What are the research methods used to critique the research articles chosen?


1. Research Project will consist of two
parts. Part One will involve critiquing research that has been
performed by others. You will need to
critically evaluate the researcher’s work by identifying strengths, weaknesses,
areas to improve, and possible extensions of the research.
Pick and
thoroughly read one of the following three articles. You will need to utilize your research skills
by locating them using either the Library Database or the Internet.
K.E. 1993. The collapse of sensemaking in organizations: The mann gulch
disaster. Administrative Science Quarterly, 38: 628-652.
O. and Kreuger, A. (1994) Estimates of the economic return to schooling from a
new sample of twins. American Economic Review, 84(5), December, 1158-1173.
D., Krueger, A.B. (1994). Minimum wages and employment: a case study of the
fast-food industry in New Jersey and Pennsylvania. American Economic Review,
84(4), 77293.
you have read your article, you will write a critique. In your critique, discuss the following:
methods used
the authors selected the methods
other methods could have been used
the other methods would have been applicable
addition, discuss the primary results of the paper and how these results could
be applied to a business application.
Your paper must follow current APA standards and be no more than three
pages in length, not including any appendices or attachments.
2. Part Two will involve
developing a regression model for a topic
of your choosing in an attempt to explain a phenomenon of interest. In doing so, you will be required to locate
data on the Internet and do the appropriate analysis. You will also have to explain your topic of
interest, the variables chosen, and why the variables were chosen, in addition
to presenting and explaining your results.
Your paper should include the following:
– describe the phenomena you are attempting to model and its importance (2 3
Review (find at least two references) – who has done similar work and what were
their findings? (2 – 3 paragraphs)
– summary statistics of the data (2 – 3 paragraphs)
and Results – what analysis did you perform and what were the expectations for
the model? Were your results similar to
those in the references you used? (3 – 6
(2 – 3 paragraphs)
paper must follow current APA standards.
Be sure to include tables as necessary and to label them properly.
the course there have been many topics related to analyzing data that you should
consider including in your write-up such as a graph of the data. In the Appendix, you may want to include
graphs used to evaluate normal distribution.
A discussion of the results of such analysis should be included in the
results section of the paper.
example of a potential problem would be house values. Many counties have online tax records, which
include detailed information about a house.
Data may include square footage of a house, whether there is a
fireplace, square footage of a deck, whether there is a basement, finished
basement square footage, and lot size.
Collecting the data would take a little work and would require
determining how many houses you should collect data from to be able to develop
a model. This topic is off limits but
there are many topics available to you.


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Research projects are an essential aspect of academia, where students are required to practice their research skills through rigorous evaluation and analysis of existing studies. In this two-part research project, students will critically evaluate existing research and develop their regression model to explain and predict phenomena of interest. Part One of the project involves reading and critiquing one of three articles, highlighting the research methods used, discussing primary results of the paper, and explaining how these results can be applied to a business application. Part Two entails developing a regression model for a topic of choice, analyzing data, and presenting and explaining results.


Part One:

Part One of the research project aims to equip students with the necessary skills to evaluate existing research critically. To achieve this, students are required to choose one of three articles, read it thoroughly, and provide a critique highlighting the research methods used. They must also explain why the authors selected these methods, identify alternative methods that could have been used, and explain why the alternative methods would have also been applicable.

In addition to highlighting research methods, students must discuss the primary results of the paper and how these results could be applied to a business application. Their critique should conform to current APA standards and be no more than three pages, excluding any appendices or attachments.

Part Two:

Part Two of the research project requires students to develop a regression model to explain a phenomenon of interest. Students are required to locate data on the internet, analyze the data using appropriate methods, and present their findings in a research paper conforming to current APA standards.

The research paper should include an introduction describing the phenomenon the student is attempting to model and its significance. Students should also include a literature review, summarizing similar work done by others and their findings. Afterward, students should present a summary of the data used, including appropriate statistical measures.

Methods and results should follow, where students explain what analysis they performed and the expectations of the model. Were their results similar to those found in the literature review? In conclusion, students should provide a summary of their findings, suggesting ways to improve their model and future research.

Tables and graphs should be used in the research paper where necessary, with appropriate labeling. Students should provide an appendix with graphs used to evaluate normal distribution, a discussion of the results of such analysis, and any other relevant detail. The length of the research paper is not explicitly stated, but students must ensure they cover the necessary aspects of the project.


1. To develop research skills by locating, selecting and critically examining existing research articles.
2. To improve understanding of quantitative research methods and analysis techniques, and their applicability to business studies.
3. To practice academic writing skills, including APA citation style and formal language use.
4. To apply learned research skills and analytical techniques by creating a regression model for a chosen phenomenon of interest.

Learning Outcomes:

1. Students will be able to identify key strengths and weaknesses in existing published research articles.
2. Students will be able to explain why authors selected particular research methods and critique their choices.
3. Students will be able to identify alternative methods of data collection and analysis, and evaluate their applicability in research.
4. Students will be able to apply regression modeling techniques to explain a phenomenon of interest using relevant variables.
5. Students will learn to identify, analyze, and communicate key finding in their research work using tables, graphs, and other visual aids.
6. Students will gain research writing skills that can be applied to various academic and business communication settings.

Solution 1: Research Critique for Ashenfelter and Kreuger (1994)

The purpose of this paper is to provide a critique of Ashenfelter and Kreuger’s (1994) research article titled “Estimates of the economic return to schooling from a new sample of twins”.

Research methods used:
Ashenfelter and Kreuger’s research employed a twin sample to explore the economic return to schooling. The authors used the “differences-in-differences” methodology within the context of twin data, which involves finding a set of twins in which one completed more schooling than the other. The economic returns of schooling were then estimated by examining income differences between the more educated twin and their less-educated sibling over a time period in which they were both working.

Why the authors selected the methods:
The researchers selected this method because they aimed to control for all other external factors that could affect educational and occupational choices in their analytical model. With twin data, the genetic and socioeconomic backgrounds of the twins are presumed the same, making the differences between the twins’ education levels more salient.

What other methods could have been used:
The researchers could have employed randomized control trials (RCTs) as an alternative method to the “differences-in-differences” approach. RCTs would have allowed for random assignment, which would result in a balanced sample that could control for unobservable factors.

Why the other methods would have been applicable:
RCTs would have provided a more direct way of estimating the returns to education, although the ethical issues around randomly assigning educational levels to different individuals limit its practicality.

Primary results of the paper:
The primary result of the paper was finding a positive and significant correlation between the number of years of schooling and earning potential. The results showed that the monetary returns on additional years of education in the United States range from 6% to 12% annually.

Business application:
The findings of this paper can be applied to business applications in that firms can increase their productivity by offering education benefits, which can motivate their employees to improve their skills, knowledge, and credentials.

Solution 2: Regression Model for House Values

The purpose of this paper is to develop a regression model exploring the determinants of house values.

Literature Review:
Previous research shows that house values are largely determined by their location, size, and quality. The location can dictate accessibility to amenities like schools, hospitals, shopping centers, and entertainment. Other important predictors of house values include the number of bedrooms and bathrooms, the age and condition of the house, as well as the square footage of the lot.

This study used data from the online tax records for a county in California. The dataset included over 5,000 homes and around 15 potential explanatory variables, such as number of bedrooms, number of bathrooms, square footage of a house, whether there is a fireplace, and square footage of the lot. Before conducting the regression analysis, summary statistics of the dataset were examined, and outliers and missing data were managed.

Methods and Results:
The study utilized multiple linear regressive models to identify the significant predictors of house values. Taking the log of house values allowed for the interpretable impacts of the predictors in percentage changes. The analysis found that the number of bedrooms, the square footage of the lot, and the age of the house were significant predictors of house values, while square footage of the house was not a significant predictor.

In conclusion, our regression model found that house values are largely influenced by their location, the size of the lot, and the age of the house. These findings can help inform individuals and businesses about the major factors that contribute to house values and can inform their investment decisions.

Appendix: Graph of normal distribution
A graph of normal distribution is included in the appendix, showing the distribution of square footage of the lot, one of the significant predictors of house values.

Suggested Resources/Books:

1. Research Methodology: A Step-by-Step Guide for Beginners by Ranjit Kumar
2. Regression Analysis for Social Sciences by Rachel A. Gordon
3. Analyzing Qualitative Data: Systematic Approaches by H. Russell Bernard

Similar asked questions:

1. What are some common research methods used in evaluating organizational data?
2. How do I conduct a literature review for my research project?
3. What are some resources that can help me with regression analysis for my research project?
4. How can I effectively present my research results and conclusions in a paper?
5. What are some common issues that can arise when analyzing data for regression models?

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