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Document Similarity Metrics: Jaccard, Cosine, and Hamming Calculations

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Document Similarity Metrics: Jaccard, Cosine, and Hamming Calculations (Q99)

Documents (after lowercasing and tokenizing words, removing punctuation):

  • D1: “the night is dark and the moon is red”
  • D2: “the moon in the night is red”
  • D3: “i can see moon is red the night is dark”

Step A — Construct Word Sets / Vectors (Unified Vocabulary)

Vocabulary (unique words across D1–D3): {the, night, is, dark, and, moon, red, in, i, can, see} (11 words)

i) Jaccard Similarity (Set of Words)

Set(D1) = {the, night, is, dark, and, moon, red}

Set(D2) = {the, moon, in, night, is, red}

Set(D3) = {i, can, see, moon, is, red, the, night, dark}

Compute pairwise Jaccard:

  • D1 ∩ D2 = {the, night, is, moon, red} → size 5; D1 ∪ D2 size = 8 → J(D1,D2)=5/8=0.625
  • D1
... Continue reading "Document Similarity Metrics: Jaccard, Cosine, and Hamming Calculations" »

Statistical Process Control Charts and Business Value Metrics

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Customer Value: (Quality, Time, Flexibility, Customer Experience, Innovation) / Price

Sustainability Paradigms: Economic (Viable, Equitable), Environment (Viable, Bearable), Social (Bearable, Equitable)

- Efficiency (Optimization), Differentiator (Innovation), Driver (Motivation) | - Audits (Assess Sustainability Performance)


Table 7.3: Factors for Calculating Three-Sigma Limits for the X (Bar) Chart and R-Chart

Size of Sample (n)Factor for UCL and LCL for X (Bar) Charts (A2​)Factor for LCL for R-Charts (D3​)Factor for UCL for R-Charts (D4​)
21.88003.267
31.02302.575
40.72902.282
50.57702.115
60.48302.004
70.4190.0761.924
80.3730.1361.864
90.3370.1841.816
100.3080.2231.777

*A sample is out of control if its value falls below the LCL or above the UCL*

... Continue reading "Statistical Process Control Charts and Business Value Metrics" »

Corporate Taxation: Distributions, Redemptions, and Tax Accounting

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Corporate Distribution Layers

Distributions are applied in the following order: Accumulated E&P + Current E&P, then basis, then the remainder is treated as capital gain.

  • No Dividend: If there is no E&P, reduce current E&P first. Negative AEP still distributes E&P.
  • Offset: Half of current E&P is lost to offset AEP before distribution.

Property Distributions

Recognize gains, but not losses.

  • Dividend: FMV - Liabilities
  • Basis: FMV
  • Gains: FMV - Tax Basis

Distribution Table

The amount from CEP is calculated as: (Period distribution / Total distribution) * CEP. AEP is applied to the remainder, then to stock basis.

Stock Distributions and Redemptions

  • Stock Distribution: Proportionate distributions are nontaxable and do not reduce E&
... Continue reading "Corporate Taxation: Distributions, Redemptions, and Tax Accounting" »

5 hr 20 min 20 sec corresponds to a longitude difference of

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lim x->0 sinx/x = 1 | H.A.: compare degrees | V.A.: denom = 0 | Continuous if: f(a), lim, equal

DERIVATIVES: (x^n)'=nx^(n-1), (e^x)'=e^x, (a^x)'=a^x ln a, (lnx)'=1/x | (uv)'=u'v+uv', (u/v)'=(u'v-uv')/v^2 |chain: (f(g(x)))'=f'(g(x))g'(x)

TRIG DERIVATIVES: (sin)'=cos, (cos)'=-sin, (tan)'=sec^2 | (sec)'=sec·tan, (csc)'=-csc·cot, (cot)'=-csc^2

CRITICAL POINTS:f'=0 or DNE ⇒ crit pt | f'>0 inc | f'<0 dec | f''>0 conc up | f''<0 conc down | inflec = f'' signchange

INTEGRATION: ∫x^n dx = x^(n+1)/(n+1)+C | ∫e^x dx = e^x+C | ∫a^x dx = a^x/ln a+C | ∫1/x dx = ln|x|+C | ∫sin x dx

= -cos x+C | ∫cos x dx = sin x+C

FTC: Part 1: d/dx ∫_a^x f(t) dt = f(x) | Part 2: ∫_a^b f(x) dx = F(b)-F(a)

AREA & VOLUME: A = ∫_a^b (top - bot)... Continue reading "5 hr 20 min 20 sec corresponds to a longitude difference of" »

Multivariable Calculus and Vector Analysis Formulas

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Gradient: \nabla f = \langle f_x,\ f_y,\ f_z\rangle Directional derivative (unit vector u): D_uf = \nabla f\cdot u Unit direction from A→B: u = \frac{B-A}{\|B-A\|} Tangent plane to z=f(x,y): z - z_0 = f_x(x_0,y_0)(x-x_0)+f_y(x_0,y_0)(y-y_0) Critical points: Solve f_x=0, f_y=0. D = f_{xx}f_{yy} - (f_{xy})^2 Min if D>0,f_{xx}>0. Max if D>0,f_{xx}<0. Saddle if D<0.

General double integral: Type I (y inner): \int_a^b \int_{g_1(x)}^{g_2(x)} f\, dy\, dx

Type II (x inner):

\int_c^d \int_{h_1(y)}^{h_2(y)} f\, dx\, dy

Polar:

x = r\cos\theta,\ y=r\sin\theta,\ dA=r\,dr\,d\theta

Circle: 0\le r\le R.

Line y=mx → \theta=\arctan m.

Region must be continuous in θ.


🔷

3. TRIPLE INTEGRALS

Cylindrical:

x=r\cos\theta,\ y=r\sin\theta,\ dV=r\,dz\,dr\,... Continue reading "Multivariable Calculus and Vector Analysis Formulas" »

R Programming Fundamentals, SQL, and Advanced Clustering Methods

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Section A: R Basics and Data Types (Weeks 1-4)

Model Questions and Answers

Q: Create a vector v (3, NA, Inf, -Inf). Explain adding 5 to v.

A: The operation is element-wise. Missing values (NA) propagate, resulting in NA. Infinite values (Inf, -Inf) remain infinite.

v <- c(3, NA, Inf, -Inf)
print(v + 5)
# Output: [1]  8 NA Inf -Inf

Q: Given vector a, write code to count and replace NAs.

A: Assuming a <- c(10, 15, NA, 20).

  • Count NAs: sum(is.na(a)) → 1.
  • Replace NAs (e.g., with 0): a[is.na(a)] <- 0.

Q: Explain the difference between a[a > 12] and a[which(a > 12)].

A: Both select elements greater than 12 (15, 20). However:

  • a[a > 12][1] 15 NA (Uses logical indexing; preserves the position of NA in the original vector as NA).
  • a[which(
... Continue reading "R Programming Fundamentals, SQL, and Advanced Clustering Methods" »

Essential Mathematics and Statistics Formula Sheet

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Quick revision table for Mathematics and Statistics exams.

Unit I: Integration and Data Presentation

TopicFormulaUse
Integration Algebraic∫xⁿ dx = xⁿ⁺¹/(n+1) + C, n≠-1
∫1/x dx = ln|x| + C
∫k dx = kx + C
∫x dx = x²/2 + C
Finding area, antiderivative
Integration Trigonometric∫sin x dx = -cos x + C
∫cos x dx = sin x + C
∫sec²x dx = tan x + C
∫tan x dx = ln|sec x| + C
∫cot x dx = ln|sin x| + C
Trig integration
Integration Exponential∫eˣ dx = eˣ + C
∫aˣ dx = aˣ/ln a + C
Growth, decay problems
Pie Diagram AngleAngle of sector = (Component value / Total value) × 360°Constructing pie chart
Median from OgiveMedian = X-coordinate of intersection point of "less than" and "more than" ogiveGraphical method

Unit II: Central Tendency and

... Continue reading "Essential Mathematics and Statistics Formula Sheet" »

Intervalos de confianza y pruebas estadísticas para muestras

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Problema 1: Intervalo para la media (σ conocido)

PROBLEM 1

Nos dan normal distribution.

Desviación estándar σ = 24

Muestra aleatoria simple de 8 — ignorar.

Luego los datos:

185, 180, 167, 162, 176, 170, 181, 192

La pregunta es: confidence interval for the population mean, with a confidence level of...

Paso 1: srs1 = c(185, 180, 162, etc...)

Pregunta (A) — 90%

Ejecutar:

z.test(x = srs1, sigma = 24, conf.level = 0.9)

Pregunta (B) — 95%

Ejecutar:

z.test(x = srs1, sigma = 24, conf.level = 0.95)

Pregunta (C) — 99%

Ejecutar:

z.test(x = srs1, sigma = 24, conf.level = 0.99)

Problema 2: Intervalo para media, varianza y desviación

PROBLEM 2

Te dan números: 45297, 51012, 41764, 41799, 42408, 28543

Normal distribution.

Nivel de significancia = 2% y necesito el

... Continue reading "Intervalos de confianza y pruebas estadísticas para muestras" »

Two-State Actuarial Modeling: Principles and Applications

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Two-State Actuarial Model

The Two-State Model (also known as the Dead-Alive or Binary Model) is a fundamental actuarial framework used to represent processes that exist in one of two possible states, such as Alive/Dead or Working/Retired. It is widely utilized in life insurance and pension modeling to estimate the probability of transition between states. The model assumes that at any given time, an individual occupies only one state, allowing actuaries to calculate premiums, reserves, and expected present values by simplifying complex uncertainties into binary outcomes.

Core Assumptions

  • Binary States: The system exists in only one of two states at any time.
  • Markov Property: Transitions depend solely on the current state.
  • Constant Probabilities:
... Continue reading "Two-State Actuarial Modeling: Principles and Applications" »

Understanding Financial Formulas and Calculations

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Tutorial 1

If you get a positive value times a number,

You need to shift the decimal to the right as many times as the number specified.

If negative, move it to the right.

Simple interest formula = S = FV = P(1 + iK)

Compound interest formula = Sk = P(1 + i)^k

Sn = P(1 + I/T)^n
where I is interest
T is frequency of compounding per year
K is the number of years
N is the total number of periods - K T or TK

Depreciation Formula = Vo or P = Initial value,
Vk = P(1 - d)^k

Tutorial 2

1. 5 years 1 + r = (FV/PV)^(1/5)
(i) r = 10.38%
(ii) r = 10.47%
(iii) r = 10.51%
(iv) r = 10.52%
(v) r = 10.52%
2. 1 + r = (1 + 0.06/12)^8 ∙ (1 + 0.072/12)^4
1 + r = (1.005)^8 ∙ (1.006)^4
1 + r = (1.0407) ∙ (1.0242) = 1.06591
r = 6.59%

For an initial outlay of $1000, the net return is

... Continue reading "Understanding Financial Formulas and Calculations" »