Estee Lauder Bus 225

please help me understand the problem

To carry out their analysis, planning, implementation, and control responsibilities, marketing managers need a marketing information system (MIS) to assess information needs, develop the needed information, and distribute it in a timely manner. Assume that you are a Marketing Manager of Foodpanda and your company wants you to deploy an efficient Marketing information system. Explain how marketing intelligence will help Foodpanda in collecting information and forecasting demand?

An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. Table 3   Quarter Percent change in income Percent Change in appliance sold Quarter Percent change in income Percent Change in appliance sold 1 -2.3 -2.5 6 -1.0 1.0 2 -1.5 -1.0 7 0.7 1.4 3 2.8 7.4 8 5.2 3.4 4 0.5 2.6 9 -2.5 -0.5 5 4.6 8.5 10 1.7 1.8 1) What forecasting model should be used for this data.Why? 2) Develop the forecasting model that you have proposed in(a). 3) Compute the relationship for these data. In your opinion, is the relationship between independent variable strong enough to base a predictive the…

The following table shows quarterly sales (in thousand units) for a product over 4 years. The overall sales average for the entire 4 years is 166.125 (thousand units). Fill in the missing values assuming there is no trend. Round seasonal indexes to 4 decimal places. Report Averages accurate to at most 2 decimal places. Report Actual sales ('000) accurate to the nearest integer. Year Year Seasonal Year 1 Year 2 Average 4 Index Quarter 205 211 182 1.1768 1 Quarter 152 170 158 156 2 Quarter 182 190 198 193 3 Quarter 128 112 113 0.7178 4

The table below shows the sales for a plastics manufacturer recorded over the past year. The seasonal indexes for each quarter are also provided). To track the trend for these four quarters, use the indexes to deseasonalize the sales data. Quarter 1 Sales 738 Index 75.0 Deseasonalized Sales 234 1012 104.0 1196 121.0 962 100.0 What are deseasonalized sales for quarter 2? 973.1 1052.5 1291.5 1012.0 1027.7

Hi, I need help with solving for the following values (boxed). Thank you.

An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. (Hint: Provides your answers in two decimal points)Table 1 Quarter % change in income % Change in appliance sold Quarter % change in income % Change in appliance sold 1 -2.3 -2.5 6 -1.0 1.0 2 -1.5 -1.0 7 0.7 1.4 3 2.8 7.4 8 5.2 3.4 4 0.5 2.6 9 -2.5 -0.5 5 4.6 8.5 10 1.7 1.8 (a) What forecasting model should be used for this data. Why? (b) Develop the forecasting model that you have proposed in (a)

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The following table shows quarterly sales (in thousand units) for a product over 4 years. The overall sales average for the entire 4 years is 126.0625 (thousand units).Fill in the missing values assuming there is no trend.Round seasonal indexes to 4 decimal places.Report Averages accurate to at most 2 decimal places.Report Actual sales ('000) accurate to the nearest integer.   Year 1 Year 2 Year 3 Year 4 Average Seasonal Index Quarter 1 92 93 95 106     Quarter 2 105 106 105 101     Quarter 3 197 187   196   1.5211 Quarter 4   106 116 121   0.8865 PART BSuppose actual quarterly sales (in thousands) for Year 5 are 93, 123, 206, and 126 respectively. Assuming there is no trend, forecast sales for the four quarters of Year 5.Use seasonal indexes (rounded to 4 decimal places) from Part A.Report forecast answers as integers accurate to the nearest thousand.Quarter 1 forecast =  thousandQuarter 2 forecast =  thousandQuarter 3 forecast =  thousandQuarter 4 forecast =…

The table below shows the sales figures for a brand of shoe over the last 12 months.   Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- 1. A simple three-month moving average. 2. A three-period weighted moving average using weights of 1, 2, and 3. Assign the highest weight to the most recent data.                    3. Exponential Smoothing when α= .6 and the forecast for March is 350. 4. Determine which of the three forecasting techniques is the most accurate using MAD.

Since the Covid-19 outbreak, the use of sports facilities and venues has dropped significantly. You have a group of friends who are frequent visitors to a swimming pool and they are interested in understanding the impact of Covid-19 on the income of the swimming pool operator. Knowing that you have learned the knowledge related to making forecasts, your friends ask for your opinion on the following questions.  Please use relevant data in the Excel workbook Q2_input_file.xlsx in Canvas (next to this question paper) to answer the following questions.  (a) Comment on the underlying pattern in the swimming pool attendances over 2016 1Q – 2019 4Q. Please limit the answer to within one page.  (b) Use a suitable method to forecast the swimming pool attendances for every quarter between 2020 1Q and 2021 2Q, assuming that actual data in that range is not yet available. After that, combined with the actual data, estimate the income loss of the swimming pool for each quarter in that range,…

Paraphrase this one. Analyze and elaborate in 200 words. Why organizations use time series data analysis? Time series analysis helps organizations understand the underlying causes of trends or systemic patterns over time. Using data visualizations, business users can see seasonal trends and dig deeper into why these trends occur. With modern analytics platforms, these visualizations can go far beyond line graphs. When organizations analyze data over consistent intervals, they can also use time series forecasting to predict the likelihood of future events. Time series forecasting is part of predictive analytics. It can show likely changes in the data, like seasonality or cyclic behavior, which provides a better understanding of data variables and helps forecast better.

PLEASE CHOOSE ONE ANSWER AND CLARIFY THE CHOICE A quantitative forecasting class assumes that sales (or other items to be forecast) follow a repetitive pattern over time. When a retailer uses daily sales of each product to identify patterns and to forecast inventory requirements, this is an example of: A::a deterministic model B::a causal model C::a time series forecasting technique D::a qualitative model       “A” items are high-dollar value items which represent a small portion (usually 10-20 percent) of requisitions, purchase orders, and inventory items, but a large portion of annual spend (usually 70-80 percent). “A” items in ABC analysis are: A::reviewed infrequently B::normally carried in large quantities C::stored in a relatively insecure warehouse D::particularly critical in financial terms       Decoupling inventories are carried __________________________________. The amounts and locations of raw material, work-in-process, and finished goods decoupling inventories depend on…

Cell phone sales for a California-based firm over the last 10 weeks are shown in the following table. Plot the data, and visually check to see if a linear trend line would be appropriate.Then determine the equation of the trend line, and predict sales for weeks 11 and 12.Week Unit Sales1 7002 7243 7204 7285 7406 7427 7588 7509 77010 775

Create a line graph for this set of monthly sales numbers. Run a regression analysis.       What is the regression equation?     Is the regression equation significant? How can you tell? What is the Rsquare?  What does this signify?   What is the sales forecast for month 13?       1 550   2 548   3 546   4 549   5 550   6 548   7 551   8 551   9 552   10 551   11 553   12 553

Assume that this restaurant was one of a chain of 20 restaurants across Greater Sydney with a head office in the CBD. Compare and contrast the Jury of Executive Opinion and the Sales Force Composite Method when it comes to generating business forecasts. You must contextualise your discussion to this case study

Calculate and answer parts a through d. Include all calculations and spreadsheets in your post. Explain why the moving average method was used instead of another forecasting method. What might be another forecasting method that could prove to be just as useful? The figures below indicate the number of mergers that took place in the savings and loan industry over a 12-year period. Year Mergers Year Mergers 2000 46 2006 83 2001 46 2007 123 2002 62 2008 97 2003 45 2009 186 2004 64 2010 225 2005 61 2011 240 Calculate a 5-year moving average to forecast the number of mergers for 2012. Use the moving average technique to determine the forecast for 2005 to 2011. Calculate measurement error using MSE and MAD. Calculate a 5-year weighted moving average to forecast the number of mergers for 2012. Use weights of 0.10, 0.15, 0.20, 0.25, and 0.30,with the most recent year weighted being the largest. Use regression analysis to forecast the number of mergers in 2012.

The following table shows the number of televisions sold over the last ten years at a local electronic store. Year TV Sales  1 150 2 300 3 480 4 600 5 630 6 640 7 700 8 825 9 900 10 980 i. Using trend projection, develop a formula to predict sales for years 11 and 12. You have to show all working. You will need to develop a table to calculate the slope and the intercept. ii. Use that formula to forecast television sales for years 11 and 12.

Please help with correct answers in details: step by step as last submission were given incorrect answers A statistical program is recommended. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. Quarter Year 1 Year 2 Year 3 1 1,690 1,800 1,850 2 940 900 1,100 3 2,625 2,900 2,930 4 2,500 2,360 2,615

The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.

Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the 3-period weighted moving average method to forecast the number of sales to expect next month.  Use the following weights:  0.4 for the most recent, 0.3 for the 2nd most recent, and 0.3 for the 3rd most recent. Month Demand Forecast 1 308 337 2 388 341.4 3 344 368 4 400 342.8 5 341 378.4

Although the unpredicted, yet disruptive, impact of the CoViD-19 pandemic is global and has negatively affected all organizations, identify a business organization that you think has been affected the most. In the new normal, which forecasting time horizon (short-range, medium-range, or long-range) would you suggest should be adopted by this organization in forecasting the demand for its main product? Justify your answer. Cite your assumptions. Cite 2 to 3 factors that this business organization should use as a basis for forecasting the demand for its main product. Justify your answer.

Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.

As a Sales Head for a consumer durable firm, you wish to have sales forecast trends based on past sales rendered. Briefly describe the methods of forecasting future demand on the basis of past sales.

What changes would you make if you were in control of the iTunes store's database administration? Which methods of forecasting would you suggest employing predictive analytics for in order to ascertain which musical acts and films will have the biggest number of ticket sales in the next year?

Please answer parts i, ii and iii of the below question.  The table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January  69 February  75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150   Using the following, forecast the sales for the months up to January the following year:- i) A simple three month moving average. ii) A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii) Exponential Smoothing when α= .6 and the forecast for March is 350.