Search
Search Funnelback University
- Refined by:
- Date: 2017
21 -
30 of
39
search results for TALK:PC53 20 |u:www.statslab.cam.ac.uk
where 0
match all words and 39
match some words.
Results that match 1 of 2 words
-
14. Lecture 15. Hypothesis testing in the linear model ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-15-linear-hypotheses-4.pdf6 Mar 2017: x 4 507.9 127.0 1.17 0.354. Residuals 20 2170.1 108.5. The p-value is 0.35, and so there is no evidence for a difference -
6. Lecture 7. Simple Hypotheses Lecture 7. Simple Hypotheses ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-07-simple-hypotheses-4.pdf6 Feb 2017: 20 is known. We want to find. the best size α test of H0 :µ=µ0 against H1 :µ=µ1, where µ0 and µ1 are knownfixed values with µ1 > µ0. -
15. Lecture 16. Linear model examples, and ’rules of ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-16-linear-examples.pdf6 Mar 2017: We expect 20 sixes, and so the difference between observed and expected is10. -
15. Lecture 16. Linear model examples, and ’rules of ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-16-linear-examples-4.pdf6 Mar 2017: We expect 20 sixes, and so the difference between observed and expected is10. -
The 1-2 model
www.statslab.cam.ac.uk/~grg/papers/conm14020.pdf18 Aug 2017: 17]), and this transformationgreatly facilitates its analysis. The above Ising model may be regarded as a special case of the eight-vertexmodel of Lin and Wu [20]. ... Commun. Probab. 19 (2014), no. 23, 8, DOI 10.1214/ECP.v19-3105. MR3197119[20] K. -
NEW FRONTIERS IN RANDOM GEOMETRY (RaG)EP/I03372X/1 REPORT 1/7/16 – ...
www.statslab.cam.ac.uk/~grg/rag-reports/report2017.pdf23 Oct 2017: 20. Random walks on the random graph, Nathanael Berestycki, EyalLubetzky, Yuval Peres, Allan Sly, Annals of Probability. ... Grimmett, Z.Li, European Journal of Combinatorics 20 (2013), Paper P47, 14 pp. -
0. Statistics 1B Statistics 1B 1 (1–1) 0. Lecture ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-01-intro-prob.pdf18 Jan 2017: Y (x, y ). =X. x. [Y. fY |X (y | x ). ]fX (x ) =. X. x fX (x ). Lecture 1. Introduction and probability review 20 (1–1). ... 12. Lecture 1. Introduction and probability review 31 (1–1). 1. Introduction and probability review 1.20. -
0. Statistics 1B Statistics 1B 1 (1–1) 0. Lecture ...
www.statslab.cam.ac.uk/Dept/People/djsteaching/S1B-17-01-intro-prob-4.pdf17 Jan 2017: Yx fX,Y (x, y ). =. Xx. [. YfY |X (y | x ). ]fX (x ) =. Xx fX (x ). Lecture 1. Introduction and probability review 20 (1–1). ... 12. Lecture 1. Introduction and probability review 31 (1–1). 1. Introduction and probability review 1.20. -
SELF-AVOIDING WALKS AND AMENABILITY GEOFFREY R. GRIMMETT AND…
www.statslab.cam.ac.uk/~grg/papers/new10.pdf3 Jul 2017: In summary,. {e1,e2} ={〈1,s1t 〉,〈1,st〉. }, {g1,g2} =. {〈1,s1t2〉,〈1,st2〉. }. 20 GEOFFREY R. ... Amer. Math. Soc. 369 (2017), 5961–5980.[20] , Self-avoiding walks and connective constants, (2017), http://arxiv.org/abs/1704. -
Strong law of large numbers for the capacity of ...
www.statslab.cam.ac.uk/~ps422/wiener7.pdf22 Dec 2017: 20. Proof of Lemma 3.8. We first extend the definition of the τi and Ai to negative indices:. ... C. (n exp(λ. L) exp. (c ε. 2n. E[Y 20]. Lε. )).
Search history
Recently clicked results
Recently clicked results
Your click history is empty.
Recent searches
Recent searches
Your search history is empty.