Notes, summaries, assignments, exams, and problems for Mathematics

Key Advantages of Bonds for Investors

Investing in bonds offers several key benefits:

• Source of Current Income: They are a good source of regular income.
• Relative Safety: Investment in bonds is relatively safe from large losses.
• Priority in Default: In case of default, bondholders receive their payments before shareholders can be compensated.

Comprehensive Bond Classification

Bonds are classified by their key features, which include:

• Form of Payment
• Coupon Payment
• Collateral
• Type of Circulation
• Type of Issuers
• Recall Possibility
• Place of Circulation
• Quality
• Other Miscellaneous Types

By Form of Payment

• Non-interest-bearing Bonds
• Regular Serial Bonds
• Deferred-interest Bonds
• Income Bonds
• Indexed Bonds
• Optional Payment Bonds

By Coupon Payment

• Coupon Bonds
• Zero-coupon Bonds
• Full

Understanding Kurtosis: Distribution Shape

Kurtosis is a statistical measure that describes the shape of a distribution’s tails compared to a normal distribution. It tells us whether the data are heavy-tailed or light-tailed.

In simple terms, kurtosis indicates the degree of peakedness and the presence of outliers in data.

Types of Kurtosis

• Mesokurtic: Normal distribution (kurtosis = 3).
• Leptokurtic: More peaked, heavy tails (kurtosis > 3).
• Platykurtic: Flatter peak, light tails (kurtosis < 3).

Key Concepts in Hypothesis Testing

1. Null Hypothesis (H₀)

It is a statistical statement that assumes no effect or no difference.

Example: “There is no difference between two groups.”

2. Alternative Hypothesis (H₁ / Hₐ)

It is the opposite of the... Continue reading "Key Statistical Concepts: Kurtosis & Hypothesis Testing" »

Hypothesis Testing

Statistical Test Selection

1. If the population standard deviation is unknown and the sample size is less than 30: t-test

2. If the population standard deviation is known and the sample size is less than 30: t-test

7. Hypothesis test on population mean; n = 25; σ = 2.5: z-test

8. Hypothesis test on population mean; n = 50; s = 7.2: z-test

18. Test statistic for sample size above 30: z-test

19. Test statistic when population standard deviation is known: z-test

20. Test statistic when population standard deviation is unknown: t-test

21. When to use the t-test: I and II

24. Optimal sample size for z-test: Equal to or larger than 30

Hypotheses and Significance

3. H₀: μ = 30

4. H₁: μ > 30

5. No

9. False: The alternative hypothesis typically... Continue reading "Hypothesis Testing: A Concise Statistical Method Reference" »

What is Data Science?

• An interdisciplinary field combining statistics, computer science, and business knowledge.
• Its goal is to extract valuable insights and knowledge from data (both structured and unstructured).
• It answers key business questions: what happened, why, what will happen, and what to do about it.
• The process involves collecting, cleaning, processing, analyzing, and communicating data insights.

Statistical Inference: Making Educated Guesses

• It's the process of using sample data to make educated guesses or draw conclusions about a much larger population.
• Essentially, it lets you make generalizations about a whole group based on a smaller part of it.

Key Goals of Statistical Inference

• Estimation: To guess the value of a population parameter

Question 1: Decimal Representation of a Fraction

Question: Consider the fraction 6/7. The decimal representation of this fraction is:

Answer: 6 ÷ 7 = 0.857142857... (repeating)

Question 2: Vaccinated to Unvaccinated Ratio

Question: If 60% of a population is vaccinated, what is the ratio of vaccinated to unvaccinated individuals?

Answer: 60% vaccinated → 60 : 40 → Simplified = 3 : 2

Question 3: Property Tax Calculation

Question: A property has been assessed at $225,000. The mill rate is 14.5. To find the property tax, you would multiply the assessed value by:

Answer: The mill rate of 14.5 means $14.50 per $1,000 of assessed value. To convert this to a decimal factor, divide by 1,000:

• 14.5 ÷ 1,000 = 0.0145
• Property tax = $225,000 × 0.0145 = $3,262.

Key Concepts in Engineering Economics

Engineering Economics is the science dealing with quantitative analysis techniques for selecting the most preferable alternative from several technically viable options.

Fundamental Principles

Four fundamental principles must be applied in all engineering economic decisions:

• The time value of money
• Differential (or incremental) cost and revenue
• Marginal cost and revenue
• The trade-off between risk and reward

Core Terminology Explained

Ethics

A set of principles that guides a decision-maker in distinguishing between right and wrong.

Market Interest Rate

The interest rate quoted by financial institutions, which refers to the cost of money for borrowers or the earnings from money for lenders.

Interest Rate

The cost, or price,

Managerial Decision-Making and Business Analytics

Types of Managerial Decisions

To effectively plan, coordinate, and lead, managers make several types of decisions:

• Strategic Decisions: Address high-level issues and the overall direction of the organization. They define future goals and are long-term and complex.
• Tactical Decisions: Focus on how to achieve the goals and objectives set by the strategy. These are typically made by mid-level management for the medium term.
• Operational Decisions: Pertain to day-to-day operations. They are made by operations managers and are often simple and routine.

The Decision-Making Process (DMP)

A structured approach to decision-making involves several key steps:

1. Identify and define the problem.
2. Determine the criteria

Chapter 1: Understanding Variables

Types of Variables

• Categorical: Smoker (current, former, no)
• Ordinal: Non, light, moderate, heavy smoker (ordered categories)
• Quantitative: BMI, Age, Weight (numerical measurements)

Key Definitions

• Observation: Measurements are made (individual or aggregate).
• Variable: The generic characteristic we measure (e.g., age).
• Value: A realized measurement (e.g., 27).

Chapter 2: Statistical Studies

Surveys: Census and Sampling

• Goal: Describe population characteristics.
• Census: Attempts to reach the entire population (costly, time-consuming).
• Sampling: Uses a sample of the population (allows for inferences, saves time and money).
• Simple Random Sampling: Based on probability.
• Issues with Sampling: Under-coverage, volunteer bias,

Parametric Inference Fundamentals

The probability distribution of the population under study is known, except for a finite number of parameters. Its goal is to estimate those parameters. Examples include the T-test and ANOVA.

Non-Parametric Inference Basics

The distribution of the population is not known. It is used to test the assumptions of parametric methods, for example, to check if the population distribution is normal.

What is a Statistic?

A random variable function of the sample that does not depend on the unknown parameter.

Understanding Estimators

A statistic whose values are acceptable for estimating an unknown parameter.

Unbiasedness in Estimation

We do not allow systematic overestimation or underestimation of the parameter, which would result... Continue reading "Statistical Inference & Hypothesis Testing Concepts" »

De Morgan's Law

De Morgan's Law: (Flip if the union is true)

, image of set: [min, max]; one-to-one: horizontal line test; Onto: Image must equal domain; Bijective: one-to-one and Onto

|| EV

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Possible Outcomes and Probability Calculations

• Repetition formula: n^k
  • Example: 5 awards (k) and 30 students (n), with no limit to awards per student.
• Permutation formula: P(n, k) = n! / (n - k)!
  • Example: Each student gets 1 award, so the number of students decreases by one each award.
• No overlap probability: P(n, k) / repetition formula
• Arrangements: a = slots → a! can be multiplied by arrangements within slots
• Die sum probability:
  • List combinations that lead to the sum for each die.
  • If a die is rolled multiple times, each combination has (rolls)! permutations.
  • Add