1、了解 Bernoulli 概型，熟练掌握二项分布、Poisson 分布； 2、熟练掌握均匀分布、正态分布和指数分布及其性质； 3、熟记二项分布、泊松分布、均匀分布的数学期望和方差；

1、理解总体、个体和样本的概念； 2、了解经验分布函数和直方图的作法，知道格林汶科定理； 3、理解样本均值、样本方差和样本矩的概念并会计算；

1.(每题2分,共10分)判断题(若正确,则在题前的括号中打√;否则,打): (a)()若合式公式A是永真式当且仅当合式公式B是永真式,则AB是永真式。 (b)()若合式公式A是可满足的,则~A是不可满足的。 (c)()v((,x)y~(,y)是可满足的 (d)()设P是一个由P系统增加单个合式公式pq作为公理所得到的系统,则P是协调的

Syntax Formation Rules for P The The Axiomatic Structure of P Theorems and Derived Rules

Substitutivity of Equivalence Let A,M and N be wffs and let AMN be the result of replacing M by N at zero or more occurrences (henceforth called designate occurrences) of M in A. 1. AMN is a wff. 2. If |= M ≡ N then |= A ≡ AMN

Axiom Schemata for F Axiom Schema 1 A ∨ A ⊃ A Axiom Schema 2 A ⊃ (B ∨ A) Axiom Schema 3 A ⊃ B ⊃ (C ∨ A ⊃ (B ∨ C)) Axiom Schema 4 ∀xA ⊃ Sxt A where t is a term free for the individual variable x in A Axiom Schema 5 ∀x(A ∨ B) ⊃ (A ∨ ∀xB) provided that x is not free in A

Interpretation An interpretation I of F is , where D is a non-empty set called the domain of individuals. I0 is a mapping defined on the constants of F satisfying 1. If c is an individual constant, then I0(c) ∈ D. 2. If f n is an n-ary function constant, then I0(f n) : Dn → D

Two forms of Completeness Theorem Let Γ be a set of wffs. The following parts are equivalent. If Γ |= A then Γ ` A If Γ is consistent, then Γ is satisfiable

第4.1节 数理统计学中的基本概念 第4.2节 分布密度的近似求法 第4.3节 期望与方差的点估计 第4.4节 期望、方差的区间估计及Excel实现 第4.5节 点估计法

北方工业大学：《概率论与数理统计》课程教学资源（PPT课件讲稿）第二章 随机变量及其分布