Biostat 202B - UCLA (Winter 2018)


  • Instructor : Donatello Telesca
  • Lecture: WM 1:00 pm to 2:50 am- PUB HLT 51-279
  • Office Hours: TBD
  • Teaching Assistant:  TBD

Homework

  • HW 1 [Due 1/17]
  • HW 2 [Due 1/22]
  • HW 3 [Due 1/31]
  • HW 4 [Due 2/07]
  • HW 5 [Due 2/21]
  • HW 6 [Due 2/28]
  • HW 7 [Due 3/07]
  • HW 8 [Due 3/14]

Schedule of Lectures

  • (1/08) Introduction - Inferential Principles 
  • (1/10) Large Sample Theory
  • (1/15) No Class - MLK Jr. Holiday
  • (1/17) Large Sample Theory [HW 1 due]
  • (1/22) Large Sample Theory
  • (1/24)  [HW 2 due]
  • (1/29) 
  • (1/31) [HW 3 due]
  • (2/05) 
  • (2/07) [HW 4 due]
  • (2/12) Midterm
  • (2/14)
  • (2/19) No Class - Presidents Day Holiday
  • (2/21)  [HW 5 due]
  • (2/26) 
  • (2/28) [HW 6 due]
  • (3/05) 
  • (3/07) [HW 7 due]
  • (3/12) 
  • (3/14) [HW 8 due]

Coursework
8 HW Assignments 20%  
Midterm (02/12) 30%
Final (03/23) 50%


Reading List

(Recommended Textbooks)

  • G Casella and RL Berger. Statistical Inference. Second Edition. Duxbury. [Required]
  • JB Kadane. Principles of Uncertainty. CRC Press [A good base reference for Bayesian Inference]
  • T Ferguson. A Course in Large Sample Theory. Chapman & Hall. [Contained volume on asymptotics]
  • AW Van der Vaart. Asymptotic Statistics. [Advanced asymptotics]
  • CP Robert. The Bayesian Choice. [Advanced Bayesian Theory]


(Journal Articles and other Miscellaneous References)

[MLE History]

  • Aldrich J (1997) R.A. Fisher and the Making of Maximum Likelihood 1912-1922. Statistical Science, Vol 12, No 3.  pp 162-176.

[Hypothesis Testing and Philosophy of Science] 

  • Mayo, D. and Spanos, A. (2006). Severe testing as a basic concept in a Neyman-Pearson philosophy of induction. British Journal for the Philosophy of Science, 57, pp 323–357.
  • Popper, K. (1959). The Logic of Scientific Discovery. Basic Books, New York.
  • Howson, C. and Urbach, P. (2005). Scientific Reasoning: The Bayesian Approach. 3rd ed. Open Court, Chicago, IL.
  • Jeffreys, H. (1939). Theory of Probability. 1st ed. Cambridge University Press, Cambridge.

[Critiques of P-values as Measures of Evidence]

  • Berger JO and Selke T (1987). Testing a point null hypothesis: The irreconciliability of p values and evidence. JASA, Vol.82, 397, pp 112-122.
  • Johnson VE (2013). Revised Standard for Statistical Evidence. PNAS, Vol 110, No.48, pp 19313-19317.

Computing
Recommended computing for Biostat 202B will be based on the R programming language.
For more information please visit (http://cran.r-project.org/). A recommended platform for R programming and analysis is RStudio (https://www.rstudio.com/).