Research on Madrid 2004 Bombing

In March, 2004, commuter trains in Madrid, Spain were attacked, and terrorism was suspected. Research this incident and prepare a report that describes the following:

Which group or groups were responsible for the attack? Describe how this was investigated.

How did the group carry out the attack? Provide a detailed description of the attack.

Why did the attackers choose this particular target? What did they hope to achieve?

How did investigators identify the attackers? Was anyone punished for the attack?

Conclude your report by explaining whether the group achieved its goal.

Support your responses with examples.

The project is adapted from the Chapter 4 Case Study dealing with North–South Airline In January 2012, Northern Airlines merged with Southeast Airlines to create the fourth largest U.S. carrier. The new North–South Airline inherited both an aging fleet of Boeing 727-300 aircraft and Stephen Ruth. Stephen was a tough former Secretary of the Navy who stepped in as new president and chairman of the board.

Stephen’s first concern in creating a financially solid company was maintenance costs. It was commonly surmised in the airline industry that maintenance costs rise with the age of the aircraft. He quickly noticed that historically there had been a significant difference in the reported B727-300 maintenance costs (from ATA Form 41s) in both the airframe and the engine areas between Northern Airlines and Southeast Airlines, with Southeast having the newer fleet.

On February 12, 2012, Peg Jones, vice president for operations and maintenance, was called into Stephen’s office and asked to study the issue. Specifically, Stephen wanted to know whether the average fleet age was correlated to direct airframe maintenance costs and whether there was a relationship between average fleet age and direct engine maintenance costs. Peg was to report back by February 26 with the answer, along with quantitative and graphical descriptions of the relationship.

Peg’s first step was to have her staff construct the average age of the Northern and Southeast B727-300 fleets, by quarter, since the introduction of that aircraft to service by each airline in late 1993 and early 1994. The average age of each fleet was calculated by first multiplying the total number of calendar days each aircraft had been in service at the pertinent point in time by the average daily utilization of the respective fleet to determine the total fleet hours flown. The total fleet hours flown was then divided by the number of aircraft in service at that time, giving the age of the “average” aircraft in the fleet.

The average utilization was found by taking the actual total fleet hours flown on September 30, 2011, from Northern and Southeast data, and dividing by the total days in service for all aircraft at that time. The average utilization for Southeast was 8.3 hours per day, and the average utilization for Northern was 8.7 hours per day. Because the available cost data were calculated for each yearly period ending at the end of the first quarter, average fleet age was calculated at the same points in time. The fleet data are shown in the following table.

The project is derived from a case study located at the end of chapter 4 dealing with regression analysis. Please note, however that some of the numbers in the project tables in the text have been changed so students should get their complete instructions from the Project area provided in Getting Started section of the Table of Contents. Students should use the Data Analysis add-on pack from the standard Microsoft Excel software available in every Microsoft Office software since 2007. The project requirements are:  

1. Prepare Excel Data Analysis Regression Tables demonstrating your excellence at determining Northern and Southeast Costs to Average Age. Besides the data tables, copied from the project instructions, four regression models are required each on a separate tab. Place each regression model with supporting data labels, line fit plots, and other required items on a separate worksheet tab.
2. On each worksheet tab (other than the data table tab) include:
   1. a copy of your data entry screen (Use Alt+Print Screen to copy picture of Regression Data Entry from Data Analysis in Excel and paste on correct worksheet tab).
   2. The regression model derived from the data tables.
   3. Line Fit Plot for each Worksheet tab.
   4. Labels of the data included.
   5. Highlight with yellow and label the following four items on each regression model:
      1. Coefficient of determination
      2. Coefficient of correlation or covariance
      3. Slope, and
      4. Beta or intercept
3. Finally prepare a formal response, using Microsoft Word, from Peg Jones’s to Stephen Ruth explaining your numbers and calculations. Which costs are correlated with the average age of the aircraft? What is the slope and beta? Explain the coefficient of determination and covariance. Explain how this information benefits each airline.

Submit your Excel Worksheet with five tabs (data, plus 4 tabs for the regressions) to the assignment drop box. Also include your formal response in a Microsoft Word document. Late work will not be accepted. The Excel worksheet and Word documents must be submitted BEFORE then end of Unit 7. This project is worth 160 points.

Note: Dates and names of airlines and individuals have been changed in this case to maintain confidentiality. The data and issues described here are real.

Northern Airline Data (numbers have been changed from text)

Southeast Airline Data (numbers have been changed from text)

For each of the following transactions, determine if Raymond Corporation has earned revenue during the month of May and, if so, how much it has earned.

1. Customers paid Raymond $1,500 for work Raymond will perform in June.
2. Customers purchased $6,000 of inventory for which they have not yet paid.
3. Raymond performed work for customers and was paid $3,400 in cash.
4. Customers paid Raymond $2,300 for inventory purchased in April
   
   
   Record the journal entries for above.

A poll printed the results of a survey of 880Americans focusing on their perception of the quality of Japanese products. It has been observed that the sentiment towards Japanese products has actually improved over time. Is there sufficient evidence to conclude that American sentiment towards Japanese products changed from 1999 to 2005?

Step 1 of 10: State the null and alternative hypothesis.

Step 2 of 10: What does the null hypothesis indicate about the proportions of Americans in each rating category?

The proportions of Americans in each rating category are all thought to be equal.

or

The proportions of Americans in each rating category are different for each category (and equal to the previously accepted values).

Step 3 of 10: State the null and alternative hypothesis in terms of the expected proportions for each category.

Step 4 of 10: Find the expected value for the number of Americans who rate Japanese products good to excellent. Round your answer to two decimal places.

Step 5 of 10: Find the expected value for the number of Americans who rate Japanese products average. Round your answer to two decimal places.

Step 6 of 10: Find the value of the test statistic. Round your answer to three decimal places.

Step 7 of 10: Find the degrees of freedom associated with the test statistic for this problem.

Step 8 of 10: Find the critical value of the test at the 0.025 level of significance. Round your answer to three decimal places.

Step 9 of 10: Make the decision to reject or fail to reject the null hypothesis at the 0.025 level of significance.

Step 10 of 10: State the conclusion of the hypothesis test at the 0.025 level of significance.

Using Amazon as the publicly owned company.

Describe what the firm does, its primary inputs, and its base of consumers (buyers); define the market the firm operates in;

Analyze the demand for the firm's product(s);

Evaluate the factors affecting the firm's production costs and supply decisions;

A government researcher is analyzing the relationship between retail sales (in $ millions) and the gross national product (GNP in $ billions). He also wonders whether there are significant differences in retail sales related to the quarters of the year. He collects 10 years of quarterly data. A portion is shown in the accompanying table. Retail sales (in millions) GNP (in billions) d1 d2 d3 2000 1 696048 9740.5 1 0 0 2 753211 9983.5 0 1 0 3 746875 10048.0 0 0 1 4 792622 10184.9 0 0 0 2001 1 704757 10206.2 1 0 0 2 779011 10350.9 0 1 0 3 756128 10332.2 0 0 1 4 827829 10463.1 0 0 0 2002 1 717302 10549.7 1 0 0 2 790486 10634.7 0 1 0 3 792657 10749.1 0 0 1 4 833877 10832.2 0 0 0 2003 1 741233 10940.2 1 0 0 2 819940 11073.6 0 1 0 3 831222 11321.2 0 0 1 4 875437 11508.3 0 0 0 2004 1 795916 11707.8 1 0 0 2 871970 11864.2 0 1 0 3 873695 12047.3 0 0 1 4 938213 12216.6 0 0 0 2005 1 836952 12486.3 1 0 0 2 932713 12613.0 0 1 0 3 940880 12848.7 0 0 1 4 987085 12994.1 0 0 0 2006 1 897180 13264.0 1 0 0 2 987406 13423.3 0 1 0 3 978211 13514.8 0 0 1 4 1018775 13683.2 0 0 0 2007 1 923997 13859.8 1 0 0 2 1016136 14087.6 0 1 0 3 1002312 14302.9 0 0 1 4 1062803 14489.9 0 0 0 2008 1 953358 14520.7 1 0 0 2 1032919 14647.3 0 1 0 3 1006551 14689.2 0 0 1 4 966329 14317.2 0 0 0 2009 1 839625 14172.2 1 0 0 2 919646 14164.2 0 1 0 3 926265 14281.9 0 0 1 4 985649 14442.8 0 0 0

a. Estimate y = β0 + β1x + β2d1 + β3d2 + β4d3 where y is retail sales, x is GNP, d1 is a dummy variable that equals 1 if quarter 1 and 0 otherwise, d2 is a dummy variable that equals 1 if quarter 2 and 0 otherwise, and d3 is a dummy variable that equals 1 if quarter 3 and 0 otherwise. Here the reference category is quarter 4. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

d-1. Reformulate the model to determine, at the 5% significance level, if sales differ between quarter 2 and quarter 3. Your model must account for all quarters. Use quarter 3 as the reference category. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

Revenue recognition – accrual basis vs. cash basis: Ring The Bells, Inc. provides doorbell repair services to customers and began operations in February 2018. On March 4^th, 2018, Ring The Bells, Inc. collected $2,400 in cash from customers for services performed in February 2018. On March 11^th, Ring The Bells, Inc. provided $690 worth of services to customers, all of whom paid in cash. On March 25^th, 2018 Ring the Bells provided additional services worth $3,470 on account to customers, which will not be collected until April.

(1pt) Using accrual-basis accounting, how much revenue would Ring the Bells record for March 2018? Briefly explain or show how you got your answer.

(1pt) Using cash-basis accounting, how much revenue would Ring the Bells record for March 2018? Briefly explain or show how you got your answer.

Expense recognition – accrual basis vs. cash basis: Ring The Bells, Inc. provides doorbell repair services to customers and began operations in February 2018. On March 2^nd, 2018, Ring The Bells, Inc. paid $800 in cash to creditors for supplies purchased on account on February 1^st and used in February 2018. On March 15^th, Ring The Bells, Inc. paid $1,850 in cash to employees for work done March 1^st-15^th. On March 29^th, 2018 Ring the Bells received a bill of $720 from the utility company for March utilities used which will not be paid until April.

(1pt) Using accrual-basis accounting, how much in expenses would Ring the Bells record for March 2018? Briefly explain or show how you got your answer.

(1pt) Using cash-basis accounting, how much in expenses would Ring the Bells record for March 2018? Briefly explain or show how you got your answer.

A company has three manufacturing plants, and you want to determine whether there is a difference in the average age of workers at the three locations. The following data are the ages of five randomly selected workers at each plant. Perform a test to determine whether there is a significant difference in the mean ages of the workers at the three plants. Use α = 0.01. Interpret on your findings.

You are the owner of a lawn service company (LawnCo) which provides grounds and maintenance services to a range of corporate customers. Customers are expected to pay on the first of each month, in advance of receiving services. One of your corporate customers is an eldercare facility whose grounds you have maintained for many years. The customer has not paid for the last three months of services (from Oct.–Dec. 2020); nevertheless, to maintain a positive relationship, your company continued to provide mowing and weed control services to the eldercare facility during that time. Your company ceased providing services in January 2021 and found out in that same month that the eldercare facility filed for bankruptcy in September. Your company now believes that collection of the missed payments is extremely unlikely.  Your company has already issued financial statements to lenders (for the period ending 12/31/20) which reflected revenue and a corresponding account receivable related to this customer of $10,000 per month for services provided to this customer. Those financial statements also reflected the company’s standard allowance (reserve) amount on receivables, of 4% of sales. In total, your company’s average monthly sales amount to $500,000.

Required:

Your paper should be structured in the format of an issues memo.

1. Evaluate whether receipt of this information indicates you have a change in accounting estimate or whether the customer’s bankruptcy should result in this event being considered an error in previously issued financial statements.

2. Next, describe the accounting treatment (as required by the Codification) for each alternative, then support your explanations with draft journal entries.

3. Finally, briefly state which treatment appears to be more appropriate given the circumstances. If you must make any assumptions in reaching this conclusion, state these.