STATISTICS NOTES ON THE WEB

Penn State

• Penn State has a lot of online stat courses. This is a fantastic resource.
  Stat 200 Intro Stat
  Stat 414/415 Calculus based Intro to Probability and Math Stat
  Stat 461 ANOVA
  Stat 462 Regression
  Stat 464 Nonparametrics
  Stat 480 SAS
  Stat 481 SAS Intermediate
  Stat 482 SAS Advanced
  Stat 484 Topics in R
  Stat 485 Intermediate R
  Stat 500 Applied Stat
  Stat 501 Regression
  Stat 502 Analysis of Variance
  Stat 503 Design of Experiemnts
  Stat 504 Count Data
  Stat 505 Applied Multivariate Stat
  Stat 506 Sampling
  Stat 507 Epidemiological Methods
  Stat 509 Clinical Trials
  Stat 510 Time Series
  Stat 897D Data Mining/Stat Learning
  Stat 555 Stat Analysis of Genomic Data
  Stat 800 Intro to Applied Stat
  

Electronic Statistics text

• Electronic Statistics Book, from Dell. Applied Stat, design, multivariate, data mining, and more.
  http://www.statsoft.com/Textbook
• Marco Taboga. Title: Lectures on probability theory and mathematical statistics. Third edition. Looks good.
  https://www.statlect.com/

Electronic Statistics text

• Hossein Pishro-Nik. Title: Introduction to Probability & Statistics
  Looks like a good math stat book. Includes some videos.
  https://www.probabilitycourse.com/

Engineering Statistics Handbook

• Engineering Statistics Handbook. Lots of topics.
  http://www.itl.nist.gov/div898/handbook/

Statistical Analysis Handbook

• Statistical Analysis Handbook - (c) 2015 Dr M J de Smith
  http://www.statsref.com/HTML/

Medical Stat terminology

• Study Design 101. Intro to medical statistical terminology.
  https://himmelfarb.gwu.edu/tutorials/studydesign101/

Marcel Finan

• Marcel Finan. Arkansas Tech Univ. He has prepared extensive quality notes on SOA actuarial exams P, FM, MFE, MLC, and C. Huge amount of work. Thanks.
  http://faculty.atu.edu/mfinan/actuaries.html

Daniel Hall

• Daniel Hall. U of Georgia. Lots of notes on courses Regression, Design, Multivariate, contegorical, etc.
  https://faculty.franklin.uga.edu/dhall/content/courses

Angelo Canty

• Angelo Canty course notes. McMaster University. Notes on Appl Regression, Computational Inference, Stat Foundations.
  http://ms.mcmaster.ca/canty/http://ms.mcmaster.ca/canty/

Richard Lockhart

• Richard Lockhart. Univ British Columbia. Course notes in time series, sampling, linear models, appl prob, stoch processess, multivariate, math stat.
  http://people.stat.sfu.ca/~lockhart/Teaching/Teaching.html#nav

Karen Buro



• Dr. Karen Buro. MacEwan University.
  Count Data, Regression, Anova.
  https://academic.macewan.ca/burok/

Davar Khoshnevisan. U of Utah.



• http://www.math.utah.edu/~davar/lecture-notes.html

The Analysis Factor



• The Analysis Factor is a collection of resources, mainly free, some requiring sign-up, some not, by a team of statistical consultants, led by Karen Grace-Martin. note especially the Statistical Resources by Topic in lower right corner. The articles can generally be viewed without sign-up, and are very good.
  http://www.theanalysisfactor.com/

Miscellaneous

• Cross Validated is a site where people pose [research/conceptual] statistics questions and others respond. Nice to know such a site exists. It's interesting to search for your topic of interest.
  http://stats.stackexchange.com/
• Introducing Monte Carlo Methods with R, slides by Christian P. Robert and George Casella. 239 pp.
  http://www.stat.ufl.edu/archived/casella/ShortCourse/MCMC-UseR.pdf
• Peter McCullagh notes on Cumulants, 6 pp.
  http://www.stat.uchicago.edu/~pmcc/courses/stat306/cumulants.pdf
• Probability Notes by Peter Cameron, Queen Mary University of London, 86 pp., intro calculus based math stat course.
  http://www.maths.qmul.ac.uk/~pjc/notes/prob.pdf
• John Braun. Univ of British Columbia. Naive data Analysis. Grad level.
  http://www.stats.uwo.ca/faculty/braun/ss9924/additionalnotes/naiveSmoothing.pdf
• Applied Statistical Methods. Larry Winner. University of Florida
  http://www.stat.ufl.edu/~winner/statnotescomp/appstat.pdf
• Survival Analysis. Eric Wolsztynski & Jian Huang. University College Cork, Ireland.
  http://euclid.ucc.ie/pages/staff/Eric/st3054/st3054_slides.pdf
• Econometrics. Bruce E. Hansen. University of Wisconsin. Book manuscript.
  http://www.ssc.wisc.edu/~bhansen/econometrics/Econometrics.pdf
• Nonparametrics. Philip Stark. U. California- Berkeley.
  https://www.stat.berkeley.edu/~stark/Teach/S240/Notes/index.htm
• Nonparametric Statistics. P. Breheny. U of Kentucky. Notes. Assignments. Data sets.
  https://web.as.uky.edu/statistics/users/pbreheny/621/F12/notes.html

Calculus Based Probability and Math Stat

• Mathematical statistics, Lecture notes by Janet Godolphin. University of Surrey.
  http://personal.maths.surrey.ac.uk/st/D.Terhesiu/ms237/ms237.pdf
• Probability Lecture Notes. Math 135. UCDavis. Janko Gravner. Math Stat plus Markov chains. Looks v. good.
  https://www.math.ucdavis.edu/~gravner/MAT135A/resources/lecturenotes.pdf
• The Analysis of Data: Part 1 (Probabiblity). Guy Lebanon. Amazon.
  http://theanalysisofdata.com/probability/
• Probability for Data Science, By Ani Adhikari and Jim Pitman. This is the textbook for the Probability for Data Science class at UC Berkeley.
  https://textbook.prob140.org/

Multivariate Statistics

• Multivariate Statistics. 3rd Web Edition. David W. Stockburger, Missouri State University
  http://www.psychstat.missouristate.edu/multibook/mlt00.htm
• Multivariate Statistics. Doug Wiens. U of Alberta.
  http://www.mathstat.ualberta.ca/~wiens/stat575/stat575.html

Regression

• Xing Su. Johns Hopkins. Regression and other topics. Includes R commands.
  http://sux13.github.io/DataScienceSpCourseNotes/
• Regression. Walter W. Piegorsch. University of Arizona. Slides and notes based on Kutner et al.
  http://math.arizona.edu/~piegorsch/571A/STAT571A.Fall14.html

Categorical Data Analysis

• Categorical Data Analysis. Alan Agresti. U of Florida
  http://www.stat.ufl.edu/~aa/sta4504/notes.pdf
• Categorical Data Analysis. Christopher Adolph. University of Washington (Seattle). Slides.
  http://faculty.washington.edu/cadolph/mle/topic1.p.pdf

Inference

• Inference. Larry Wasserman. CMU.
  http://www.stat.cmu.edu/~larry/=stat705/
• Jeff Hart's notes on Chapters 6-10 of Casella and Berger's Inference book.
  http://www.stat.tamu.edu/~hart/611/611.html

Sampling

• Sampling. Kristofer Jennings Purdue.
  http://www.stat.purdue.edu/~jennings/stat522/
• Sampling. Shalab. IIT (Kanpur)
  http://home.iitk.ac.in/~shalab/course1.htm
• Sampling. Carl Schwartz. Simon Fraser Univ.
  http://people.stat.sfu.ca/~cschwarz/Stat-650/Notes/PDFbigbook-R/R-part004.pdf

Measure Theoretic Probability

• "Random" site from Univ of Alabama, Huntsville. Devoted to probability and math stat.
  http://www.math.uah.edu/stat/
• Measure Theoretic Probability. Amir Dembo.
  http://statweb.stanford.edu/~adembo/stat-310a/lnotes.pdf
• Richard Bass notes on Grad Probability, undergrad probability, stochastic processes, etc.
  http://bass.math.uconn.edu/lecture.html

Time Series

• Time Series Analysis, Anna Mikusheva, MIT.
  http://ocw.mit.edu/courses/economics/14-384-time-series-analysis-fall-2013/lecture-notes/
• Time Series. Eric Wolsztynski. University College Cork, Ireland
  http://euclid.ucc.ie/pages/staff/Eric/st4064/ST6006/ST6006_TSA_notes.pdf
• Time series. Bartlett. U. Cal. Berkeley.
  http://www.stat.berkeley.edu/~bartlett/courses/153-fall2010/

Design of Experiments

• Statistical Design, slides by George Casella. 190 pp.
  http://www.stat.ufl.edu/archived/casella/ShortCourse/SDSC11-1.pdf
• Design of Experiments. Gary Oehlert. U of Minnesota. Book.
  http://users.stat.umn.edu/~gary/book/fcdae.pdf
• Design of Experiments. John Grego. U of South Carolina.
  http://people.stat.sc.edu/grego/courses/stat506/
• Design of Experiments. Jeff Wu. Georgia Tech.
  http://www2.isye.gatech.edu/~jeffwu/isye6413/

Stochastic Processes

• Introduction to Stochastic Processes. Gordan Zitkovic. The University of Texas at Austin
  https://www.ma.utexas.edu/users/gordanz/notes/introduction_to_stochastic_processes.pdf
• Notes on Stochastic Processes. Kiyoshi Igusa. Brandeis University.
  http://people.brandeis.edu/~igusa/Math56F06/Math56a_lectures.pdf
• Lecture Notes on Stochastic Processes. Frank Noé, Bettina Keller and Jan-Hendrik Prinz, 2013.
  http://www.mi.fu-berlin.de/wiki/pub/CompMolBio/MarkovKetten15/stochastic_processes_2011.pdf