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Comparative analysis of graduate statistics department using perception based ranking and research based ranking

O'Neill, Cameron (2023) Comparative analysis of graduate statistics department using perception based ranking and research based ranking. Master's Thesis, University of Pittsburgh. (Unpublished)

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University rankings have become an important part of the admissions processes and their audience has grown substantially over the last two decades. Yet there is still a lack of cover- age for graduate programs outside of business, law and medical school. One of the eminent rankings is the U.S. News & World Report, which has begun ranking graduate programs through peer assessment survey data which relies heavily on institutional reputation. The purpose of the study was to estimate the difference between a perception-based ranking measured through the USNWR rankings and a research-based ranking measured through Google Scholar metrics for 96 graduate statistics department within the United States. Ad- ditionally, the researcher sought to examine the underlying bias that might be present in the two rankings. A research rank statistic was generated for each department based off the mean of the normalized Google Scholar metrics for each professor within their department. Lastly, a bootstrap sample was conducted and was used to calculate the possible ranges of values departments could take. This was used to determine if a department deviates measurably between its research rank and perception-based rank. The results showed there is a measurable difference between the perception-based ranking and the research-based ranking.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
O'Neill, Cameroncjo38@pitt.educjo38
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMentch, Lucaslkm31@pitt.edulkm31
Committee MemberCheng, Yuyucheng@pitt.eduyucheng
Committee MemberChen, Kehuikhchen@pitt.edukhchen
Date: 11 May 2023
Date Type: Publication
Defense Date: 23 March 2023
Approval Date: 11 May 2023
Submission Date: 5 April 2023
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 83
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Statistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: graduate department ranking, research based ranking, perception ranking, U.S. News & World Report graduate statistics ranking
Date Deposited: 11 May 2023 19:38
Last Modified: 11 May 2023 19:38


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