Search for tag: "assumption"

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15:30 USMR lecture 9 part 2 USMR lecture 9 part 2	USMR lecture 9 part 2 probability, odds, log odds usmr psychology ppls statistics rstats odds probability quality values competition hand observations side bin log infinity variance probabilty linear things bit outcome times assumption model From Martin Corley on November 15th, 2020 0 likes 29 plays 0 Course Code PSYL11053 Licence Type Creative Commons - Attribution Language English Date Created November 15th, 2020
22:57 RMS2 (20-21): 9.3 RMS2 (20-21): 9.3	RMS2 (20-21): 9.3 condition squares freedom levels degrees variance person factor error sums tests assumption designs interaction conditions measures things values term test From Thomas Booth on November 14th, 2020 0 likes 150 plays 0
04:13 CL - Lecture 4.h - Sequents 3 CL - Lecture 4.h - Sequents 3	CL - Lecture 4.h - Sequents 3 We can now give Gentzen's rules for ¬ ⋀ ⋁. inf1a introduction to computation informatics 1 computation and logic logic delta universe gamma rules rule deltas gammas thing adultery assumption bottom negation commerce lists times things head assets place brackets From Claudia-Elena Chirita on October 15th, 2020 0 likes 345 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
05:23 CL - Lecture 4a - Aristotle's Rules CL - Lecture 4a - Aristotle's Rules	CL - Lecture 4a - Aristotle's Rules Our first video is a recap of last week's materials. inf1a introduction to computation informatics 1 computation and logic aristotle syllogism things 's rules names column diagram forms positions syllogisms variables notation kind fact left idea venn yesterday simplicity assumption From Haoran Peng on October 11th, 2020 0 likes 523 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
03:22 CL - Lecture 3j - Aristotle's Syllogisms CL - Lecture 3j - Aristotle's Syllogisms	CL - Lecture 3j - Aristotle's Syllogisms We describe the traditional presentation of the syllogisms, and introduce Aristotle's existential assumption, on the basis of which he derives nine more syllogisms. These are not sound in our… inf1a introduction to computation informatics 1 computation and logic syllogism existential assumption rules logic aristotle assumption rule things srp conclusion p. bottom summary negations predicates syllogisms geeks fats pen srs proof fs From Haoran Peng on October 5th, 2020 0 likes 417 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
05:01 CL - Lecture 3g - Making more rules with… CL - Lecture 3g - Making more rules with contrapositions	CL - Lecture 3g - Making more rules with contrapositions Using meta-/object-level contrapositions, we can derive all 15 sound syllogisms from Barbara. inf1a introduction to computation informatics 1 computation and logic contraposition sound syllogism rule rules assumption assumptions conclusion b. scotland alcohol bottom thing things c. barbara positions control answer position level knots From Haoran Peng on October 3rd, 2020 0 likes 445 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
03:44 CL - Lecture 3e - Constructing a Counterexample CL - Lecture 3e - Constructing a Counterexample	CL - Lecture 3e - Constructing a Counterexample In the last video, we showed a rule is sound using Venn diagrams. In this video, we will again use Venn diagrams to construct counter-examples for unsound rules. inf1a introduction to computation informatics 1 computation and logic syllogism counter-example unsound model things kinds conclusion possibilities thing premises examples moment collection predicates b. assumption fall power letters cubed c. ice pay From Haoran Peng on October 3rd, 2020 0 likes 475 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
11:20 RMS2 (20-21) 4.3 RMS2 (20-21) 4.3	RMS2 (20-21) 4.3 Research Methods & Statistics 2 (20-21) Week 4 Lecture 3 multicollinearity predictors predictor regression model linear values errors outcome linearity vif assumption assumptions problem function plots performance context relation thing From Josiah King on September 18th, 2020 0 likes 283 plays 0 Licence Type All rights reserved The University of Edinburgh
07:44 RMS2 (20-21) 4.2 RMS2 (20-21) 4.2	RMS2 (20-21) 4.2 Research Methods & Statistics 2 (20-21) Week 4 Lecture 2 values variable transformation log function assumptions variables heteroscedasticity outcome residuals normality homoscedasticity errors regression assumption end skewness nonlinearity relations experience From Josiah King on September 18th, 2020 0 likes 277 plays 0 Licence Type All rights reserved The University of Edinburgh
21:46 RMS2 (20-21) 4.1 RMS2 (20-21) 4.1	RMS2 (20-21) 4.1 Research Methods & Statistics 2 (20-21) Week 4 Lecture 1 assumption linear regression test model errors values residuals assumptions homoscedasticity plot function variance normality linearity relationship plots independence violation distribution From Josiah King on September 18th, 2020 0 likes 299 plays 0 Licence Type All rights reserved The University of Edinburgh
19:54 Lecture 2 Part 2 Kaltura Capture recording -… Lecture 2 Part 2 Kaltura Capture recording - September 12th 2020, 4:02:30 pm	Lecture 2 Part 2 Kaltura Capture recording - September 12th 2020, 4:02:30 pm Lecture 2 part 2 rationalists lecture 2 part 2 week 2 god existence spinoza concept essence substance power argument contradiction nature definition proposition leibnitz square demonstration beings idea substances assumption toddlers From Pauline Phemister on September 12th, 2020 0 likes 17 plays 0 Course Code PHIL10086 Licence Type Creative Commons - Attribution Date Created September 12th, 2020
12:26 dapR2 (20-21): 9.1 dapR2 (20-21): 9.1	dapR2 (20-21): 9.1 Data Analysis in Psychology in R 2, 2020/21.Week 9Lecture 1 predictors multicollinearity predictor regression linear model outcome assumptions vif values errors linearity assumption problem function performance context relation thing models From Aja Murray on September 12th, 2020 0 likes 106 plays 0 Licence Type All rights reserved The University of Edinburgh
08:08 dapR2 (20-21): 4.4 dapR2 (20-21): 4.4	dapR2 (20-21): 4.4 values variable transformation log function assumptions variables heteroscedasticity outcome residuals normality homoscedasticity errors regression assumption end skewness nonlinearity relations experience From Aja Murray on September 12th, 2020 0 likes 173 plays 0
22:40 dapR2 (20-21): 4.3 dapR2 (20-21): 4.3	dapR2 (20-21): 4.3 assumption linear regression model test errors values assumptions residuals homoscedasticity plot function variance normality linearity relationship plots independence violation predictor From Aja Murray on September 12th, 2020 0 likes 294 plays 0
12:25 3.6-part2: Applications of the Poisson… 3.6-part2: Applications of the Poisson distribution	3.6-part2: Applications of the Poisson distribution . ... delta interval poisson probability events distribution t. assumption alpha parameter process event calls occurrence expression ratio fact times assumptions proposition From Vesselin Velichkov on July 20th, 2020 0 likes 46 plays 0 Licence Type All rights reserved The University of Edinburgh
20:02 26a 26a	26a Stationary Processes and the Markov Assumption variables umbrella evidence rain model probability values yesterday parents slice assumption sequence boss variable distribution words likelihood transition process stuff From Alexandra Lascarides on July 17th, 2020 0 likes 2 plays 0 Licence Type All rights reserved The University of Edinburgh

Search for tag: "assumption"

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