# Is Correlational study a good choice?

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I have to develop a research design for a pretend study. It will be quantitative to study the effects of linguistic modification on nursing exams for one year. The original exam and the modified exam will be randomly assigned to students (native English speakers and English as a second language students). There would be scores from four groups to compare:

native English speakers recieving the original exam

English as a second language receiving the original exam

native English speakers recieving the modified exam

English as a second language recieving the modified exam

I have no idea what kind of quantitative analysis to use for this. Would this be correlational? If you have a better idea please tell me as I am stuck.

Assessment strategies in nursing education need to respect the diverse student population. Multiple-choice examinations are a popular assessment tool because they reflect the type of questions that make up the national licensure exam. However, small qualitative studies have shown that linguistic bias is a determent to English as a second language (ESL) and culturally diverse students' success in nursing programs and in passing the national licensure examination. This study will quantitatively determine if there is a difference between successes on linguistic modified exams and ESL students and the non-modified exams. The study will also show whether the native English speaking (NS) fairs better on the modified exam.

One exam will be the regular exam given in class

the other will be "modified" so there is no language bias in the exam

Example: regulare exam might say "the patient was drinking gatoraid for his clear liquid diet" and ESL and culturally diverse students might not know what gatoraid is

whereas a native who grew up here would know gatoraid is a clear liquid.

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The solution determines whether correlational study is a good choice.

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Hi,

I just provide with you some of my thoughts. It might help you.

First of all, it seems to me that you cannot conduct a correlation analysis. It looks like the NS students would perform equally on both the modified exam and non-modified exam (since they have no problems with language), while ESL students would perform differently on the two type of exams.

Secondly, I do not think you can just do one single quantitative analysis. However, you may conduct several hypothesis tests. For instance,

1) Determine if there is a difference between successes on ...

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- "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
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