Prepare a report using regression analysis, Advanced Statistics

Paul Jordan has just been hired as a management analyst at Digital Cell Phone Inc. Digital Cell manufactures a broad line of phones for the consumer market. Paul's boss, John Smithers, chief operations officer, has asked Paul to stop by his office this morning. After a brief exchange of pleasantries over a cup of coffee, he says he has a special assignment for Paul: "We've always just made an education guess about how many phones we need to make each month. Usually w e just look at how many we sold last month and plan to produce about the same number. This sometimes works fine. But most months we either have too many phones in inventory or we are out of stock. Neither situation is good."

Handing Paul the table shown here, Smithers continues, "Here are our actual orders entered for the past 36 months. There are 144 phones per case. I was hoping that since you graduated recently from the University of Alaska, you might have studied some techniques that would help us plan better. It's been a while since I was in college- I think I forgot most of the details I learned then. I'd like you to analyze these data and give me an idea of what our business will look like over the next 6 to 12 months. Do you think you can handle this?"

"Of course," Paul replies, sounding more confident than he really is. "How much time do I have?"

"I need your report on the Monday before Thanksgiving-that would be November 20th. I plan to take it home with me and read it during the holiday. Since I'm sure you will not be around during the holiday, be sure that you explain things carefully so that I can understand your recommendation without having to ask you any more questions. Since you are new to the company, you should know that I like to see all the details and complete justification for recommendations from my staff."

With that Paul was dismissed. Arriving back at his office, he began his analysis.

Discussion Questions:

1.) Prepare Paul Jordan's report to John Smithers using regression analysis. Provide a summary of the cell phone industry outlook as part of Paul's response.

2.) Adding seasonality into your model, how does the analysis change?

Posted Date: 3/2/2013 3:01:36 AM | Location : United States







Related Discussions:- Prepare a report using regression analysis, Assignment Help, Ask Question on Prepare a report using regression analysis, Get Answer, Expert's Help, Prepare a report using regression analysis Discussions

Write discussion on Prepare a report using regression analysis
Your posts are moderated
Related Questions
Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi

Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the

Confounding:  A procedure observed in some factorial designs in which it is impossible to differentiate between some main effects or interactions, on the basis of the particular d

Histogram is the graphical representation of the set of observations in which class frequencies are represented by the regions of rectangles centred on the class interval. If the f

Random allocation is a technique for creating the treatment and control groups particularly in accordance of the clinical trial. Subjects receive the active treatment or the place


How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;

an oil company is considering whether or not to bid for an offshore drilling contract. The bid would cost $60 with a 65% chance of gaining the contract. Outcome success Probability

Reasons for screening data     Garbage in-garbage out     Missing data          a. Amount of missing data is less crucial than the pattern of it. If randomly

The statistical methods for estimation and inference which are based on a function of sample observations, probability distribution of which does not rely upon a complete speci?cat