For all annotation, your final submission should include the:
• Completed Annotation in MS Words or Pdf format.
Your article annotation
mpleted Annotation in MS Words or Pdf format.
Your article annotation should have four sections as described below:
Section 1 – Article Information Marks: 1
1. Title of the Article
2. Name of the Author(s)
3. Source of the Article
a. Journal Name
b. Publication Details – Year, Volume, Issue, and page nos.
Section 2 – Preliminary Analysis (1 Paragraph). Marks: 2
1. Purpose of Research – summarize aim of the study and specific research objectives
2. Nature of Research – is the study exploratory, descriptive, causal?
3. Theoretical Framework – describe the model followed or proposed in the study
4. Conclusion – summarize the major findings of the study.
Section 3 – Methods & Empirics (3 Paragraphs). Marks: 3
1. Research Method – describe in detail the research method used in this study.
If the author(s) does not discuss the research method in detail, or the explanation is not clear from the article, please refer to external sources.
2. Data Collection
a. Identify the prime mode of data collection.
b. Describe the process of data collection.
c. Discuss the measuring instrument.
3. Sampling Technique
a. Identify the target population.
b. Describe the sampling technique.
c. Assess how well the sample represents the population.
4. Goodness of Measures & Analysis
a. Describe the efforts made by the researcher(s) to ensure reliability & validity of the study.
b. Describe the tools used for analyzing the data.
Section 4 – Critical Review (2 Paragraphs). Marks: 4
Use this space to note your overall evaluation of the article. In your opinion, how good this article was compared to other articles, either in the discipline/area, or in the same journal
5.Problem 4 (20 points). Consider the Newmarket 5K dataset. A dataset with certain rows deleted (where there was no Age
there was no Age and/or Sex entered) has been created. It is called Newmarket_Cleaned.csv.
Data file: Newmarket_Cleaned.csv
(Links to an external site.)
. Direct HTTP link: https://unh.box.com/shared/static/p8x4xlbean3rlslmfskfu74fe89yjui8.csv
Please use it for this problem. Consider the “Model 4” developed in class, which contained Age, Age^2, and Sex as independent variables. First re-create this model with the cleaned dataset (you will need to create the Age^2 column; you can verify your model summary against the one from class), and then proceed with this problem.
Make the necessary changes to the model to incorporate Year as a categorical explanatory variable (you may need to change how R interprets the variable, before running this model). Does the year of the race seem to be related to mean finishing time, after taking into account the other variables in Model 4? Use the 0.05 significance level. Explain your work/logic, and key output to support your answer.
Using the updated model, after accounting for age and sex, what is the expected difference in finishing times for runners from 2008 versus runners from 2004?
Using the updated model, after accounting for age and sex, what is the expected difference in finishing times for runners from 2014 versus 2011?
In the above, the directions are to treat Year as a categorical variable. Explain how the regression model would be different if it instead were treated as a numeric variable. What are the assumptions being made about the effect of Year in the two different approaches?