-- Mathlib/Probability/StrongLaw.lean
theorem sum_prob_mem_Ioc_le {X : Ω → ℝ} (hint : Integrable X) (hnonneg : 0 ≤ X) {K : ℕ} {N : ℕ}
    (hKN : K ≤ N) :
    ∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc (j : ℝ) N} ≤ ENNReal.ofReal (𝔼[X] + 1)

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
I : ↑i ≤ ↑(i + 1)
⊢ (↑i + 1) * ∫ (x : ℝ) in ↑i..↑(i + 1), 1 ∂ρ ≤ ∫ (x : ℝ) in ↑i..↑(i + 1), x + 1 ∂ρ

Tactic:
simp_rw [intervalIntegral.integral_of_le I, ← integral_mul_left]

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
I : ↑i ≤ ↑(i + 1)
⊢ ∫ (a : ℝ) in Set.Ioc ↑i ↑(i + 1), (↑i + 1) * 1 ∂ρ ≤ ∫ (x : ℝ) in Set.Ioc ↑i ↑(i + 1), x + 1 ∂ρ

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
⊢ ∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc ↑j ↑N} ≤ ENNReal.ofReal ((∫ (a : Ω), X a) + 1)

Tactic:
let ρ : Measure ℝ := Measure.map X ℙ

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
⊢ ∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc ↑j ↑N} ≤ ENNReal.ofReal ((∫ (a : Ω), X a) + 1)

Proof state:
case hf
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
I : ↑i ≤ ↑(i + 1)
⊢ IntegrableOn (fun x => (↑i + 1) * 1) (Set.Ioc ↑i ↑(i + 1)) ρ

Tactic:
exact continuous_const.integrableOn_Ioc

Result:
no goals

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ (∫ (a : Ω), X a) + ∫ (x : ℝ) in 0 ..↑N, 1 ∂ρ ≤ (∫ (a : Ω), X a) + 1

Tactic:
refine add_le_add le_rfl ?_

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ ∫ (x : ℝ) in 0 ..↑N, 1 ∂ρ ≤ 1

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
k : ℕ
x✝ : k < N
⊢ IntervalIntegrable (fun x => x + 1) ρ ↑k ↑(k + 1)

Tactic:
exact (continuous_id.add continuous_const).intervalIntegrable _ _

Result:
no goals

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
⊢ ((↑i + 1) ⊓ ↑K) * ∫ (x : ℝ) in ↑i..↑i + 1, 1 ∂ρ ≤ (↑i + 1) * ∫ (x : ℝ) in ↑i..↑i + 1, 1 ∂ρ

Tactic:
refine mul_le_mul_of_nonneg_right (min_le_left _ _) ?_

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
⊢ 0 ≤ ∫ (x : ℝ) in ↑i..↑i + 1, 1 ∂ρ

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ ∑ x ∈ (range K).sigma fun a => Ico a N, ∫ (x : ℝ) in ↑x.snd..↑(x.snd + 1), 1 ∂ρ =
    ∑ x ∈ (range N).sigma fun a => range ((a + 1) ⊓ K), ∫ (x : ℝ) in ↑x.fst..↑(x.fst + 1), 1 ∂ρ

Tactic:
refine sum_nbij' (fun p ↦ ⟨p.2, p.1⟩) (fun p ↦ ⟨p.2, p.1⟩) ?_ ?_ ?_ ?_ ?_ <;>
  aesop (add simp Nat.lt_succ_iff)

Result:
no goals

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
A : ∑ j ∈ range K, ∫ (x : ℝ) in ↑j..↑N, 1 ∂ρ ≤ (∫ (a : Ω), X a) + 1
a b : ℝ
⊢ ℙ {ω | X ω ∈ Set.Ioc a b} = ℙ (X ⁻¹' Set.Ioc a b)

Tactic:
rfl

Result:
no goals

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
A : ∑ j ∈ range K, ∫ (x : ℝ) in ↑j..↑N, 1 ∂ρ ≤ (∫ (a : Ω), X a) + 1
B : ∀ (a b : ℝ), ℙ {ω | X ω ∈ Set.Ioc a b} = ENNReal.ofReal (∫ (x : ℝ) in Set.Ioc a b, 1 ∂ρ)
⊢ ∑ j ∈ range K, ENNReal.ofReal (∫ (x : ℝ) in Set.Ioc ↑j ↑N, 1 ∂ρ) =
    ENNReal.ofReal (∑ j ∈ range K, ∫ (x : ℝ) in Set.Ioc ↑j ↑N, 1 ∂ρ)

Tactic:
rw [ENNReal.ofReal_sum_of_nonneg]

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
A : ∑ j ∈ range K, ∫ (x : ℝ) in ↑j..↑N, 1 ∂ρ ≤ (∫ (a : Ω), X a) + 1
B : ∀ (a b : ℝ), ℙ {ω | X ω ∈ Set.Ioc a b} = ENNReal.ofReal (∫ (x : ℝ) in Set.Ioc a b, 1 ∂ρ)
⊢ ∀ i ∈ range K, 0 ≤ ∫ (x : ℝ) in Set.Ioc ↑i ↑N, 1 ∂ρ

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ ∑ i ∈ range N, ∫ (x : ℝ) in ↑i..↑(i + 1), x + 1 ∂ρ = ∫ (x : ℝ) in 0 ..↑N, x + 1 ∂ρ

Tactic:
rw [intervalIntegral.sum_integral_adjacent_intervals fun k _ => ?_]

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ ∫ (x : ℝ) in ↑0 ..↑N, x + 1 ∂ρ = ∫ (x : ℝ) in 0 ..↑N, x + 1 ∂ρ

Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
k : ℕ
x✝ : k < N
⊢ IntervalIntegrable (fun x => x + 1) ρ ↑k ↑(k + 1)

Proof state:
case h
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
I : ↑i ≤ ↑(i + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑i ↑(i + 1)
⊢ (↑i + 1) * 1 ≤ x + 1

Tactic:
simp only [Nat.cast_add, Nat.cast_one, Set.mem_Ioc] at hx

Result:
case h
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
i : ℕ
x✝ : i ∈ range N
I : ↑i ≤ ↑(i + 1)
x : ℝ
hx : ↑i < x ∧ x ≤ ↑i + 1
⊢ (↑i + 1) * 1 ≤ x + 1

Proof state:
case hg
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ IntervalIntegrable (fun x => 1) ρ 0 ↑N

Tactic:
exact continuous_const.intervalIntegrable _ _

Result:
no goals

Proof state:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
j : ℕ
hj : j ∈ range K
⊢ ∀ k ∈ Set.Ico j N, IntervalIntegrable (fun x => 1) ρ ↑k ↑(k + 1)

Tactic:
intro k _

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K N : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
j : ℕ
hj : j ∈ range K
k : ℕ
a✝ : k ∈ Set.Ico j N
⊢ IntervalIntegrable (fun x => 1) ρ ↑k ↑(k + 1)