definition 11.6 Moments, variance, standard deviation
open in the book ·
parts/02-mathematical-methods/09-probability-statistics.tex:182
· p. 373
- ground object -- no derivation owed
Rests on
-
depends_on
proposition 11.5
Transfer, linearity, monotonicity
¶
-
depends_on
definition 11.4
Expectation
¶
-
depends_on
definition 7.45
Series
¶
- depends_on definition 7.2 Absolute value ¶
-
depends_on
definition 7.4
Convergence
¶
- depends_on definition 7.2 Absolute value ¶ ↺
-
depends_on
definition 11.3
Discrete random variable
¶
- depends_on definition 11.1 Discrete probability space ¶
-
depends_on
definition 7.45
Series
¶
-
depends_on
proposition 11.2
Elementary rules
¶
- depends_on definition 11.1 Discrete probability space ¶ ↺
- proves proof ch:09-probability-statistics@proof-1 ¶
- proves proof ch:09-probability-statistics@proof-2 ¶
-
depends_on
definition 11.4
Expectation
¶
Supports
-
depends_on
definition 11.11
Covariance and correlation
¶
- depends_on corollary 11.15 Bounds on the correlation coefficient ¶
-
depends_on
definition 11.16
Sample mean, variance and correlation
¶
- depends_on example 11.19 A counting measurement ¶
- depends_on example 11.31 A length measurement ¶
-
depends_on
proposition 11.17
Sampling identities
¶
- depends_on example 11.19 A counting measurement ¶ ↺
- depends_on example 11.31 A length measurement ¶ ↺
-
depends_on
lemma 11.63
Cauchy–Schwarz for random
variables
¶
- depends_on corollary 11.15 Bounds on the correlation coefficient ¶ ↺
- depends_on corollary 11.65 When the bound is attained ¶
-
depends_on
lemma A.199
The standardised third moment is at least
one
¶
- depends_on lemma A.200 Transform estimate ¶
-
depends_on
theorem 11.64
Cramér–Rao inequality
¶
- depends_on corollary 11.65 When the bound is attained ¶ ↺
- depends_on example 11.62 Information in a counting experiment ¶
-
depends_on
proposition 11.12
Bilinearity
¶
-
depends_on
example 11.18
Three standard discrete
distributions
¶
- depends_on example 11.19 A counting measurement ¶ ↺
-
depends_on
proposition 11.14
Independence implies zero covariance; the converse
fails
¶
- depends_on example 11.18 Three standard discrete distributions ¶ ↺
- depends_on proposition 11.17 Sampling identities ¶ ↺
- depends_on proposition 11.17 Sampling identities ¶ ↺
-
depends_on
example 11.18
Three standard discrete
distributions
¶
- depends_on definition 11.16 Sample mean, variance and correlation ¶ ↺
- depends_on example 11.18 Three standard discrete distributions ¶ ↺
- depends_on lemma 11.63 Cauchy–Schwarz for random variables ¶ ↺
-
depends_on
lemma 11.50
Markov and Chebyshev inequalities
¶
-
depends_on
corollary 11.51
Weak law of large numbers
¶
-
depends_on
theorem A.205
Weak law under integrability alone
¶
-
depends_on
lemma A.208
The three averages
¶
- depends_on corollary A.210 Uniform quadratic approximation on the $n^{-1/2}$ scale ¶
- depends_on lemma A.211 Root-$n$ localisation ¶
-
depends_on
lemma A.208
The three averages
¶
-
depends_on
theorem 11.67
Asymptotics of the MLE
¶
- depends_on proposition 11.72 Nuisance parameters cost information ¶
-
depends_on
theorem 11.88
Wilks
¶
- depends_on corollary 11.89 Degrees of freedom with nuisance parameters ¶
-
depends_on
theorem A.205
Weak law under integrability alone
¶
-
depends_on
theorem 11.101
Davies' bound
¶
- depends_on corollary 11.105 Trials factor at high significance ¶
- depends_on example 11.107 Degrading a local five sigma ¶
-
depends_on
corollary 11.51
Weak law of large numbers
¶
-
depends_on
proposition 11.7
Variance identity
¶
-
depends_on
proposition 11.10
What the mean and the median minimise
¶
- depends_on example 11.30 Exponential lifetimes ¶
-
depends_on
proposition 11.10
What the mean and the median minimise
¶
Neighborhood
Every logical edge within two steps of this node.
- declared and complete
- partly declared
- a check failed
- not graded
- declared in the source
- inferred from structure
Edges
| type | direction | node | provenance | where |
|---|---|---|---|---|
depends_on |
→ | Transfer, linearity, monotonicity | declared | parts/02-mathematical-methods/09-probability-statistics.tex:194 |
depends_on |
← | Covariance and correlation | declared | parts/02-mathematical-methods/09-probability-statistics.tex:325 |
depends_on |
← | Sample mean, variance and correlation | declared | parts/02-mathematical-methods/09-probability-statistics.tex:453 |
depends_on |
← | Three standard discrete distributions | declared | parts/02-mathematical-methods/09-probability-statistics.tex:523 |
depends_on |
← | Cauchy–Schwarz for random variables | declared | parts/02-mathematical-methods/09-probability-statistics.tex:1806 |
depends_on |
← | Markov and Chebyshev inequalities | declared | parts/02-mathematical-methods/09-probability-statistics.tex:1408 |
depends_on |
← | Variance identity | declared | parts/02-mathematical-methods/09-probability-statistics.tex:215 |