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194. AU PUQ2 MarApr2017 06 100%

BRAND MOST USED BY DENTISTS www.colgateprofessional.com Active moderate or extensive caries lesions Active initial caries lesions BRAND MOST USED BY DENTISTS No active caries lesions www.colgateprofessional.com Based on steps 1 and 2, select the likelihood.

https://www.pdf-archive.com/2017/03/23/194-au-puq2-marapr2017-06/

23/03/2017 www.pdf-archive.com

sparse-inverse-covariance 95%

The problem is to maximize the log-likelihood log(det(Θ)) − tr(SΘ) − ρ||Θ||1 Over non negative definite matrices Θ.

https://www.pdf-archive.com/2017/01/19/sparse-inverse-covariance/

19/01/2017 www.pdf-archive.com

lec-15.6up 95%

(One flips or tosses a coin) What do we mean by the likelihood of tails is 50%?

https://www.pdf-archive.com/2016/03/09/lec-15-6up/

09/03/2016 www.pdf-archive.com

Stat 4202 Notes 92%

Statistics 4202 Lecture Notes Professor Chang SP17 February 27th, 2017 Section 12.6 Likelihood Ratio Tests Recall that NP lemma gave most powerful test when both the null and alternative hypotheses were simple.

https://www.pdf-archive.com/2017/03/05/stat-4202-notes/

05/03/2017 www.pdf-archive.com

MTH3260 Exam Sheet 88%

ε) = 0 n→∞ Strong Law of Large Numbers P(Sn /n → µ) = 1 Central Limit Theorem √ P( n(Sn /m − µ) 6 x) → P(σZ 6 x) Maximum Likelihood Estimation n Y L(Θ;

https://www.pdf-archive.com/2017/12/14/mth3260-exam-sheet/

14/12/2017 www.pdf-archive.com

Sub-Optimal as Optimal 87%

Bayes’ theorem says that the probability that a particular hypothesis is true given the data (the posterior probability) is equal to the probability that one would see those exact same data if the hypothesis were true (the likelihood) times the probability that the hypothesis is true (the prior probability), divided by that same product for all other possible hypotheses that could explain the data, i.e.

https://www.pdf-archive.com/2016/09/15/sub-optimal-as-optimal/

15/09/2016 www.pdf-archive.com

MORI - Leadership - Independence - September 2016 85%

All giving a voting intention and (9/10 or 10/10) likelihood to vote (at INDY4) Total (Weight ed) (x) Gender Male Female (a) (b) Employment status of respondent AGE 16-24 (c) 25-34 (d) 35-54 (e) 55 or more (f) Work Sector Working Working (full (partNot time) time) working Retired (g) (h) (i) (j) Public (l) Tenure Rent Owner council occup Housing Rented ied Assoc.

https://www.pdf-archive.com/2016/09/15/mori-leadership-independence-september-2016/

15/09/2016 www.pdf-archive.com

MORI - March 2017 - Independence - Brexit - Local Elections 84%

All giving a voting intention and (9/10 or 10/10) likelihood to vote (at INDY4) Total (Weight ed) (x) Gender Male (a) Female (b) Employment status of respondent AGE 16-24 (c) 25-34 (d) 35-54 (e) 55 or more (f) Work Sector Working Working (full (partNot time) time) working Retired (g) (h) (i) (j) Tenure Private /Selfempl -oyed (k) Public (l) Owner occup ied (m) Rent council Housing Rented Assoc.

https://www.pdf-archive.com/2017/03/13/mori-march-2017-independence-brexit-local-elections/

13/03/2017 www.pdf-archive.com

24-Agus Santoso 83%

PERBANDINGAN METODE KEMUNGKINAN MAKSIMUM DAN BAYES DALAM MENAKSIR KEMAMPUAN PESERTA TES PADA RANCANGAN TES ADAPTIF Agus Santoso Jurusan Statistik FMIPA Universitas Terbuka email:aguss@ut.ac.id ABSTRAK Penelitian ini bertujuan untuk membandingkan metode Kemungkinan Maksimum (Maximum Likelihood,) dan metode Bayes dalam menaksir kemampuan peserta pada rancangan tes adaptif.

https://www.pdf-archive.com/2011/12/05/24-agus-santoso/

05/12/2011 www.pdf-archive.com

HLM Likelihood 82%

1 2 3 4 5 6 7 8 RANK PAST WINNER NAME 2012 2011 2010 2009 2008 2007 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 - 1 1 1 1 1 1 - 1 2 1 1 1 1 1 1 - 1 2 3= 3= 5 6= 6= 6= 9= 9= 9= 9= 9= 9= 9= 9= 9= 18= 18= 18= 21= 21= 21= 24= 24= 24= 24= 24= 24= 24= 24= 24= 24= 34= 34= 34= 34= 34= 34= 40= 40= 40= 40= 40= 40= 40= Gorst-Williams, Jessica Farrow, Paul Coney, James Holt, Natalie Salmon, James Ellson, Andrew Lewis, Paul Salway, Jeff Atherton, Mark Cowie, Ian East, Saxon Gammell, Kara Milner, Leah Pridham, Helen Selby, Thomas Simon, Emma Wright, Melanie Budworth, David Prestridge, Jeff Shaw, Esther Davies, Madeleine Pow, Helen Womack, Stephen Bain, Simon Dyson, Richard Gompertz, Simon Norman, Tessa Reynard, Cherry Rice, Nick Shannon, Laura Thomas, Paul Thornill, Jo Walford, Janet Alexander, Ruth Bourke, Lorna Cumbo, Jo Phillips, James Thickett, Robert Thomas, Charlie Charles, James Colman, Elizabeth Howard, Laura Husband, John Jones, Rory Langston, Rob Martin, Natalie 9 TOTAL AWARDS WON 4 5 3 3 4 3 3 3 2 2 2 2 2 2 2 2 4 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10 11 RECENCY LIKELIHOOD SCORE WEIGHTING 1.0 0.7 1.0 1.0 0.7 0.8 0.8 0.8 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.5 0.8 0.8 0.8 0.7 0.7 0.7 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.8 0.8 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.7 0.7 0.7 0.7 400.0 333.3 300.0 300.0 266.7 250.0 250.0 250.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 166.7 166.7 166.7 133.3 133.3 133.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 83.3 83.3 83.3 83.3 83.3 83.3 66.7 66.7 66.7 66.7 66.7 66.7 66.7 40= 40= 40= 40= 40= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 79= 79= 79= 79= 79= 79= 79= 1 McDonald, Mairi Montagu-Smith, Nina Powley, Tanya Shepherd, Gary Whateley, Laura Colman, Liz Daley, James Flaherty, Sharon Insley, Jill Jones, Lee Lappin, John Lobo, Dylan MacGillivray, Lauren O'Connor, Rebecca Peston, Robert Ridge, Sophie Rowley, David Vincent, Matthew Butterworth, Myra Fitzsimmons, John Gallagher, Rosemary Gilmore, Grainne Goff, Sharleen Greenwood, John Hazell, Tony Levene, Tony Lewis, Martin McMillan, Paul Morris, Sylvia Quinton, Lucy Rouse, Lynn Salih, Chris Aiken, Adam Anker, Guy Judge, Dan Kassam, Isabelle Savage, Ralph Sawers, David Taylor, Margaret 2 - - 1 1 1 1 - 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0.7 0.7 0.3 0.7 0.7 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.3 0.3 0.3 0.3 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 66.7 66.7 66.7 66.7 66.7 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 16.7 16.7 16.7 16.7 16.7 16.7 16.7 3 4 5 6 7 8 9 10 11 What the table shows:

https://www.pdf-archive.com/2013/04/29/hlm-likelihood/

29/04/2013 www.pdf-archive.com

Winners - HLM 82%

1 RANK 1 2 3= 3= 5 6= 6= 6= 9= 9= 9= 9= 9= 9= 9= 9= 9= 18= 18= 18= 21= 21= 21= 24= 24= 24= 24= 24= 24= 24= 24= 24= 24= 34= 34= 34= 34= 34= 34= 40= 40= 40= 40= 40= 40= 40= 2 PAST WINNER NAME Gorst-Williams, Jessica Farrow, Paul Coney, James Holt, Natalie Salmon, James Ellson, Andrew Lewis, Paul Salway, Jeff Atherton, Mark Cowie, Ian East, Saxon Gammell, Kara Milner, Leah Pridham, Helen Selby, Thomas Simon, Emma Wright, Melanie Budworth, David Prestridge, Jeff Shaw, Esther Davies, Madeleine Pow, Helen Womack, Stephen Bain, Simon Dyson, Richard Gompertz, Simon Norman, Tessa Reynard, Cherry Rice, Nick Shannon, Laura Thomas, Paul Thornill, Jo Walford, Janet Alexander, Ruth Bourke, Lorna Cumbo, Jo Phillips, James Thickett, Robert Thomas, Charlie Charles, James Colman, Elizabeth Howard, Laura Husband, John Jones, Rory Langston, Rob Martin, Natalie 3 4 5 6 7 8 9 10 11 RECENCY SCORE LIKELIHOOD SCORE 1.0 0.7 1.0 1.0 0.7 0.8 0.8 0.8 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.5 0.8 0.8 0.8 0.7 0.7 0.7 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.8 0.8 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.7 0.7 0.7 0.7 400.0 333.3 300.0 300.0 266.7 250.0 250.0 250.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 166.7 166.7 166.7 133.3 133.3 133.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 83.3 83.3 83.3 83.3 83.3 83.3 66.7 66.7 66.7 66.7 66.7 66.7 66.7 2012 2011 2010 2009 2008 2007 TOTAL AWARDS WON 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 - 1 1 1 1 1 1 - 1 2 1 1 1 1 1 1 - 4 5 3 3 4 3 3 3 2 2 2 2 2 2 2 2 4 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 40= 40= 40= 40= 40= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 52= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 65= 79= 79= 79= 79= 79= 79= 79= 1 McDonald, Mairi Montagu-Smith, Nina Powley, Tanya Shepherd, Gary Whateley, Laura Colman, Liz Daley, James Flaherty, Sharon Insley, Jill Jones, Lee Lappin, John Lobo, Dylan MacGillivray, Lauren O'Connor, Rebecca Peston, Robert Ridge, Sophie Rowley, David Vincent, Matthew Butterworth, Myra Fitzsimmons, John Gallagher, Rosemary Gilmore, Grainne Goff, Sharleen Greenwood, John Hazell, Tony Levene, Tony Lewis, Martin McMillan, Paul Morris, Sylvia Quinton, Lucy Rouse, Lynn Salih, Chris Aiken, Adam Anker, Guy Judge, Dan Kassam, Isabelle Savage, Ralph Sawers, David Taylor, Margaret 2 - - 1 1 1 1 - 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 1 1 1 1 1 1 1 1 1 1 1 1 1 - 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0.7 0.7 0.3 0.7 0.7 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.3 0.3 0.3 0.3 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 66.7 66.7 66.7 66.7 66.7 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 33.3 16.7 16.7 16.7 16.7 16.7 16.7 16.7 3 4 5 6 7 8 9 10 11 What the table shows:

https://www.pdf-archive.com/2013/05/10/winners-hlm/

10/05/2013 www.pdf-archive.com

Big date 2015 draft agenda for event bright 80%

Big Data, Big Models, and Intractable Likelihood 12:10 – 13:40 Lunch (not provided) 13:40 – 14:20 John Geweke:

https://www.pdf-archive.com/2015/02/18/big-date-2015-draft-agenda-for-event-bright/

18/02/2015 www.pdf-archive.com

report 79%

10 4.3.1 Max-likelihood estimation .

https://www.pdf-archive.com/2016/06/06/report/

06/06/2016 www.pdf-archive.com

Fowler CA6 Stay Order 77%

(1) whether the State has a likelihood of * The Honorable Joseph M.

https://www.pdf-archive.com/2018/01/08/fowler-ca6-stay-order/

08/01/2018 www.pdf-archive.com

MORI GB Poll on EU membership June 2015 76%

All Total (Weighted ) Likelihood to vote Always usually depends (Q15a) Gender Age Always usually depends (Q15a) AND (10) 9/10 Absol like-utely Would NOT lihood certain (6 to 10) (7 to 10) (8 to 10) (9 to 10) vote Male Female 18-34 35-54 Unweighted Total 1005 868 742 698 856 837 810 758 65 501 504 233 Weighted Total 1005 365 55+ UnWgt Total Social Class 18-24 25-34 35-44 45-54 55-64 407 95 138 173 192 180 118 173 169 180 146 65+ 75+ AB C1 C2 DE 227 84 276 323 185 221 ABC1 C2DE 599 406 1005 Total 218 100 269 271 219 246 1005 855 723 678 839 813 787 738 73 489 516 291 349 364 540 465 Satisfied 435 43% 383 45% 335 46% 309 46% 389 46% 371 46% 363 46% 341 46% 21 29%s 229 47% 206 40% 118 41% 152 43% 166 45% 40 34%s 78 45% 77 45% 75 42% 59 40% 107 49% 46 130 112 46%s 48% 41% 100 46% 93 38% 242 45% 194 42% 423 42% Dissatisfied 461 46% 399 47% 328 45% 316 47% 377 45% 369 45% 356 45% 334 45% 35 48%s 218 45% 244 47% 139 48% 165 47% 158 43% 63 54%s 76 44% 73 43% 92 51% 71 49% 87 40% 41 119 126 41%s 44% 46% 95 44% 122 50% 244 45% 217 47% 475 47% Don't know 108 11% 74 9% 60 8% 54 8% 73 9% 72 9% 68 9% 63 9% 17 23%s 42 9% 66 13% 35 12% 33 9% 41 11% 15 13%s 20 11% 19 11% 13 7% 16 11% 25 11% 13 13%s 20 8% 34 12% 23 11% 31 12% 54 10% 54 12% 107 11% Net satisfied -26 -3% -16 -2% 7 1% -6 -1% 12 1% 2 * 6 1% 8 1% -14 -19%s 11 2% -37 -7% -21 -7% -13 -4% 8 2% -23 -20%s 3 1% 4 2% -17 -9% -12 -8% 20 9% 4 4%s 11 4% -14 -5% 5 2% -28 -12% -23 -5% -52 -5% Fieldwork dates :

https://www.pdf-archive.com/2016/09/15/mori-gb-poll-on-eu-membership-june-2015/

15/09/2016 www.pdf-archive.com

SonyTriceraPI 76%

When a plaintiff shows a reasonable likelihood of success on her copyright infringement claims, she is entitled to a rebuttable presumption of irreparable harm.

https://www.pdf-archive.com/2016/01/28/sonytricerapi/

28/01/2016 www.pdf-archive.com

testing-correlation-regime 75%

and 2) an increase in democratic characteristics within a regime will increase the probabilistic likelihood that an individual will be efficacious.

https://www.pdf-archive.com/2017/09/21/testing-correlation-regime/

21/09/2017 www.pdf-archive.com

8-antifraud-strategies 74%

We know from our own experience that the likelihood of a good customer to perform fraud is very small.

https://www.pdf-archive.com/2014/10/30/8-antifraud-strategies/

30/10/2014 www.pdf-archive.com

25-Agus Santoso 74%

Namun penerapan metode maximum likelihood untuk mengestimasi kemampuan peserta tes dan kriteria fungsi informasi maksimum untuk menampilkan butir soal berikutnya pada tes adaptif mengakibatkan butir soal yang diberikan kepada peserta tes mudah dikenali, khususnya pada urutan butir soal awal yang disajikan pada peserta tes Oleh karena itu diperlukan strategi pemilihan butir alternatif pada algoritma tes adaptif.

https://www.pdf-archive.com/2011/03/16/25-agus-santoso/

16/03/2011 www.pdf-archive.com

Feb3 DC Hearing 74%

In the weeks since President Trump signed the Executive 5 Order at issue here, six federal judges around the country 6 have enjoined or stayed parts of it in response to action by 7 particular plaintiffs, finding a likelihood of success on the 8 merits of the challenges.

https://www.pdf-archive.com/2017/02/10/feb3-dc-hearing/

10/02/2017 www.pdf-archive.com

Organic versus All Natural Labeling 73%

However, once a consumer established a history of buying a certain brand or product the likelihood of choosing a product solely based on its package claim was reduced.

https://www.pdf-archive.com/2016/05/23/organic-versus-all-natural-labeling/

23/05/2016 www.pdf-archive.com

17-35105 (1) 70%

Nevertheless, we hold that the Government has not shown a likelihood of success on the merits of its appeal, nor has it shown that failure to enter a stay would cause irreparable injury, and we therefore deny its emergency motion for a stay.

https://www.pdf-archive.com/2017/02/10/17-35105-1/

10/02/2017 www.pdf-archive.com

art 1 69%

This is concerning because stereotype threat has been shown to have ironic effects on performance and behavior, which inadvertently increase an individual’s likelihood of confirming the stereotype (e.g., Bosson, Haymovitz, &

https://www.pdf-archive.com/2017/12/22/art-1/

22/12/2017 www.pdf-archive.com

document 69%

Nevertheless, we hold that the Government has not shown a likelihood of success on the merits of its appeal, nor has it shown that failure to enter a stay would cause irreparable injury, and we therefore deny its emergency motion for a stay.

https://www.pdf-archive.com/2017/02/10/document/

09/02/2017 www.pdf-archive.com

Human Resource Managment cont'd 69%

Well developed, comprehensive HR policies reduce your risk for being sued by employees for discrimination or wrongful termination, and reduce the likelihood of losses if you are.

https://www.pdf-archive.com/2014/03/11/human-resource-managment-cont-d/

11/03/2014 www.pdf-archive.com