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.
Grading
This activity will be graded based on the Week 3 Lab Rubric.
Outcomes
CO 1: Given scenarios supported by population data, apply sampling techniques and explain potential pitfalls and biases in data collection.
CO 2: Given datasets with qualitative and quantitative data, differentiate between the types of data and how they can be applied in statistical studies for everyday life.
bellow I is the article.