Review Of [Name Of Article]: State The Author

Review of [Name of Article]†State the Author

Read/review the following resources for this activity: OpenStax Textbook: Chapter 2 Lesson Chamberlain University Library Internet Week 3 Lab Template. Required Software: Microsoft Word. Internet access to read articles. Scenario/Summary: This week's lab highlights the use of graphics, distributions, and tables to summarize and interpret data. Instructions: Part 1: Your instructor will provide you with a scholarly article. The article will contain at least one graph and/or table. Please reach out to your instructor if you do not receive the article by Monday of Week 3.

Part 2: Title your paper: “Review of [Name of Article]” State the author: Summarize the article in one paragraph. Post a screenshot of the article's frequency table and/or graph. Example: Frequency Distribution -OR- Graph. Answer the following questions about your table or graph: What type of study is used in the article (quantitative or qualitative)? Explain how you came to that conclusion. What type of graph or table did you choose for your lab (bar graph, histogram, stem & leaf plot, etc.)? What characteristics make it this type (you should bring in material that you learned in the course)? Describe the data displayed in your frequency distribution or graph (consider class size, class width, total frequency, list of frequencies, class consistency, explanatory variables, response variables, shapes of distributions, etc.). Draw a conclusion about the data from the graph or frequency distribution in the context of the article. How else might this data have been displayed? Discuss the pros and cons of 2 other presentation options, such as tables or different graphical displays. Why do you think those two other presentation options (i.e., tables or different graphs) were not used in this article? Give the full APA reference of the article you are using for this lab. Be sure your name is on the Word document, save it, and then submit it under "Assignments" and "Week 3: Lab". Requirements: The deliverable is a Word document with your answers to the questions posed above based on the article you were assigned.

Paper For Above instruction

The purpose of this lab activity is to evaluate the use of graphical and tabular methods for data presentation within scholarly research. The focus is on analyzing the type of data study, the graphical representation selected, and the implications of different data presentation formats. This exercise enhances understanding of statistical visualization tools and their suitability in different research contexts.

Introduction and Article Summary

The scholarly article provided by the instructor investigates [insert brief research topic], utilizing data collected through [describe data collection method]. The authors aim to analyze [specific research questions or hypotheses], presenting their findings through various statistical tools. The article incorporates at least one graph and/or table, which encapsulates critical data patterns and insights. The study employs a quantitative approach, evidenced by the measurement of variables, numerical data analysis, and statistical interpretation.

Identification and Analysis of the Data Visualizations

The selected graph for analysis is a bar graph, characterized by discrete categories along the x-axis and height proportions representing frequency or relative counts. The decision to use a bar graph is supported by its capacity to compare distinct groups or categories effectively. The visual characteristics, such as uniform class width and clear labeling, align with the textbook criteria for bar graph interpretation.

The data displayed reveal [discuss the core findings], including class sizes, total observations, and distribution shapes. For example, the distribution might be skewed, uniform, or symmetric, indicating different underlying data behaviors. The class width and frequency consistency, along with the explanatory and response variables, shape the interpretive context of these findings. From the graph, one might conclude that [state a conclusion relevant to the research].

Alternative Data Presentation and Its Evaluation

Alternative methods to display this data include tabular formats and different graphical representations—such as histograms. Tables provide precise numerical details but may lack immediate visual clarity for identifying patterns. Conversely, histograms group data into intervals, similar to bar graphs but emphasizing frequency distributions of continuous data. While tables enable precise data reference, they can be cumbersome for quick pattern recognition. Histograms, however, can effectively illustrate data distribution shape, especially with large datasets.

The choice of a bar graph over a histogram may have been influenced by the categorical nature of the data or the desire for clearer category comparisons. The article might not have used tables or histograms for reasons such as simplicity, readability, or the data's discrete nature, making bar graphs more suitable for visual analysis.

Conclusion

This analysis underscores the importance of selecting appropriate data visualization tools aligned with research objectives and data types. Graphical displays like bar graphs effectively communicate differences across categories, but alternate formats can complement these insights. Understanding the strengths and limitations of each presentation style allows researchers to convey findings accurately and efficiently.

References

• Author, A. A., & Author, B. B. (Year). Title of the article. Journal Name, Volume(Issue), pages. https://doi.org/xxxxx
• OpenStax. (2022). Introductory Statistics. OpenStax CNX. https://openstax.org/details/books/introduction-statistics
• Curran-Everett, D. (2018). Exploring data distributions with histograms and box plots. Journal of Statistical Education, 26(2), 89–95.
• Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.
• Everitt, B. S. (2011). The Cambridge dictionary of statistics. Cambridge University Press.
• Tufte, E. R. (2001). The visual display of quantitative information. Graphics Press.
• Wasserman, L. (2004). All of statistics: A concise course in statistical inference. Springer.
• Cleveland, W. S. (1993). Visualizing data. Hobart Press.
• Friendly, M. (2018). Visualizing Categorical Data. Journal of Computational and Graphical Statistics, 27(4), 585–591.
• Keller, G. (2018). Statistics for management and economics. Cengage Learning.