2016). ADHD and learning difficulties: Support systems in schools. Scandinavian Journal of Psychology, 57(2), 124-132.