Course Summary (PDF format)
Excel
Spreadsheets
Basic Excel worksheet
techniques
are covered in one topic. Additional topic-specific techniques are used in
lessons covering the MBA topics below. Solutions illustrate basic functions
implementing algebraic formulas and also the
built-in
functions (e.g., FV, NPV,
VAR, STDEV, CORREL, RSQ, NORMDIST)
that you will use most often in your MBA experience.
Financial
Math
Familiarity with time value of money concepts, formulas, and spreadsheet
solution techniques should be considered a prerequisite for your MBA
experience. Because everything else in financial math is built on this
foundation of
shifting one cash payment at one time
to its equivalent at
another time, you should be clear about this before you start.
Annuities and perpetuities
are the simplest smooth patterns of cash flows over time.
Bonds
are a mixture of annuities and future values.
Net present value
allows you to convert an irregular set of cash flows back to the present to
compare one course of action with another. Such problems appear throughout the
MBA curriculum.
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Time Value of Money
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Annual Compounding
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Present Value
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Rate
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Number of Periods
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Future Value
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Sub-Annual Compounding
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same as Annual plus:
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Periods per Year
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Annuities and Perpetuities
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Bond Basics
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Net Present Value
Accounting
Making sense of accounting requires a clear understanding of the three main
financial statements and how these statements represent standard business
transactions. The math is simple. The challenge lies in the logic, definitions,
and conventions. Using Intel's financial statements as an example, you learn
the basics about the
balance sheet, income statement, and statement of cash
flows.
After studying each financial statement separately, you then work on the
connections among the three statements
with a set of examples.
You use the
balance sheet equation and t-accounts
to characterize standard business transactions in terms of offsetting
debits and credits
. Finally, you apply what you learned with t-accounts to make appropriate
journal entries.
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Balance Sheet
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Assets
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Liabilities
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Equity
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Balance Sheet Equation
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Transactions
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Income Statement
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Revenues
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Expenses
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Cash vs. Depreciation
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Statement of Cash Flows
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Operating Activities
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Investing Activities
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Financing Activities
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Cash vs. Depreciation
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T Accounts and Balance Sheet Equation
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Balances
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Debits
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Credits
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Transactions
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Journals
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Journal Entry Template
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Debits
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Credits
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Transactions
Microeconomics
Marginal analysis
addresses the question of how much to produce to maximize profit, given
specified costs and revenues. Problem statements and solutions involve either
tables or formulas. You learn to distinguish among marginal, total, and average
costs and revenues.
Supply and demand
are the classic economics concept. You learn to create and interpret the
classic linear "curves", compute the
equilibrium point
that maximizes profit and the corresponding
consumer
surplus. You examine market segmentation, and use demand curves as part
of marginal analysis.
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Marginal Analysis
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Tables
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Formulas and Calculus
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Supply and Demand
Statistics
and Probability
You start with
basic summary statistics, which form the
foundation. You then tackle statistics of linear combinations, which is a fancy
way of saying
stock
portfolios.
Tables and graphs summarize raw data. You need to know how to make them and
work with them.
Regression
allows you to draw a best-fit line through a set of data points. You can do it
visually or computationally. Both approaches are a snap using Excel.
The
standard normal "bell curve"
is the king of continuous distributions. You learn to work with continuous
distributions in terms of intervals rather than points. Excel makes solutions a
breeze but you may, depending on your MBA program, need to learn the z-table
approach and its corresponding pictographs and conversions.
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Basic Summary Statistics
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Mean, Median, and Mode
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Variance and Standard Deviation
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Linear Combinations (e.g., Stock Portfolios)
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Covariance and Correlation
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Portfolio Statistics from Individual Stock Returns
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Portfolio Statistics from Individual Stock Statistics
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Discrete Probability Distributions
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Linear Regression
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Regression Line Equation
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Prediction
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Measure of Linearity
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Continuous Distributions
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Uniform
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Standard Normal
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Normal
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