(See attached files for full problem description)
Write a 700- to 1,000-word report for Brian Usher offering a critical analysis of current and proposed pricing strategies and profitability for the two business units.
? Include an assessment of whether Odyssey Isle's current pricing strategy is profit-maximizing.
? Analyze the revenue and profit implications for the alternative pricing strategies proposed by Bob Radcliffe, James Bender, and Nell Richards.
? Discuss how Odyssey Isle's current and proposed pricing strategies affect consumer surplus.
? Recommend an optimal pricing strategy at Odyssey Isle. Your proposal should specify the exact prices that should be charged to visitors and demonstrate that these prices will produce the maximum level of profits for Odyssey Isle.
? Analyze JetSetter's current practice of bundling the golf option with the luxury option. Recommend an optimal bundling strategy for the golf, luxury, and family options. Discuss profits under each alternative.
? Evaluate JetSetter's bundling options for a Big Apple Platinum package. Discuss profits for each possible option: separate prices, mixed bundling, and pure bundling. Recommend a Big Apple Platinum package pricing strategy.
When we want to test two samples to determine if it is likely that the population means (estimated by the sample means) are different, we typically use a t-test. If the samples are large, we can also use a z-test. (Note that the formulas for computing s, t and/or z in the case of a two-sample test are different than the formulas for computing the same values in a one-sample test. Use Excel data analysis to conduct tests comparing two sample means.)
Using ANOVA (short for Analysis of Variance), however, we can test 3 or more sample means to determine if at least one of the sample means comes from a population with a mean that is significantly different from all of the others in the test. We actually do this by estimating a combined population variance two different ways and comparing the two estimates (the ratio of these two variance estimates follows the so-called "F distribution").
Why do we need a new test method to compare the means of 3 or more populations? Why can't we just use a series of z-tests or t-tests to compare all of the possible pairs of population means to see if one (or more) is different?
Most of the testing is to determine one or two things:
1. Is there a statistically significant difference between two or more population means? (based on comparison of 2 or more sample means)
2. Is there a statistically significant relationship between two or more variables? We can use regression analysis or chi-square tests to answer this second question.)View Full Posting Details