MAT 240 Project One

the following data represents a set do demands that have occurred over the last several years at a soap making company.  The data were collected on an annual basis. Year Actual Demand (At) Forecast (Ft) 1 310   2 365   3 395   4 415   5 450   6 465   7     a) using the SIMPLE AVERAGE method to predict the demand for the 7th year b) the SIMPLE MOVING AVERAGE method to predict the demand for the 7th year

Question 9 Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. Y = 120 - 15 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to: O Increase by 120 units Decease by 30 units O Increase by 2Q units Next « Previous Submi No new data to save. Last checked at 9:51pm

I Consider the demand for trading cards listed below. Month Demand Jan. 51,000 48,000 Feb. March 55,000 April May 58,000 66,000 June 69,000 80,000 July Aug. 95,000 Use Excel to prepare a forecast for September, October, and November using linear regression Print out the sheet of results, as well as a sheet containing the formulas that you used ( can be used to toggle between displaying values and displaying formulas or you can click on Formulas>Formula Auditing→Show Formulas.) and for the cars is 16.000

In your company (electrical goods manufacturing), you want to forecast demand as well of a particular range of Smart TVs. Its monthly sales previous year, are presented in the table below: Month Sales January 400 February 650 March 1,150 April 1,700 May 500 June 900 July 1,150 August 1900 September 600 October 650 November 1,600 December 2050 Based on the above historical sales data: A) Create the corresponding graph and comment on the demand (sales) in terms of in trend, seasonality and periodicity please draw the diagram!!!!

7 Suppose the following model describes the relationship between annual salary (salary) and the number of previous years of labor market experience (exper): log(salary) = 10.6 + .027 exper. (i) What is salary when exper = 0? When exper = 5? (Hint: You will need to exponentiate.) (ii) Use equation (A.28) to approximate the percentage increase in salary when exper increases by five years. (iii) Use the results of part (i) to compute the exact percentage difference in salary when exper = 5 and еxper = 0. Comment on how this compares with the approximation in part (ii).

The Wall Street Journal’s website, www.wsj.com, reported the number of cars and light-duty trucks sold through October of 2014 and October of 2015. The top sixteen manufacturers are listed here. The sales information for all manufacturers can be accessed in a data file below.  Sales data are often reported in this way to compare current sales to last year’s sales.     Year-to-Date Sales   Manufacturer Through October 2015   Through October 2014   General Motors Corp. 2,562,840   2,434,707   Ford Motor Company 2,178,587   2,065,612   Toyota Motor Sales USA Inc. 2,071,446   1,975,368   Chrysler 1,814,268   1,687,313   American Honda Motor Co Inc. 1,320,217   1,281,777   Nissan North America Inc. 1,238,535   1,166,389   Hyundai Motor America 638,195   607,539   Kia Motors America Inc. 526,024   489,711   Subaru of America Inc. 480,331   418,497   Volkswagen of America Inc. 294,602   301,187   Mercedes-Benz 301,915   281,728   BMW of North America Inc.…

You are a member your company"s strategic planning group. Your company is in the business equipment sales and services field. You are tasked with the following: a. Using the National Income and Product Accounts, develop some benchmark measures of the overall economy and your business in order to provide a standard for judging performance. b. Distinguish between CPI and GDP deflator calculations and suggest which might be more appropriate for benchmarking your business-to-business pricing strategy. c. Employee recruitment is central to your company"s success. Distinguish between structural and cyclical unemployment. Explain how unemployment can vary between demographic groups and how this might influence your recruiting efforts. d. Since your company has operations in Europe as well as Asia, please provide some guidance on the differences in European and American labor markets that would impact your decisions on plant location, sales, and labor market hiring policies in these…

DQ1:  Electric Vehicles and Battery Supply Chain As the automotive industry shifts toward electric vehicles (EVs), there is growing attention on the supply chain for batteries, a crucial component. Explore the relationship between supply and demand in the context of electric vehicles: How has the growing demand for electric vehicles impacted the demand for battery components? How have companies like Tesla and other automakers responded to this increased demand? Discuss the concept of supply constraints in the battery industry. How do factors like access to raw materials, technological advancements, and production capacity influence the supply of batteries for electric vehicles?   DQ2:  Think about a product or service that has undergone a dramatic increase in popularity in recent years, such as electric vehicles (EVs) or streaming services. Discuss how changes in consumer preferences and technological advancements have influenced the demand for this product or service. How have…

The monthly demand of a company is showed below, please use the static method to forecast the demand for Year 6. Sales Year 1 Year 2 Year 3 Year 4 Year 5 JAN 2,000 3,000 2,000 5,000 5,000 FEB 3,000 4,000 5,000 4,000 2,000 MAR 3,000 3,000 5,000 4,000 3,000 APR 3,000 5,000 3,000 2,000 2,000 MAY 4,000 5,000 4,000 5,000 7,000 JUN 6,000 8,000 6,000 7,000 6,000 JUL 7,000 3,000 7,000 10,000 8,000 AUG 6,000 8,000 10,000 14,000 10,000 SEP 10,000 12,000 15,000 16,000 20,000 OCT 12,000 12,000 15,000 16,000 20,000 NOV 14,000 16,000 18,000 20,000 22,000 DEC 8,000 10,000 8,000 12,000 8,000 Total 78,000 89,000 98,000 115,000 113,000

Below is a table containing data on product demand for the most recent three months along with the forecasts that had been made for those three previous months. Calculate the MSE. Month Demand Forecast 1 308 310 388 390 344 342 23

Sonia is planning to start a new designer cloth shop. Her problem is to decide how large her shop should be. The annual returns will depend on both the size of her shop and a number of marketing factors related to the current market conditions and demand for designer wear. After a careful analysis, Sonia came up with the following table: Size of shop good market (R.O) fair market (R.O) poor market (R.O) Samll scale 1024 9765 -500 Medium scale  1500 3000 -2000 Large scale  2000 3000 -4000 Very large scale  3000 5000 -7000 a)what will be her decision based on Pessimist criteria? b) what will be her decision based on Optimistic criteria? c) what will be her decision based on Laplace criteria?

Ypsilanti Market Research conducted a survey to find out whether people who earn more money purchase more expensive goods. The following graph indicates the relationship between income the survey subjects earned and the price of the home that they purchased. PRICE (Thousands of dollars per home) 500 450 400 350 300 250 200 150 100 50 L 0 10 20 30 40 50 60 70 80 INCOME (Thousands of dollars per year) 90 100

Demand Factor Average American household income Roundtrip airfare from Des Moines (DSM) to Atlantic City (ACY) Room rate at the Continental Hotel and Casino, which is near the Rivers PRICE (Dollars per room) Use the graph input tool to help you answer the following questions. You will not be graded on any changes you make to this graph. Note: Once you enter a value in a white field, the graph and any corresponding amounts in each grey field will change accordingly. 500 450 400 350 300 250 200 150 100 50 0 0 Demand 50 100 150 200 250 300 350 400 450 500 QUANTITY (Hotel rooms) Graph Input Tool Market for Rivers's Hotel Rooms Price (Dollars per room) Quantity Demanded (Hotel rooms per night) Demand Factors Average Income (Thousands of dollars) Initial Value $50,000 per year $200 per roundtrip $250 per night Airfare from DSM to ACY (Dollars per roundtrip) Room Rate at Continental (Dollars per night) 350 150 50 200 250 ?

A random sample of 100 households has been selected in order to establish a price index for housing utilities. The following average annual figures have been obtained. Housing Utilities 2017 Electricity 1,97 Gas 7,90 0,29 2,40 Telephone Water Price(Rand/Unit) 2018 2,05 8,25 0,30 2,45 2019 2,09 8,60 0,31 2,50 2017 62 9 296 55 Quantities 2018 64 9 297 56 2019 68 10 298 58 . a) Find the price relative for Electricity, using (2017= 100). Interpret. b) Find the quantity relative for Water, using (2018= 100). Interpret. c) Calculate the Laspeyre's price index for 2019, using 2017 = 100. What is the percentage increase in 2019 price over those in 2017? Interpret. d) Calculate the Paasche's price index for 2018, using 2017 = 100. What is the percentage increase in 2018 price over those in 2017? Interpret. e) By how much has this households utility in these four utilities changed between 2017 and 2019? Assume price are held constant at base year 2017.

5. Exercise 5.5 A firm experienced the demand shown in the following table. Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 forecasts may be begun by assuming Y t+ F Yt •) and w = 0.3 ). (Note: The exponential smoothing Moving Average Actual Demand (5-year) (3-year) Exponential Smoothing (W = 0.9) Year (W = 0.3) 2000 900 2001 885 900 900 2002 875 2003 870 887 ▼ 2004 870 877 ▼ 2005 875 880 872 Y 2006 885 875 872 2007 900 875 877 2008 920 880 887 - 2009 945 890 902 Y 2010 905 922 The following table shows the square errors, (Y; - T1-) , for forecasts from 2005 through 2009. Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Exponential Smoothing Moving Average Year (5-year) (3-year) (W = 0.9) (W = 0.3) 2005 25 9 25 25 2006 100 169 100 36 2007 625 529 256 361 2008 1,600 1,089 484 1,089 2009 3,025 1,849 729 2,304 RMSE Based on the RMSE criterion,…

The table below is extracted from Goodland Republic Bureau of Statistics records for 2016 -2017. Use the information to answer the questions that follow. Item     Price 2017 (Base Year)   Price 2018 Production Price per Unit ($) Production Price per Unit ($) Rice (tons) 50,000 1.50 55,000 2.00 Wheat (tons) 100,000 2.00 98,000 2.50 Tractors mid-size (units) 50,000 23000.00 45,000 2,450.00 Cotton (tons) 120,000 100.00 110,000 120.00 Used cars 5,000 5,000.00 6,000 7,000.00 Manufacture garments (tons) 150,000 50.00 145,000 70.00 Eggs (trays) 2,000 2.50 2,300 3.50 Coca Cola (litres) 6,000 0.80 6,500 1.20 Pepsi Cola (litres) 700 1.10 850 1.50 Beef (tons) 5,000 6.50 4,800 8.50 Second Hand Clothes (tons) 500 15.00 450 25.00 Alcoholic Beverages (litres) 500 3.25 600 3.75 Milk (litres) 7,000 2.30 7,500 2.50 Examine the…

The table below is extracted from Goodland Republic Bureau of Statistics records for 2016 -2017. Use the information to answer the questions that follow. Goodland Economy 2013 and 2018 I tem Price 2017 (Base year) Price 2018 Price per Price per Unit ($) | Production 55,000 98,000 45,000 2,450.00 110,000 6.000 7,000.00 Unit ($) Production 50,000 100,000 50,000 23,000.00 120,000 5,000 Rice ( tons) Wheat (tons) Tractors mid-size (units) Cotton (tons) Used cars Manufacture garments ( tons) Eggs (Trays) Соса Cola (litres) Pepsi Cola (litres) Beef (tons) Second hand cloths (tons) Alcoholic Beverages (litres) Milk (litres) 1.50 2.00 2.00 2.50 100.00 120.00 5,000.00 50.00 150,000 2,000 6,000 700 145,000 2,300 6,500 70.00 2.50 3.50 0.80 1.20 1.50 1.10 850 5,000 500 500 4,800 450 600 6.50 8.50 15.00 25.00 3.25 3.75 7,000 2.30 7,500 2.50 Examine the status of the economic welfare in Goodland Republic in 2018 based on your GDP deflator, nominal GDP and Real GDP. Also, explain the reasons why it is…

10 00 Interest Rate (%) N B Investment Demand 0 $30 60 90 120 150 Investment ($) Price Level Multiple Choice AS Real GDP ($) AD₁ (1=120) AD₂ (1=90) *AD3 (1=60) Refer to the graphs, in which the numbers in parentheses near the AD₁, AD2, and AD3 labels indicate the level of investment spending associated with each curve. All numbers are in billions of dollars. The interest rate and the level of investment spending in the economy are at point D on the investment demand curve. To achieve the long-run goal of a noninflationary, full-employment output Qfin the economy, the Fed should try to decrease aggregate demand by increasing the interest rate from 2 to 4 percent. decrease aggregate demand by increasing the interest rate from 4 to 6 percent. increase aggregate demand by decreasing the interest rate from 4 to 2 percent. increase the level of investment spending from $120 billion to $150 billion.

5. Among important factors that affecting the price of land lot are size, number of mature trees and distance to the lake. Using data for 60 recently sold land lots are shown below: B 1 SUMMARY OUTPUT 2 3. Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 0.4924 0.2425 0.2019 40.24 8 Observations 60 9. 10 ANOVA Significance F 5.97 11 df S MS 9676.6 0.0013 12 Regression 13 Residual 3 29,030 90,694 56 1619.5 14 Total 59 119,724 15 16 Coefficients Standard Error t Stat P-value 0.0331 0.2156 17 Intercept 51.39 23.52 2.19 18 Lot size 0.700 0.559 1.25 19 Trees 0.679 0.229 2.96 0.0045 20 Distance -0.378 0.195 -1.94 0.0577 a) Write the regression equation b) What is the standard error of estimate? Interpret its value. c) What is the coefficient of determination? Interpret its value. d) What is the adjusted coefficient of determination? Interpret its value. e) Test the validity of the model. f) Interpret each of the coefficients. g) Test at 5% level of…

Forecast the demand for the rice for a country for the year 2019 on the basis of 7-year data given in table: Year                                              2012 2013 2014 2015 2016 2017 2018 Population (millions)                      10     12      15    20      25    30     40 Rice consumed  (million tonnes)     40     50      60    70     80     90    100

Sales Sales Force Sales Force Training Performance Effectiveness Sales Force Customer Orentation Please perform the quantitative analysis with the above variables. 1.0 Introduction 1.1 Objectives 1.2 Assumptions 1.3 Other Considerations 1.4 Hypotheses

Question 1 (AV7.1) You have been employed as the chief economist for the economy SKL Land. The head statistician has provided you with the following information: Compensation of Employees 900 Consumption of goods 850 Corporate profits 400 Rent Income 125 Factor income paid to the world 325 Consumption of services 475 Factor Income received from the world 170 Residential investments 350 Indirect taxes 775 Non-residential investments 525 Subsidies 125 Government Expenditure 925 Depreciation 120 Imports 700 Net interest 75 Exports 300 Proprietors income 300   Calculate SKL Land’s GDP using (1) the Income and (2) the Expenditure Approach

For each of the proposals, use the previous graph to determine the new number of research assistants hired. Then compute the after-tax amount paid by employers (that is, the wage paid to workers plus any taxes collected from the employers) and the after-tax amount earned by research assistants (that is, the wage received by workers minus any taxes collected from the workers). Levied on Employers (Dollars per hour) 4 Tax Proposal 0 2 Levied on Workers (Dollars per hour) 0 4 2 Quantity Hired (Number of workers) After-Tax Wage Paid by Employers (Dollars per hour) O The proposal in which the entire tax is collected from workers O The proposal in which the tax is collected from each side evenly O The proposal in which the tax is collected from employers O None of the proposals is better than the others After-Tax Wage Received by Workers (Dollars per hour) Suppose the government doesn't want to discourage employers from hiring research assistants and, therefore, wants to minimize the share…

21. Consider a firm subject to quarter-to-quarter variation in its sales. Suppose that the following equation was estimated using quarterly data for the period 2011–2018 (the time variable goes from 1 to 32). The variables D1, D2, and D3 are, respectively, dummy variables for the first, second, and third quarters (e.g., D1 is equal to 1 in the first quarter and 0 otherwise). Qt =a+bt+c1D1+c2D2+c3D3 The results of the estimation are presented here:   a. Calculate the intercept in each of the four quarters. What do these values imply?  b. Use this estimated equation to forecast sales in the fourth quarter of 2019.

Question: a) Calculate Regression Analysis of the data. b) Calculate Profit of a shop for 45 units sales

analysis of the data indicated that the demand curve for x product is estimated to be linear and given by equation Qd = 150-3P and the supply curve for x product appears to be linear as well and is estimated as Qs=P-10. Graphically draw these two curves, labeling all relevant looking (such as intercepts for each line) on the horizontal and vertical axes

I- Demand for a product is estimated to be Q=960 - 1.2P + 1.4Y +.003A where, Q and P are the quantity and price of the product respectively, Y is income, and A is the advertising expenditures. All the variables are in the natural logarithmic form and all the estimated coefficients are statistically significant. The average annual sale and the average price of the product are 60000 units and $8000 respectively. A. Price elasticity of demand is -------------, income elasticity of demand is ---------, advertising elasticity of demand is B. The optimum level of advertising spending for the firm is

■CASE STUDY THE PROPERTY MANAGER AS ECONOMIST-PLANNER After graduating from college with honors and a master's degree in eco- nomics, Charles Gill was hired by the local urban renewal authority in his home town of approximately 500,000 people. His responsibilities were in the areas of statistics, financial planning, and research. When activities of the urban renewal authority began to wind down upon completion of a major downtown redevelopment project, one of the directors, a businessman who had acquired some real estate investment property, hired Charles to manage one of his residential rental properties. The area's economy had slowed with the general downturn that occurred throughout the country and severely depressed the price of real estate in many areas, including property in Charles's town. In addition, a local defense factory had closed, leaving hundreds out of work. Charles saw there were suddenly many properties available that were priced far less than they had sold for just a…

PRICE (Dollars per room) 500 450 400 350 300 250 200 150 100 50 0 Demand D 50 100 150 200 250 300 350 400 450 500 QUANTITY (Hotel rooms) Graph Input Tool Market for Oceans's Hotel Rooms Price (Dollars per room) Quantity Demanded (Hotel rooms per night) Demand Factors Average Income (Thousands of dollars) Airfare from MSY to ACY (Dollars per roundtrip) Room Rate at Meadows (Dollars per night) 350 150 50 200 250 ? For each of the following scenarios, begin by assuming that all demand factors are set to their original values and Oceans is charging $350 per room per night. If average household income increases by 20%, from $50,000 to $60,000 per year, the quantity of rooms demanded at the Oceans from rooms per night to rooms per night. Therefore, the income elasticity of demand is. , meaning that hotel rooms at the Oceans are If the price of an airline ticket from MSY to ACY were to increase by 10%, from $200 to $220 roundtrip, while all other demand factors remain at their initial values,…