PROJECT PART C: Regression and Correlation Analysis Essay

The picture above reflects the stock price in dollars of our company over the frame of 10 periods. While the stock price of our company has thoroughly and exponentially increased in the overall time period, there are two small dips in the 2nd and 3rd time period. One of the few reasons for these dips could be the reformulation of the brand. The brand previously contained alcohol in its original formulation. Only few of these kinds of changes are positively perceived in the market. Hence, with such drastic changes people might be uncertain if they want to buy the stock price reducing the demand of the stock, decreasing the stock price of Allstar.

2. What is the company 's rate of net income growth in 2004,2005, and 2006? Is projected net income growing faster or slower than projected sales? After computing these values, take a hard look at the 2004 income statement data to see if you want to make any adjustments.

The rise in revenue was rapid starting from the year of operations. The key period of business was from April to September were revenues were equal to 65% of total revenue as the product was seasonal. The basis of forecasting for the year 1981 & 1982 is the expectations of sales by Mr. Turner & Mr. Rose. It is given that total sales were $ 15.80 million in first half of year 1981 and the total sales in 1981 to reach $ 30 million. Profit after tax was expected to be $ 1 million for 1st half and we assumed for the next half, profit will be in proportion to first half & expected to be amounting to $ 0.90 million. For year 1982, the sales expectation by Mr. Rose was around more than $ 71 million &

The case involves the decision to locate a new store at one of two candidate sites. The decision will be based on estimates of sales potential, and for this purpose, you will need to develop a multiple regression model to predict sales. Specific case questions are given in the textbook, and the necessary data is in the file named pamsue.xls.

Seven models were created in order to obtain the model in which all-remaining variables are statistically significant and the final equation to predict sales is as follow:

A firm has decided through regression analysis that its sales (S) are a function of

The following allocation of advertising campaign budget was used to estimate number of new policies sold:

The purpose of this case is to determine which key variables drive Crusty Pizza Restaurant’s monthly profit and then forecast what the monthly profit would be for potential stores. Based off of this information we will be able to make a recommendation to Crusty Dough Pizza Restaurant on which stores they should open and which they avoid. The group was provided 60 restaurants’ data that included monthly profit, student population, advertising expenditures, parking spots, population within 20 miles, pizza varieties, and competitors within 15 miles. For the potential stores we were given all of this

Using all the transactions in the data set, determine the revenue maximizing price for Copa. Here is a step-by-step approach: a) Fit a logit price-response curve to the data using the MLE approach discussed in class. (NOTE: For better numerical precision and to get good results in Excel, use prices in 100s. That is if the quote is $150 per person for a contract, use $1.5 per person in the MLE calculations.) b) Based on the fitted logit curve, what is the price (per person) that maximizes expected revenue per event? What is the expected revenue per transaction for that price? c) Assuming the annual number of inquiries remains the same, what would be the total expected revenue for the company if the price you determined in part (b) is used? How does the annual expected revenue compare to the total revenue earned by Copa in 2007? 2) Analyze the data to determine whether there are multiple price segments. a) What is your segmentation criterion? Explain clearly. b) What is the revenue maximizing price for each segment? What is the expected revenue for each transaction in that segment? (You have to repeat the analysis in part (1) for each of the segments.)

* Our company’s sales forecast has been based on performance from previous years along with market circumstances. We are looking at the future of the business objectively which we then can evaluate past to

1. Using the historical data as a guide (Exhibit 6.1), construct a pro forma (forecasted) profit and loss statement for the clinic's average month for all of 2010 assuming the status quo. With no change in volume (utilization), is the clinic projected to make a profit?

Given the data in this worksheet, what do the aging schedules tell you about customers’ payment patterns at the end of March and June? Explain.

Greaves provided five years and two months of annual sales data. Using Stat Tools, the following analysis were run: Moving Average, Exponential Smoothing Simple, Exponential Smoothing Holt’s, and Exponential Smoothing Winter’s. Following a comparison on the average on all models, the Exponential Smoothing Winter’s was found to be the most suitable model for the case. A graph analysis is captured below.

As previously mentioned, no analysis is given for the regression model, so we shall at least attempt to ask the appropriate questions needed to make an intelligent decision. We begin by looking at the structure of the regression model prior to performing the diagnostic procedures. First, we must understand why the consultants chose to model the revenue in the markdown period as a product of the observed performance in the regular period, the PL effect, Department effect, the promotions effect, and a constant. If there are no PL effects, department effects, or promotions effects, then the revenue is simply a function of the overserved performance in the regular price period. This is logical, as adding in an “effect” simply scales the revenue.

During performing the sales forecast for Victoria's Secret, I learned that for most part that Victoria's Secret has an incline in their profits. They have however hit a few bumps here and there. The causes of this could be more cost for Victoria's Secret purchasing materials and production of their products. Another reason for this could also be a slower rate in sales than usual. Like I said, for the most Victoria Secret has seen an incline in their profits and sales throughout the years. Performing the percentage of sales forecast for Victoria's Secret, I established a forecasted sales of 5 percent which means that they would have to have a sales of $2,808 compared to their last years $2,675. This is a very feasible number for Victoria Secret to achieve, considering that majority of their money in assets outweighs their liabilities.