1.) Explain why the notes are an integral part of the financial statements

2.) Explain why the characteristics of comparability and consistency are important in financial reporting

3.) Explain the differences between accounts payable, short-term debt, current maturities of long-term debt, accrued liabilities and unearned revenue.

Consider a firm producing two goods, good A and good B, by using a fixed amount of labor. The production possibilities set of the firm is given by Y = {(a,b) ∈ R2 + | a2 +4b2 ≤ 16}. Assume the price of A and the price of B are equal to $1. Solve the revenue maximizing level of outputs for the firm.

The management and discussion and analysis (MD&A) section of the annual report provides valuable information on an entity's revenue and expenses. The information contained therein, helps deriving various ratio analyses.

What information do you find in the MD & A that is important in assessing the earnings and earnings potential of a selected company and why?

And now here we are…a Starbucks on nearly every corner. Even Homer Simpson had something to say about this in a recent episode! This is where I need your help. I would like you to perform a thorough analysis of the data involving the number of Starbucks locations. Our investors are interested to know about the rate of growth as well as to understand issues related to forecasting the number of Starbucks locations in the future. And specifically, we are wondering when the number of stores will reach 37,000 locations. You see, there are currently 37,000 McDonald’s restaurants worldwide, and we have set a goal to reach that number by the year 2020. Do you think we can do it?

1. identify the initial value and the growth rate of your exponential model and explain what they mean in context of Starbucks Stores. Put your explanations in a text box.
2. How well does the exponential function compare to the data from the Starbucks Company Time Line? Answer in a short paragraph in a text box.
3. Use your exponential model to predict when Starbucks will match McDonald’s for the number of locations.

Can you please answer the question

Education reform is one of the most hotly debated subjects on both state and national policy makers’ list of socioeconomic topics. Consider a linear regression model that relates school expenditures and family background to student performance in Massachusetts using 224 school districts. The response variable is the mean score on the MCAS (Massachusetts Comprehensive Assessment System) exam given in May 1998 to 10th graders. Four explanatory variables are used: (1) STR is the student-to-teacher ratio in %, (2) TSAL is the average teacher’s salary in $1,000s, (3) INC is the median household income in $1,000s, and (4) SGL is the percentage of single-parent households. A portion of the data is shown in the accompanying table.

SOURCE: Massachusetts Department of Education and the Census of Population and Housing.

Click here for the Excel Data File

a. For each explanatory variable, discuss whether it is likely to have a positive or negative causal effect on Score.

b-1. Estimate the sample regression equation. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

b-2. Are the signs of the slope coefficients as expected?

c. What is the predicted score if STR = 18, TSAL = 50, INC = 60, SGL = 5? (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

d. What is the predicted score if everything else is the same as above except INC = 80? (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

The following table reports the Consumer Pirce Index for the Los Angeles area on a monthly basis from January 1998 to December 2000 (base year=1982-1984). Eliminating the data for 2000, use Excel to forecast the index for all of 2000 using a three-and -six month average. Which provides a better forecast for 2000 using the data provided?

Could this be answered within excel + handwritten notes and thoroughly explained. Please and thank you

INTRODUCTION TO LINEAR CORRELATION AND REGRESSION ANALYSIS.

An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead). Consumers, of all income and wealth classes, were surveyed. Every year, 1500 consumers were interviewed. The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually. Below is the data shown for the last 24 years.

Date                X                     Y (in thousands of dollars)

1994                79.1                 55.6

1995                79                    54.8

1996                80.2                 55.4

1997                80.5                 55.9

1998                81.2                 56.4

1999                80.8                 57.3

2000                81.2                 57

2001                80.7                 57.5

2002                80.3                 56.9

2003                79.4                 55.8

2004                78.6                 56.1

2005                78.3                 55.7

2006                78.3                 55.7

2007                77.8                 55

2008                77.7                 54.4

2009                77.6                 54

2010                77.6                 56

2011                78.5                 56.7

2012                78.3                 56.3

2013                78.5                 57.2

2014                78.9                 57.8

2015                79.8                 58.7

2016                80.4                 59.3

2017                80.7                 59.9

Questions:

1. Do you think that measuring the level of optimism is a good predictor for trying to forecast future spending on luxury items? Explain why or why not.
2. How would you be able to improve on the model? You must provide a minimum of two specific ways to go about improving the model.
3. If the economist expects that, by year’s end, the average level of consumer confidence will hit 81.5 points, how much will be expected by consumers to spend on luxury items?