Experimental Design

Sample Solution

Inferential statistics are used in experimental design to make generalizations about a population based on a sample of data. This is done by calculating a statistic (e.g., mean, standard deviation) from the sample data and then using this statistic to estimate a parameter (e.g., population mean, population standard deviation) for the population.

There are two main types of inferential statistics: parametric and nonparametric. Parametric statistics assume that the data follow a normal distribution, while nonparametric statistics do not have this assumption. The type of inferential statistic used depends on the specific research question and the characteristics of the data.

Full Answer Section

Here are some examples of how inferential statistics are used in experimental design:

• To compare two groups: A researcher might use a t-test to compare the mean scores of two groups of students on a math test. The t-test would allow the researcher to determine whether there is a statistically significant difference between the two groups.
• To assess the effectiveness of an intervention: A researcher might use an ANOVA to compare the mean scores of three groups of students on a reading test: one group that received no intervention, one group that received a reading intervention, and one group that received a different reading intervention. The ANOVA would allow the researcher to determine whether there is a statistically significant difference between the three groups.
• To make predictions about the future: A researcher might use a regression analysis to predict the SAT scores of a group of students based on their high school GPA. The regression analysis would allow the researcher to develop an equation that can be used to predict SAT scores for future students.

Examples of when parametric statistics are used versus nonparametric statistics in educational research

Parametric statistics are often used when the data are normally distributed and the researcher is interested in making comparisons or predictions. Nonparametric statistics are often used when the data are not normally distributed or the researcher is not interested in making comparisons or predictions.

Here are some specific examples of when parametric and nonparametric statistics are used in educational research:

• Parametric statistics:

  • Comparing the mean scores of two groups on a math test
  • Assessing the effectiveness of an intervention using an ANOVA
  • Making predictions about the SAT scores of a group of students based on their high school GPA

• Nonparametric statistics:

  • Comparing the median scores of two groups on a reading test
  • Assessing the effectiveness of an intervention using a Mann-Whitney U test
  • Ranking the reading scores of a group of students

Similarities and differences for students with ADHD on a 504 Plan or IEP

Students with ADHD who have a 504 Plan or an IEP share some similarities, but there are also some important differences between the two plans.

Similarities:

• Both plans are designed to provide students with ADHD with the accommodations and support they need to succeed in school.
• Both plans are individualized, meaning that they are tailored to the specific needs of each student.
• Both plans require regular review and updates to ensure that they are meeting the student's needs.

Differences:

• 504 Plans are designed to provide accommodations for students with disabilities who do not need special education services.
• IEPs are designed to provide special education services for students with disabilities who need more than accommodations to succeed in school.
• 504 Plans are implemented by the school's general education team.
• IEPs are implemented by a team that includes the student's parents, teachers, and other professionals.

Here is a table that summarizes the similarities and differences between 504 Plans and IEPs:

Conclusion

Inferential statistics are a valuable tool for researchers in experimental design. They can be used to make generalizations about a population based on a sample of data, to compare two or more groups, to assess the effectiveness of an intervention, and to make predictions about the future. Parametric statistics are often used when the data are normally distributed, while nonparametric statistics are often used when the data are not normally distributed. Students with ADHD who have a 504 Plan or an IEP share some similarities, but there are also some important differences between the two plans.