-- Mathlib/Probability/StrongLaw.lean
theorem sum_variance_truncation_le {X : Ω → ℝ} (hint : Integrable X) (hnonneg : 0 ≤ X) (K : ℕ) :
    ∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * 𝔼[truncation X j ^ 2] ≤ 2 * 𝔼[X]

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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ ∑ x ∈ (range K).sigma range, (↑x.fst ^ 2)⁻¹ * ∫ (x : ℝ) in ↑x.snd..↑(x.snd + 1), x ^ 2 ∂ρ =
    ∑ x ∈ (range K).sigma fun a => Ioo a K, (↑x.snd ^ 2)⁻¹ * ∫ (x : ℝ) in ↑x.fst..↑(x.fst + 1), x ^ 2 ∂ρ

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

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
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation X ↑j ^ 2) a ≤ 2 * ∫ (a : Ω), X a

Tactic:
set Y := fun n : ℕ => truncation X n

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation X ↑j ^ 2) a ≤ 2 * ∫ (a : Ω), X a

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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
⊢ 2 / (↑k + 1) * ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂ρ

Tactic:
have Ik : (k : ℝ) ≤ (k + 1 : ℕ) := by simp

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ 2 / (↑k + 1) * ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ ∫ (x : ℝ) in ↑0 ..↑K, 2 * x ∂ρ = 2 * ∫ (x : ℝ) in 0 ..↑K, x ∂ρ

Tactic:
rw [intervalIntegral.integral_const_mul]

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ 2 * ∫ (x : ℝ) in ↑0 ..↑K, x ∂ρ = 2 * ∫ (x : ℝ) in 0 ..↑K, x ∂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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
⊢ ↑k ≤ ↑(k + 1)

Tactic:
simp

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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ ∑ k ∈ range K, 2 / (↑k + 1) * ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ ≤ ∑ k ∈ range K, ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂ρ

Tactic:
apply sum_le_sum 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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
⊢ 2 / (↑k + 1) * ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑k ↑(k + 1)
⊢ 2 / (↑k + 1) * x ^ 2 = x / (↑k + 1) * (2 * x)

Tactic:
ring

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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ ∑ k ∈ range K, ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂ρ = 2 * ∫ (x : ℝ) in 0 ..↑K, x ∂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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
⊢ ∫ (x : ℝ) in ↑0 ..↑K, 2 * x ∂ρ = 2 * ∫ (x : ℝ) in 0 ..↑K, x ∂ρ

Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k < K
⊢ IntervalIntegrable (HMul.hMul 2) ρ ↑k ↑(k + 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
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ 2 / (↑k + 1) * ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂ρ

Tactic:
rw [← intervalIntegral.integral_const_mul, intervalIntegral.integral_of_le Ik,
  intervalIntegral.integral_of_le Ik]

Result:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ ∫ (x : ℝ) in Set.Ioc ↑k ↑(k + 1), 2 / (↑k + 1) * x ^ 2 ∂ρ ≤ ∫ (x : ℝ) in Set.Ioc ↑k ↑(k + 1), 2 * x ∂ρ

Proof state:
case refine_2
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (HMul.hMul 2) (Set.Ioc ↑k ↑(k + 1)) ρ

Tactic:
apply Continuous.integrableOn_Ioc

Result:
case refine_2.hf
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n => truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0 ..↑n, x ^ 2 ∂ρ
k : ℕ
x✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ Continuous (HMul.hMul 2)