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English Grammar and Vocabulary Exercises

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Part I: Complete the Following Table

Sentence TypeExample
AffirmativeCarlos is in the house.
NegativeCarlos isn't in the house.
QuestionIs Carlos in the house?
AffirmativeWe are 23 years old.
NegativeWe aren't 23 years old.
QuestionAre we 23 years old?

Part II: Complete the Following Sentences

  1. She is from the United States. She is American.
  2. She is from Nigeria. She is Nigerian.
  3. She is from Germany. She is German.
  4. They are from Egypt. They are Egyptian.
  5. We are from Canada. We are Canadian.

Part III: Select the Correct Sentence

  1. Select the correct sentence.
    • a) She lives with Carlos, and she works on Saturdays.
  2. Select the correct sentence.
    • c) They are running in the park.
  3. Select the correct sentence.
    • b) She is 20 years old.
  4. Select the correct sentence.
    • a) We always
... Continue reading "English Grammar and Vocabulary Exercises" »

Essential Accounting Concepts and Financial Reporting

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Fundamental Accounting Principles and Practices

Core Accounting Definitions

Assets = Liabilities + Owner’s Equity: This is the fundamental accounting equation, representing the balance of a company's financial position.

Double-Entry Accounting

The recording of both debit and credit parts of every transaction, ensuring the accounting equation remains balanced.

Objective Evidence Principle

Requires that a source document (e.g., invoice, receipt) be prepared for every entry in a journal, providing verifiable proof of a transaction.

File Maintenance

The process of arranging accounts in a general ledger, assigning account numbers, and keeping records current.

Opening an Account

Writing an account title and number on the heading of an account in the ledger.... Continue reading "Essential Accounting Concepts and Financial Reporting" »

Metallurgical Sample Preparation for Microscopic Analysis

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Metallurgical sample preparation for microscopy is a crucial step in analyzing the microstructure and properties of metallic materials. Proper sample preparation is essential to obtain accurate and meaningful results. The process involves several key steps:

1. Sample Selection for Microscopy

Choose a representative portion of the material to be analyzed. Ensure that the sample is free from external contaminants and has a flat surface for preparation.

2. Precision Cutting Techniques

Use a precision cutting method to obtain a small section of the material for analysis. Common cutting techniques include abrasive cutting (using a saw with abrasive blades), wire cutting, or electrical discharge machining (EDM) for hard materials.

3. Sample Mounting for

... Continue reading "Metallurgical Sample Preparation for Microscopic Analysis" »

Understanding Bonds: Key Features and Market Dynamics

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Bond Characteristics

  • Coupon: The interest payment made by the bond issuer, usually expressed as an annual percentage of the bond's face value.
  • Par (Face Value): The amount the bondholder receives when the bond matures, typically $1,000.
  • Term to Maturity: The time remaining until the bond's maturity date when the issuer must repay the bond's par value.
  • Denomination: The face value of the bond, usually in increments of $1,000.
  • Quotation: Bonds are quoted as a percentage of their face value (e.g., a bond quoted at 95 is selling for 95% of $1,000, or $950).

Bond Prices, Yield to Maturity (YTM), Current Yield, and Rate of Return (HPR)

  • Bond Prices: The market price of a bond depends on interest rates. Prices and interest rates have an inverse relationship.
... Continue reading "Understanding Bonds: Key Features and Market Dynamics" »

Introduction to Statistics: Discrete and Continuous Random Variables, Probability Distributions, and Sampling Techniques

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Discrete Random Variables

Discrete random variables are variables that can take on a finite number of distinct values. In simpler terms, a discrete random variable is a set of possible outcomes that is countable.

Continuous Random Variables

Continuous random variables are random variables that take an infinitely uncountable number of potential values, typically measurable amounts.

Example

  1. List the sample space in the given experiment. How many outcomes are possible?

The sample space is: S = {NNN, NND, NDN, NDD, DNN, DND, DDN, DDD}

  1. Count the number of defective keyboards in each outcome in the sample space and assign this number to the outcome. For instance, if you list NND, then the number of defective keyboards is 1.

The possible values of X are 0,... Continue reading "Introduction to Statistics: Discrete and Continuous Random Variables, Probability Distributions, and Sampling Techniques" »

Inventory Management Principles and Practices

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Inventory Fundamentals

One use of inventory is to provide a hedge against inflation. ABC analysis divides an organization's on-hand inventory into three classes based upon annual dollar volume. Cycle counting is a process by which inventory records are verified. The difference(s) between the basic EOQ model and the production order quantity model is that the production order quantity model does not require the assumption of instantaneous delivery. Extra units that are held in inventory to reduce stockouts are called safety stock. Inventory record accuracy would be decreased by increasing stockroom accessibility. The two most important inventory-based questions answered by the typical inventory model are when to place an order and how many of

... Continue reading "Inventory Management Principles and Practices" »

Data Science Career Transition & Predictive Modeling

Classified in Mathematics

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Introduction: A Data Science Journey

My name is Amit Kadam, and I currently reside in Mumbai. I completed my Bachelor of Engineering (B.E.) degree in 2021. After graduation, the pandemic limited job opportunities, and my family faced financial challenges, so I took my first opportunity at Sterling as a Senior Associate, where I worked for 2.5 years.

Initially, I was responsible for document verification, but I was soon promoted to manage drug health screening processes. In this role, I handled candidate health reports, prepared data for analysis, and developed strong attention to detail and data-handling skills.

During this time, a friend who successfully transitioned into data science encouraged me to explore the field. I started by learning... Continue reading "Data Science Career Transition & Predictive Modeling" »

Statistical Relationships: Scatter, Correlation, Regression

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What is a Scatter Diagram?

Definition

A scatter diagram (or scatter plot) is a graphical representation of two variables where each point represents an observation consisting of paired values from two datasets. The horizontal axis (X-axis) represents one variable, and the vertical axis (Y-axis) represents the other.

Construction

Each point (x_i, y_i) is plotted on the graph for the corresponding values of the two variables.

Utility in Correlation Analysis

Scatter diagrams are essential for:

  • Visualizing relationships: Helps identify if a linear or non-linear relationship exists.
  • Direction of correlation:
    • Positive correlation: As X increases, Y increases (points slope upwards).
    • Negative correlation: As X increases, Y decreases (points slope downwards).
... Continue reading "Statistical Relationships: Scatter, Correlation, Regression" »

Understanding Simple Linear Regression: R-squared, Slope, and Conditions

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Write an interpretation of r^2 using the template in the Activity 2.1 Readings. We will do this one as a class.

Template: The proportion of the variation in the Y variable that is explained by the SLR model with the X variable is r^2.

For slope : Template: As x var increases by 1 unit, we predict y var  will increase/dec  by ____  y var units.

For y-intercept: When x var = 0 units, we predict that the y var  will be ____ units..

For SLR: Error = epsilon = y - yhat = y - (betahat0 + betahat1x)

SSE = residual1^2 + res. 2^2 +…+ res.  n^2 AD_4nXdgexHFktdBh3CFf6Ipr3g0Dvmpby1nEeB2kf4m3BPlVZyVmpXy0M3wvv_abbUEw0FmvELgZ4sk8s6J4Iz5loc0vp-F8fhOq9FiXmgdgpWxRvt0Y4-osnlgACEA0r4voQ32JZKQDqgWqqZ8QAv1u5nrCAGl?key=sPl0wRYNdDvyOslUfU3rFg

Standard error of regression = Root MSE (in SAS language)

The text lists six conditions for simple linear... Continue reading "Understanding Simple Linear Regression: R-squared, Slope, and Conditions" »

Financial Budgeting: Principles and Model Development

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Key Principles of Financial Budgeting

Entity Principle

Consider the company as a functional entity.

Leadership Principle

The Financial Planning Manager develops and coordinates the budget.

Authority Principle

The Finance Manager supervises and presents the budget to the Board of Directors (Partners).

Participation Principle

Involve all key participants in the budget's preparation.

Commitment Principle

All managers undertake to follow the budget, notifying any deviation in a timely manner.

Goal Principle

The budget is based on the strategic planning objectives.

Accounting Principle

A budget system should mirror the current accounting system.

Measurement Principle

All estimates must be in currency units.

Predictability Principle

The predictions generated must... Continue reading "Financial Budgeting: Principles and Model Development" »