Part 1 Overview In This Project You Are Asked To Conduct

Part 1 Overviewin This Project You Are Asked To Conduct Your Own Resea

In this project you are asked to conduct your own research into two variables that interest you. This project will give you an opportunity to apply the skills and techniques you learn in this class and to produce a professional report using appropriate technology. This is a MAJOR, on-going assignment and is worth 15% of your grade; the equivalent of one unit exam grade. Your projects will be graded in stages (Part 1, Part 2, Part 3) according to the attached rubrics. To be successful on your project you must: · Read and follow instructions carefully. · Work according to the timeline provided and submit work on time. · 10% will be deducted for each calendar day the project is submitted after the due date. A project is considered “submitted” when it is available for the professor to view on Canvas. No credit is given after 5 days late. · Students who fail to submit earlier parts of the project may still submit later parts of the project as long as their topic has been approved by their instructor and as long as they collect their own data. Points will still be taken away for lack of completeness unless those prior sections are completed and included. · Write clearly, using appropriate terminology and accurate mathematical notation. College-level writing is expected, as is the use of correct grammar. · If you need help with writing, feel free to use the HCC Writing Center: For further information, see the HCC Web page under the heading “Writing Center” or call the Writing Center at (.

PGCC students at the Laurel College Center should see the PGCC Writing Center for assistance. · Submit a neat, professional report typed using your choice of word processing software (including a mathematical notation package) and including printouts and diagrams from your choice of statistical software/technology. · In particular, embedded graphs or charts and/or computer printouts will be expected as part of the report. Hand-drawn graphs are not acceptable. · Please note: Excel should be used only with caution as it does not consistently follow accepted statistical practices. · Original work is expected. This means that students who are repeating the course are expected to create an entirely new project using two new variables of interest. · For example, you might watch a YouTube video on how to use StatCrunch or have a peer show you how to create a histogram using a different data set (not the one in your project), then try it yourself with your data set. You might consult your textbook or your instructor about a concept, but then put the explanation into your own words. · Getting Help: · For this project, you may consult any resource for general help and advice (including your instructor, tutors (LAC, HR230), classmates, or the internet) provided that your write-up (computations, explanations, and embedded diagrams) are your own work. · Submission guidelines: · You should submit your project via the Canvas link as a PDF or Word file. · VeriCite will be used as a deterrent to plagiarism. This program is integrated into the Canvas submission process. All submissions will be compared against the VeriCite database and receive an “originality” rating. · To earn the maximum score on this project, it is expected that students go “above and beyond” the minimum expectations of the project.

Paper For Above instruction

In this research proposal, I aim to analyze the potential relationship between two quantitative variables: the number of hours spent studying per week and the academic performance, specifically GPA, among college students. Understanding this relationship is significant because it can inform students and educators about the importance of study habits on academic success, potentially guiding interventions and study strategies to enhance performance.

The primary hypothesis is that increased study time correlates positively with higher GPA. It is plausible that the variable "hours of study per week" influences the "GPA" more than vice versa, thereby suggesting a cause-and-effect direction from study time to academic achievement. Exploring this relationship may highlight how study habits impact grades, which could be valuable for students striving to optimize their academic outcomes.

Participants will be drawn from a specific college student population, for example, community college students or a particular university cohort. The sample size will include at least 20 participants to gather sufficient preliminary data. Participants will be asked to respond to survey questions anonymously to encourage honesty, especially regarding sensitive information such as GPA. Ethical considerations include ensuring confidentiality, voluntary participation, and avoiding any coercion or undue influence. Participants will be informed about the purpose of the research and assured that their responses are confidential and used solely for academic purposes.

The survey will include the following questions:

• How many hours do you study for your main academic courses each week?
• What is your current GPA?

This data will be collected via a simple questionnaire, either paper-based or electronic, ensuring privacy and honesty. The variables are clearly defined: the first variable (X) is "hours of study per week," and the second variable (Y) is "GPA." The data will be used to analyze the correlation between these two variables, applying relevant statistical techniques such as Pearson’s correlation coefficient and scatter plots to visualize the relationship.

Materials include the survey instrument with these questions, and the tools required for statistical analysis—preferably software like StatCrunch, SPSS, or similar programs for data entry, computation, and graph generation. The results will be presented visually through scatter plots and numerical measures such as correlation coefficients, offering insight into the strength and nature of their association.

Approval from an Institutional Review Board (IRB) is not strictly necessary for this class project, but guidance from the instructor is required to ensure ethical standards are met. The project will be submitted as a PDF or Word document via Canvas. Original work is emphasized, with students encouraged to create entirely new projects when repeating the course, selecting different variables of interest, and utilizing independent data collection and analysis.

References

1. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage Publications.
2. Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson.
3. Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for the Behavioral Sciences (10th ed.). Cengage Learning.
4. Hatch, J. A. (2014). Doing Qualitative Research in Education Settings. State University of New York Press.
5. Moore, D. S., Notz, W., & Prophet, M. (2013). Statistics: Concepts and Controversies (8th ed.). W. H. Freeman and Company.
6. Leedy, P. D., & Ormrod, J. E. (2018). Practical Research: Planning and Design (12th ed.). Pearson.
7. Utts, J. (2015). Seeing Through Data: Using Visualisation to Improve Understanding. Sage.
8. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge.
9. Schober, P., & Boer, C. (2018). Correlation Coefficients: Appropriate Use and Interpretation. Anesthesia & Analgesia, 126(5), 1763–1768.
10. Field, A. (2018). An R Companion for the Discovering Statistics Series. Sage Publications.