# Search for tag: "comma"

#### CL - Implication

We derive the implication rule using the rules introduced last week.

From  Haoran Peng on October 20th, 2020 0 likes 293 plays 0

#### CL - Lecture 4.i - Reduction 1

We use the rules to reduce a sequent to a conjunction of simpler sequents. In this example we find that the expression asserted by the sequent is a tautology — it is equivalent to the empty…

From  Claudia-Elena Chirita on October 15th, 2020 0 likes 347 plays 0

#### CL - Lecture 4.j - Reduction 2

We use the rules to reduce a sequent to a conjunction of simple sequents, sequents that only mentions propositional letters, with no connectives, and no repetitions — in this example, we find…

From  Claudia-Elena Chirita on October 15th, 2020 0 likes 305 plays 0

#### CL - Lecture 4.f - Sequents 1

We interpret additional predicates before the turnstile. These simply express validity in a sub-universe. This means that for any sound rule the corresponding rule with additional predicates is…

From  Claudia-Elena Chirita on October 15th, 2020 0 likes 373 plays 0

#### CL - Lecture 4.e - Sequents 0

The following videos introduce sequents, a far-reaching generalisation of the idea underlying Aristotle's propositions. We have already discussed the introduction of multiple antecedents…

From  Claudia-Elena Chirita on October 15th, 2020 0 likes 345 plays 0

#### 5.2-part4: Expected value, covariance, correlation of jointly distributed RV (exercises)

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From  Vesselin Velichkov on July 20th, 2020 0 likes 1 plays 0

#### 5.2-part3: Expected value, covariance, correlation of jointly distributed RV (exercises)

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From  Vesselin Velichkov on July 20th, 2020 0 likes 1 plays 0

#### 5.2-part2: Expected value, covariance, correlation of jointly distributed RV (cont.)

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From  Vesselin Velichkov on July 20th, 2020 0 likes 2 plays 0

#### 5.2-part1: Expected value, covariance, correlation of jointly distributed RV

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From  Vesselin Velichkov on July 20th, 2020 0 likes 2 plays 0

#### 5.1-part2: Jointly distributed random variables: independence, conditional probability

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From  Vesselin Velichkov on July 20th, 2020 0 likes 3 plays 0

#### 5.1-part1: Jointly distributed random variables: JPMF, MPMF, JPDF, MPDF

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From  Vesselin Velichkov on July 20th, 2020 0 likes 1 plays 0

#### 4.4-part2: Exponential distribution: relation to Poisson distribution

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From  Vesselin Velichkov on July 20th, 2020 0 likes 1 plays 0

#### 3.4-part4: The Binomial probability distribution (exercises)

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From  Vesselin Velichkov on July 20th, 2020 0 likes 2 plays 0

#### 3.2-part3: PMF, CDF (exercises)

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From  Vesselin Velichkov on July 20th, 2020 0 likes 3 plays 0

#### 2.3-part3: Permutations and combinations (exercises)

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From  Vesselin Velichkov on July 19th, 2020 0 likes 1 plays 0

#### 2.3-part2: Permutations and combinations

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From  Vesselin Velichkov on July 19th, 2020 0 likes 1 plays 0