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Spreadsheet supplement to case UV0351.

Spreadsheet for case UV6289

The protagonist in this case is an analyst attempting to value Netflix, Inc., and check whether her recent buy recommendation at a price of $20.00 per share was still valid. Recent bad news had caused the price to drop and she needed to do her best to figure out what was the future for Netflix, and was it undervalued at $17 per share? Intended for MBA students, this case contains her discounted cash flow valuation and a set of assumptions (revenues per customer, retention rates, etc.) students can use to perform a valuation of the existing Netflix customer base as another approach toward judging the $17 stock price. There are two student spreadsheets available for this case (UV4342 and UV4343).

Spreadsheet supplement for case UV3928.

The protagonist in this case is an analyst attempting to value Netflix, Inc., and check whether her recent buy recommendation at a price of $20.00 per share was still valid. Recent bad news had caused the price to drop and she needed to do her best to figure out what was the future for Netflix, and was it undervalued at $17 per share? Intended for MBA students, this case contains her discounted cash flow valuation and a set of assumptions (revenues per customer, retention rates, etc.) students can use to perform a valuation of the existing Netflix customer base as another approach toward judging the $17 stock price. There are two student spreadsheets available for this case (UV4342 and UV4343).

Intended for MBAs, this case concerns the valuation of Netflix, Inc., which was the largest U.S. online movie rental subscription service in early 2009. After reviewing Netflix's historical financial and customer relationship performance, this case presents three approaches for valuing the firm in early 2009. The first is a company-level discounted cash flow analysis based on pro forma projections of revenues, earnings, and cash flow. The second approach attempts to judge whether the prevailing market value of Netflix was reasonable by comparing selected company ratios with those of comparable companies. The final approach is based on the assumption that Netflix's enterprise value (EV) was the sum of its current and future subscribers' values (discounted present values, to be exact). There is also a spreadsheet available for students (UV5597).

The protagonist in this case is an analyst attempting to value Netflix, Inc., and check whether her recent buy recommendation at a price of $20.00 per share was still valid. Recent bad news had caused the price to drop and she needed to do her best to figure out what was the future for Netflix, and was it undervalued at $17 per share? Intended for MBA students, this case contains her discounted cash flow valuation and a set of assumptions (revenues per customer, retention rates, etc.) students can use to perform a valuation of the existing Netflix customer base as another approach toward judging the $17 stock price. There are two student spreadsheets available for this case (UV4342 and UV4343).

A pilot/manager in a large corporate aviation department must formulate a fueling plan for an upcoming four-leg trip. Considerations for the fueling plan include different fuel prices at each airport (fuel is much cheaper if bought at home) and ramp fees levied at destination airports if fuel purchases fail to meet specified minimums. Other considerations include aircraft weight limits for takeoffs and landings (with fuel being a large component of aircraft weight), fuel tank capacity, and a company policy specifying a minimum amount of fuel required at each landing.

Spreadsheet supplement for case UV1223.

This case describes a 21-factor, 56-recipe multivariable test (MVT) conducted by Progressive Insurance with the help of QualPro, a leading MVT consulting firm. The object of the test was to improve Progressive's direct-mail retention campaign. The results of the test are available in a spreadsheet for students to analyze (UVA-S-M-0762.xls).

Progressive Insurance, a leader in the automotive insurance market, has succeeded through innovation. The case describes the company strategies for differentiating their service through Immediate Response Vehicles, Express Quote (comparing prices for prospective customers, and multichannel marketing agents, 1-800 numbers, and the Web). Through these programs and a series of creative advertising campaigns the company has built a strong brand in a relatively short time. Channels with their pricing and channel strategies remain.

The case asks students to develop a method for identifying individuals at risk of having chronic kidney disease. A 6,000 subject training set containing 34 potential predictor variables is provided along with a 2,819 subject validation set the instructor uses to evaluate student predictions. The case is based on an actual study which resulted in a simple nine-question survey that instrument health professionals use to help patients decide whether to be tested for chronic kidney disease.

Greg Mills describes his search for the perfect engagement ring which includes an analysis of the prices of 6,000 diamonds. An engineer, Greg hopes to impress Sarah Staggers by using regression to find an underpriced diamond. Students are asked to either select one of the 6,000 diamonds or provide point forecasts for prices of 3,142 diamonds in a hold-out sample. The instructor can use the actual prices of the held-out diamonds to evaluate student pricing models.

Spreadsheet supplement for case UV0869.

This comprehensive technical note explains linear regression. It is intended for students with no prior knowlede of the topic. It is devided into nine sections, which may be assigned separately: 1. The simple linear model, 2. Fitting the model using least Squares, 3. Important properties of the least-squares regression line, 4. Summary regression statistics, 5. Assumptions behind the linear model, 6. Model-building Philosophy, 7. Forecasting using the linear model, 8. Using dummy variables to represent categorical variables, and 9. Useful data transformations. The sections correspond to stand-alone notes also available through Darden Business Publishing

This note describes the basics fo time series analysis and forecasting. It discusses the kinds of patterns found in time serices (cycle, trend, adn seasonality) and the most common time series models: exponential smoothing, Holt's, and Winter's. It is written for the MBA audience.

This note describes the chi-square statistic as applied to goodness-of-fit tests. Goodness-of-fit tests check to see how closely a sample matches a particular probability distribution (e.g., normal, Poisson, binomial).

This note introduces four common underlying processes and the analytical probability distribution used to forecast the outcomes of each. The note also illustrates how to use Excel functions to calculate probabilities from the four resulting probability distributions: the binomial, normal, Poisson, and exponential.

This note describes the more common methods of calculating Price Premiums (also known as Relative Prices). Students will explore Reservations Prices and % Good Value, the concepts that form the foundation of price-quantity schedules, as well as Price Elasticity, a frequently used index of how responsive the market is to changes in price. The note stresses that understanding demand functions and Price Elasticity is key to the calculation of optimal prices and uses the familiar concept of Prisoner's Dilemma and addresses price tailoring.