Milton Friedman Papers 1931-2006

Total Page:16

File Type:pdf, Size:1020Kb

Milton Friedman Papers 1931-2006 http://oac.cdlib.org/findaid/ark:/13030/tf7t1nb2hx Online items available Register of the Milton Friedman Papers 1931-2006 Processed by Linda Bernard, Dana M. Harris, and Elizabeth Konzak Hoover Institution Archives Stanford University Stanford, California 94305-6010 Phone: (650) 723-3563 Fax: (650) 725-3445 Email: [email protected] URL: http://www.hoover.org/library-and-archives © 1997, 2008 Hoover Institution Archives. All rights reserved. Register of the Milton Friedman 77011 1 Papers 1931-2006 Register of the Milton Friedman Papers 1931-1991 Hoover Institution Archives Stanford University Stanford, California Contact Information Hoover Institution Archives Stanford University Stanford, California 94305-6010 Phone: (650) 723-3563 Fax: (650) 725-3445 Email: [email protected] URL: http://www.hoover.org/library-and-archives/ Processed by: Linda Bernard, Dana M. Harris, and Elizabeth Konzak Date Completed: 1992, revised 2008 Encoded by: Brooke Dykman Dockter and Elizabeth Konzak © 1997, 2008 Hoover Institution Archives. All rights reserved. Descriptive Summary Title: Milton Friedman papers Date (inclusive): 1931-2006 Collection number: 77011 Creator: Friedman, Milton, 1912-2006 Creator: Friedman, Rose D. Physical Description: 228 manuscript boxes, 2 oversize boxes, 4 card file boxes, 1 slide box, 1 envelope(94 linear feet) Repository: Hoover Institution Archives Stanford, California 94305-6010 Abstract: Speeches and writings, correspondence, notes, statistics, printed matter, sound recordings, videotapes, and photographs, relating to economic theory, economic conditions in the United States, and governmental economic policy. Digitized copies of many of the sound and video recordings in this collection, as well as some of Friedman's writings, are available at http://hoohila.stanford.edu/friedman/ . Physical location: Hoover Institution Archives Language: English. Access Collection is open for research. The Hoover Institution Archives only allows access to copies of audiovisual items. To listen to sound recordings or to view videos or films during your visit, please contact the Archives at least two working days before your arrival. We will then advise you of the accessibility of the material you wish to see or hear. Please note that not all audiovisual material is immediately accessible. Publication Rights For copyright status, please contact the Hoover Institution Archives. Digitized materials are protected by copyright laws and are provided for educational and research purposes only. Any infringing use may be subject to disciplinary action and/or civil or criminal liability as provided by law. If you believe you are the rights holder and object to Hoover's use of a digitized item, please contact [email protected]. Preferred Citation Register of the Milton Friedman 77011 2 Papers 1931-2006 [Identification of item], Milton Friedman papers, [Box number], Hoover Institution Archives. Acquisition Information First acquired by the Hoover Institution Archives in 1977, the collection includes additions from the 1980s until 2007 in boxes 109-112 and a large increment in boxes 113-235 acquired in 2008. Alternative Form Available Also available on microfilm (226 reels). Accruals Materials may have been added to the collection since this finding aid was prepared. To determine if this has occurred, find the collection in Stanford University's online catalog Socrates at http://library.stanford.edu/webcat . Materials have been added to the collection if the number of boxes listed in Socrates is larger than the number of boxes listed in this finding aid. 1912, July Born, Brooklyn, New York 31 1932 B.A., Rutgers University 1933 M.A., University of Chicago 1934-1935 Research assistant, Social Science Research Committee, University of Chicago 1935-1937 Associate economist, National Resources Committee, Washington, D.C. 1937-1940 Lecturer, Columbia University 1937-1946, Member, Research Staff, National Bureau of Economic Research, New York 1948-1981 1938 Married Rose Director 1940-1941 Visiting professor of economics, University of Wisconsin 1941-1943 Principal economist, Division of Tax Research, U.S. Treasury Department 1942 Professor, United States Department of Agriculture Graduate School, Washington, D.C. 1943 Author (with Carl S. Shoup and Ruth P. Mack), Taxing to Prevent Inflation 1943-1945 Associate director, Statistical Research Group, Division of War Research, Columbia University 1945 Author (with Simon S. Kuznets), Income from Independent Professional Practice 1945-1946 Associate professor of economics and statistics, University of Minnesota 1946 Ph.D., Columbia University 1946-1948 Associate professor of economics, University of Chicago 1948 Author (with Harold A. Freeman, Frederic Mosteller, W. Allen Wallis), Sampling Inspection 1948-1982 Professor of economics, University of Chicago 1950 Consultant, Economic Cooperation Administration, Office of the United States Special Representative in Europe, Paris 1953 Author, Essays in Positive Economics 1956-1979 Council of Academic Advisers, American Enterprise Institute 1957 Author, A Theory of the Consumption Function 1960 Author, A Program for Monetary Stability 1962 Author, Price Theory: A Provisional Text Author (with Rose D. Friedman), Capitalism and Freedom 1963 Author (with Anna J. Schwartz), A Monetary History of the United States, 1867-1960 Author, Inflation: Causes and Consequences 1968 Author, Dollars and Deficits: Inflation, Monetary Policy and the Balance of Payments 1968-1994 Advisory Board, Journal of Money, Credit, and Banking 1969 Author, The Optimum Quantity of Money and Other Essays 1969-1970 Member, The President's Commission on an All-Volunteer Armed Force 1970 Author (with Anna J. Schwartz), Monetary Statistics of the United States 1972 Author, An Economist's Protest: Columns on Political Economy 1973 Member, The President's Commission on White House Fellows 1975 Author, There Is no Such Thing as a Free Lunch 1976 Author, Price Theory Recipient, Nobel Prize in Economics 1977- Senior research fellow, Hoover Institution on War, Revolution and Peace, Stanford University, California 1978 Author, Tax Limitation, Inflation and the Role of Government 1980 Author (with Rose D. Friedman), Free to Choose, and presenter of a ten-part TV series on PBS of the same title. 1981-1988 Member, The President's Economic Policy Advisory Board Register of the Milton Friedman 77011 3 Papers 1931-2006 1982 Author (with Anna J. Schwartz), Monetary Trends in the U.S. and the United Kingdom 1983 Author, Bright Promises, Dismal Performance: An Economist's Protest 1983- Professor emeritus, University of Chicago 1984 Author (with Rose D. Friedman), Tyranny of the Status Quo, and presenter of a three part PBS television program of the same title. 1986 Awarded the Grand Cordon of the First Class Order of the Sacred Treasure (Japanese Government) 1988 Awarded the National Medal of Science Awarded the Presidential Medal of Freedom 1992 Author Money Mischief: Episodes in Monetary History. Author (with Thomas S. Szasz) Edited and with a Preface by Arnold S. Trebach and Kevin B. Zeese. Friedman and Szasz on Liberty and Drugs: Essays on the Free Market and Prohibition 1992- Active Member, Academia Scientiarum et Artium Europaea (European Academy of Sciences and Arts) 1993- Founding Member, National Coalition for Drug Policy Change 1996- Chairman, Board of Directors, Milton and Rose D. Friedman Foundation to promote public understanding of the need for major reform in K-12 education and the role that competition through educational choice can play in achieving that reform 1998 Author (with Rose D. Friedman) Two Lucky People: Memoirs 1999- Member, Advisory Board, California Parents for Educational Choice 2006 Died Scope and Content of Collection The Milton Friedman papers include a variety of materials relating to economic theory, economic conditions in the United States, and governmental economic policy. Friedman interacted with a wide a network of academics, economists, and politicians, with whom he corresponded frequently. The papers display his thoughts and expertise in extensive correspondence, speeches and writings, collected research materials, statistics, printed materials, and photographs, as well as audio and video recordings. Indexing Terms The following terms have been used to index the description of this collection in the library's online public access catalog. Economics. United States--Politics and government. United States--Economic conditions. United States--Economic policy. Reagan, Ronald. Phonotapes. Video tapes. Economists. Boxes: 1-5 Biographical File, 1931-1980 Scope and Content Note Articles, clippings, awards, bibliographies, biographies, school and employment records, and resolutions, arranged alphabetically by physical form Articles and clippings on Milton Friedman Box 1, Folder 1 1950-1963 Box 1, Folder 2 1963-1969 Box 1, Folder 3 1964 Box 1, Folder 4 1965-1966 Box 1, Folder 5 1967 Box 1, Folder 6 1968 Box 2, Folder 1 1969 Box 2, Folder 2 1970 Box 2, Folder 3 1970-1972 Box 2, Folder 4 1971 Box 2, Folder 5 1972-1973 Register of the Milton Friedman 77011 4 Papers 1931-2006 Biographical File, 1931-1980 Box 2, Folder 6 1973-1974 Box 3, Folder 1 1974-1976 Box 3, Folder 2 1975-1976 Box 3, Folder 3 1976 Box 4, Folder 1-2 1977 Box 4, Folder 3 1978 Box 4, Folder 4 1978-1980 Box 4, Folder 5 1979 Box 5, Folder 1 Awards Box 5, Folder 2 Bibliographies Box 5, Folder 3 Biographies Employment records Box 5, Folder 4 Civil Service Commission, 1936-1940 Box
Recommended publications
  • Statistics Making an Impact
    John Pullinger J. R. Statist. Soc. A (2013) 176, Part 4, pp. 819–839 Statistics making an impact John Pullinger House of Commons Library, London, UK [The address of the President, delivered to The Royal Statistical Society on Wednesday, June 26th, 2013] Summary. Statistics provides a special kind of understanding that enables well-informed deci- sions. As citizens and consumers we are faced with an array of choices. Statistics can help us to choose well. Our statistical brains need to be nurtured: we can all learn and practise some simple rules of statistical thinking. To understand how statistics can play a bigger part in our lives today we can draw inspiration from the founders of the Royal Statistical Society. Although in today’s world the information landscape is confused, there is an opportunity for statistics that is there to be seized.This calls for us to celebrate the discipline of statistics, to show confidence in our profession, to use statistics in the public interest and to champion statistical education. The Royal Statistical Society has a vital role to play. Keywords: Chartered Statistician; Citizenship; Economic growth; Evidence; ‘getstats’; Justice; Open data; Public good; The state; Wise choices 1. Introduction Dictionaries trace the source of the word statistics from the Latin ‘status’, the state, to the Italian ‘statista’, one skilled in statecraft, and on to the German ‘Statistik’, the science dealing with data about the condition of a state or community. The Oxford English Dictionary brings ‘statistics’ into English in 1787. Florence Nightingale held that ‘the thoughts and purpose of the Deity are only to be discovered by the statistical study of natural phenomena:::the application of the results of such study [is] the religious duty of man’ (Pearson, 1924).
    [Show full text]
  • School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK
    School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK Discussion Papers in Economics and Econometrics Professor A L Bowley’s Theory of the Representative Method John Aldrich No. 0801 This paper is available on our website http://www.socsci.soton.ac.uk/economics/Research/Discussion_Papers ISSN 0966-4246 Key names: Arthur L. Bowley, F. Y. Edgeworth, , R. A. Fisher, Adolph Jensen, J. M. Keynes, Jerzy Neyman, Karl Pearson, G. U. Yule. Keywords: History of Statistics, Sampling theory, Bayesian inference. Professor A. L. Bowley’s Theory of the Representative Method * John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract Arthur. L. Bowley (1869-1957) first advocated the use of surveys–the “representative method”–in 1906 and started to conduct surveys of economic and social conditions in 1912. Bowley’s 1926 memorandum for the International Statistical Institute on the “Measurement of the precision attained in sampling” was the first large-scale theoretical treatment of sample surveys as he conducted them. This paper examines Bowley’s arguments in the context of the statistical inference theory of the time. The great influence on Bowley’s conception of statistical inference was F. Y. Edgeworth but by 1926 R. A. Fisher was on the scene and was attacking Bayesian methods and promoting a replacement of his own. Bowley defended his Bayesian method against Fisher and against Jerzy Neyman when the latter put forward his concept of a confidence interval and applied it to the representative method. * Based on a talk given at the Sample Surveys and Bayesian Statistics Conference, Southampton, August 2008.
    [Show full text]
  • History of Health Statistics
    certain gambling problems [e.g. Pacioli (1494), Car- Health Statistics, History dano (1539), and Forestani (1603)] which were first of solved definitively by Pierre de Fermat (1601–1665) and Blaise Pascal (1623–1662). These efforts gave rise to the mathematical basis of probability theory, The field of statistics in the twentieth century statistical distribution functions (see Sampling Dis- (see Statistics, Overview) encompasses four major tributions), and statistical inference. areas; (i) the theory of probability and mathematical The analysis of uncertainty and errors of mea- statistics; (ii) the analysis of uncertainty and errors surement had its foundations in the field of astron- of measurement (see Measurement Error in omy which, from antiquity until the eighteenth cen- Epidemiologic Studies); (iii) design of experiments tury, was the dominant area for use of numerical (see Experimental Design) and sample surveys; information based on the most precise measure- and (iv) the collection, summarization, display, ments that the technologies of the times permit- and interpretation of observational data (see ted. The fallibility of their observations was evident Observational Study). These four areas are clearly to early astronomers, who took the “best” obser- interrelated and have evolved interactively over the vation when several were taken, the “best” being centuries. The first two areas are well covered assessed by such criteria as the quality of obser- in many histories of mathematical statistics while vational conditions, the fame of the observer, etc. the third area, being essentially a twentieth- But, gradually an appreciation for averaging observa- century development, has not yet been adequately tions developed and various techniques for fitting the summarized.
    [Show full text]
  • Professor A. L. Bowley's Theory of the Representative Method *
    Key names: Arthur L. Bowley, F. Y. Edgeworth, , R. A. Fisher, Adolph Jensen, J. M. Keynes, Jerzy Neyman, Karl Pearson, G. U. Yule. Keywords: History of Statistics, Sampling theory, Bayesian inference. Professor A. L. Bowley’s Theory of the Representative Method * John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract Arthur. L. Bowley (1869-1957) first advocated the use of surveys–the “representative method”–in 1906 and started to conduct surveys of economic and social conditions in 1912. Bowley’s 1926 memorandum for the International Statistical Institute on the “Measurement of the precision attained in sampling” was the first large-scale theoretical treatment of sample surveys as he conducted them. This paper examines Bowley’s arguments in the context of the statistical inference theory of the time. The great influence on Bowley’s conception of statistical inference was F. Y. Edgeworth but by 1926 R. A. Fisher was on the scene and was attacking Bayesian methods and promoting a replacement of his own. Bowley defended his Bayesian method against Fisher and against Jerzy Neyman when the latter put forward his concept of a confidence interval and applied it to the representative method. * Based on a talk given at the Sample Surveys and Bayesian Statistics Conference, Southampton, August 2008. I am grateful to Andrew Dale for his comments on an earlier draft. December 2008 1 Introduction “I think that if practical statistics has acquired something valuable in the represen- tative method, this is primarily due to Professor A.
    [Show full text]
  • David Donoho's Gauss Award
    Volume 47 • Issue 7 IMS Bulletin October/November 2018 David Donoho’s Gauss Award David Donoho is the recipient of the 2018 Carl Friedrich Gauss Prize, the major prize CONTENTS in applied mathematics awarded jointly by the International Mathematical Union 1 Donoho receives Gauss (IMU) and the German Mathematical Union. Award at ICM Bestowed every four years since 2006, the prize 2–3 Members’ news: COPSS honors scientists whose mathematical research Awards: Richard Samworth, has generated important applications beyond the Bin Yu, Susan Murphy; CR Rao, mathematical field—in technology, in business, Herman Chernoff, DJ Finney or in people’s everyday lives—and this award 4 Interview: Richard Samworth acknowledges David’s impact on a whole genera- tion of mathematical scientists. 5 COPSS Award nominations David Donoho was commended by the IMU David Donoho. Photo: IMU 6 How to nominate a Fellow President Shigefumi Mori for his “fundamental 7 Other IMS Award contribution to mathematics” during the opening ceremony of ICM 2018 in Rio de nominations Janeiro, Brazil. After the award was announced, David spoke of the joy he has experienced when 9 More nominations: Parzen Prize, Newbold Prize theories he has developed earlier in his career are applied to everyday life. “There are things I’ve done decades ago, and when I see things happen in the real world, it makes 10 Report on WNAR/IMS me so proud. The power we have in moving the world gives me a great deal of satisfac- Meeting tion in my career choice.” 11 Student Puzzle Corner He said that a career in math is not limited to pure math, and publication in 12 Recent papers: Annals of journals.
    [Show full text]
  • 45 June 2008 Editor: David W
    International Society for Clinical News Biostatistics Number 45 June 2008 Editor: David W. Warne Executive Committee 2007-08 Editorial Officers It’s not long until 2008’s conference in Copenhagen, Denmark, and this issue contains lots of information about President: Emmanuel Lesaffre (B) the conference from Philip Hougaard and Bjarne Nielsen. Vice-President: Norbert Victor (D) Next year’s conference will take place in Prague in Secretary: Harbajan Chadha-Boreham (CH) the Czech Republic and there’s an update from Zdenek Valenta. Treasurer: Koos Zwinderman (NL) John Whitehead has prepared a list of positions which will need to be filled for 2009-10, so please do consider Members volunteering to serve on the ExCom. The deadline is the end News Editor: David W. Warne (CH) of August. As announced at last year’s AGM and in the Webmaster: Bjarne Nielsen (DK) December News, we are planning to revise the Constitution: the proposed changes were placed on the Society’s website for 2007-08: Adriano Decarli (I) consultation and review from January-February 2008 and KyungMann Kim (USA) were generally considered to be a good idea. They will be put Rumana Omar (UK) to the membership for approval later this year at the same time as the postal vote for the ExCom. Catherine Quantin (F) Thanks to the contributors to this News: Emmanuel Jenö Reiczigel (H) Lesaffre, Harbajan Chadha-Boreham, Julia Singer, KyungMann Kim, Mike Campbell and Rumana Omar, Koos Marie Reilly (S) Zwinderman, John Whitehead, Sylvain Larroque, Bjarne Martin Schumacher (D) Nielsen, Philip Hougaard, Andrew Dunning, Ewa Kawalec, Vana Sypsa (GR) Zdenek Valenta and the 6 book reviewers.
    [Show full text]
  • 84483 Stats News May.Indd
    statistical society of australia incorporated newsletter May 2005 Number 111 Registered by Australia Post Publication No. NBH3503 issn 0314-6820 ‘Truth, damned truth and statistics’ It’s not every day that we can see the head of Australia’s official statistical agency in action under the scrutiny of Australia’s political press gallery. Dennis confidently faced the blowtorch for the Australian Bureau of Statistics – and the profession – in March. His talk kicks off ABS’s centenary celebrations and gave him an opportunity to air several issues. He argued that ABS has a strong and key role in a democracy by providing impartial, relevant and comprehensive information to inform public debate and decision making. As he said, ‘I am always gratified to see public debate that uses ABS statistics without qualification or question. For the fact is, the public and Australia can have strong faith in their official statistics. The same cannot be said for many other countries where pressure and influence can impact on what is collected, how it is collected and how it is released.’ Later, he said, ‘Because of this trust [in ABS’s data], discussions can focus on what the statistics mean for policy rather than on the integrity of the statistics themselves’. The reliability of ABS statistics was raised in the questions that followed his talk because the Reserve Bank had just raised interest rates for the first time after a long period, and in doing so publicly doubted the ABS statistics that the economy was already slowing. Dennis Dennis Trewin, the Australian Statistician, addresses the National Press Club displayed a keen grasp of the issues, In this issue Editorial ...........................................4 ANZJS Discussion Paper ................7 ACSPRI Winter Program ..............10 Statistics and Schooling ................
    [Show full text]
  • AP® Statistics
    About AP Statistics AP® Statistics Teacher’s Guide Michael Legacy Greenhill School Addison, Texas ™® connect to college success www.collegeboard.com i 72770-00003 • AP Statistics TG • INDC2 • Fonts: Helvetica, Minion, Serifa, Univers, Universal Greek & Math, Wingdings • D1 5/6/08 RI60953 • D1-1 5/30/08 RI60953 • D1-2 6/17/08 RI60953 • D1-3 7/10/08 RI60953 • D2 8/22/08 RI60953 • D3 9/19/08 RI60953 • D5 10/1/08 RI60953 • D6 10/7/08 RI60953 The College Board: Connecting Students to College Success The College Board is a not-for-profit membership association whose mission is to connect students to college success and opportunity. Founded in 1900, the association is composed of more than 5,400 schools, colleges, universities, and other educational organizations. Each year, the College Board serves seven million students and their parents, 23,000 high schools, and 3,500 colleges through major programs and services in college admissions, guidance, assessment, financial aid, enrollment, and teaching and learning. Among its best-known programs are the SAT®, the PSAT/NMSQT®, and the Advanced Placement Program® (AP®). The College Board is committed to the principles of excellence and equity, and that commitment is embodied in all of its programs, services, activities, and concerns. For further information visit www.collegeboard.com. © 2008 The College Board. All rights reserved. College Board, Advanced Placement Program, AP, AP Central, AP Vertical Teams, connect to college success, Pre-AP, SAT, and the acorn logo are registered trademarks of the College Board. AP Potential is a trademark owned by the College Board.
    [Show full text]
  • Statistical Modeling: the Two Cultures
    Statistical Science 2001, Vol. 16, No. 3, 199–231 Statistical Modeling: The Two Cultures Leo Breiman Abstract. There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated bya given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical communityhas been committed to the almost exclusive use of data models. This commit- ment has led to irrelevant theory, questionable conclusions, and has kept statisticians from working on a large range of interesting current prob- lems. Algorithmic modeling, both in theoryand practice, has developed rapidlyin fields outside statistics. It can be used both on large complex data sets and as a more accurate and informative alternative to data modeling on smaller data sets. If our goal as a field is to use data to solve problems, then we need to move awayfrom exclusive dependence on data models and adopt a more diverse set of tools. 1. INTRODUCTION The values of the parameters are estimated from Statistics starts with data. Think of the data as the data and the model then used for information being generated bya black box in which a vector of and/or prediction. Thus the black box is filled in like input variables x (independent variables) go in one this: side, and on the other side the response variables y linear regression come out. Inside the black box, nature functions to y logistic regression x associate the predictor variables with the response Cox model variables, so the picture is like this: Model validation.
    [Show full text]
  • Model Selection and Model Averaging
    P1: SFK/UKS P2: SFK/UKS QC: SFK/UKS T1: SFK CUUK244-Claeskens 978-0-521-85225-8 January 13, 2008 8:41 Model Selection and Model Averaging Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a suitable model is central to all statistical work with data. Selecting the variables for use in a regression model is one important example. The past two decades have seen rapid advances both in our ability to fit models and in the theoretical understanding of model selection needed to harness this ability, yet this book is the first to provide a synthesis of research from this active field, and it contains much material previously difficult or impossible to find. In addition, it gives practical advice to the researcher confronted with conflicting results. Model choice criteria are explained, discussed and compared, including Akaike’s information criterion AIC, the Bayesian information criterion BIC and the focused information criterion FIC. Importantly, the uncertainties involved with model selec- tion are addressed, with discussions of frequentist and Bayesian methods. Finally, model averaging schemes, which combine the strength of several candidate models, are presented. Worked examples on real data are complemented by derivations that provide deeper insight into the methodology. Exercises, both theoretical and data-based, guide the reader to familiarity with the methods. All data analyses are compati- ble with open-source R software, and data sets and R code are available from a companion website.
    [Show full text]
  • Measuring the Human Gut Microbiome: New Tools and Non Alcoholic Fatty Liver Disease
    Western University Scholarship@Western Electronic Thesis and Dissertation Repository 6-13-2016 12:00 AM Measuring the human gut microbiome: new tools and non alcoholic fatty liver disease Ruth G. Wong The University of Western Ontario Supervisor Dr. Gregory B. Gloor The University of Western Ontario Graduate Program in Biochemistry A thesis submitted in partial fulfillment of the equirr ements for the degree in Master of Science © Ruth G. Wong 2016 Follow this and additional works at: https://ir.lib.uwo.ca/etd Part of the Bioinformatics Commons Recommended Citation Wong, Ruth G., "Measuring the human gut microbiome: new tools and non alcoholic fatty liver disease" (2016). Electronic Thesis and Dissertation Repository. 3839. https://ir.lib.uwo.ca/etd/3839 This Dissertation/Thesis is brought to you for free and open access by Scholarship@Western. It has been accepted for inclusion in Electronic Thesis and Dissertation Repository by an authorized administrator of Scholarship@Western. For more information, please contact [email protected]. Abstract With the advent of next generation DNA and RNA sequencing, scientists can obtain a more comprehensive snapshot of the bacterial communities on the human body (known as the ‘human microbiome’), leading to information about the bacterial composition, what genes are present, and what proteins are produced. The scientific community is in a phase of developing the experiments and accompanying statistical techniques to investigate the mechanisms by which the human microbiome affects health and disease. In this thesis, I explore alternatives to the standard weighted and unweighted UniFrac distance metric that measure the difference between microbiome samples. These alternative weightings allow for the extraction of subtle differences between samples and identification of outliers not visible with traditional methods.
    [Show full text]
  • The University of North Carolina System Author(S): E
    Statistical Training and Research: The University of North Carolina System Author(s): E. Shepley Nourse, Bernard G. Greenberg, Gertrude M. Cox, David D. Mason, James E. Grizzle, Norman L. Johnson, Lyle V. Jones, John Monroe, Gordon D. Simons, Jr. Source: International Statistical Review / Revue Internationale de Statistique, Vol. 46, No. 2 (Aug., 1978), pp. 171-207 Published by: International Statistical Institute (ISI) Stable URL: http://www.jstor.org/stable/1402812 Accessed: 01/06/2010 14:44 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=isi. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. International Statistical Institute (ISI) is collaborating with JSTOR to digitize, preserve and extend access to International Statistical Review / Revue Internationale de Statistique.
    [Show full text]