Tucson Machinery, Incorporated, manufactures numerically controlled machines, which sell for an average price of $0.5 million each. Sales for these NCMs for the past two years were as follows: Use Exhibit 3.10. QUARTER LAST YEAR QUANTITY (UNITS) QUARTER THIS YEAR QUANTITY (UNITS) 1 12 1 16 2 18 2 24 3 26 3 28 4 16 4 18 Find a line using regression in Excel. Note: Round your answers to 3 decimal places. Find the trend and seasonal indexes. Note: Round your answers to 3 decimal places. Forecast sales for next year. Note: Round your answers to 2 decimal places.

Tucson Machinery, Incorporated, manufactures numerically controlled machines, which sell for an average price of $0.5 million each. Sales for these NCMs for the past two years were as follows: Use Exhibit 3.10. QUARTER LAST YEAR QUANTITY (UNITS) QUARTER THIS YEAR QUANTITY (UNITS) 1 12 1 16 2 18 2 24 3 26 3 28 4 16 4 18 Find a line using regression in Excel. Note: Round your answers to 3 decimal places. Find the trend and seasonal indexes. Note: Round your answers to 3 decimal places. Forecast sales for next year. Note: Round your answers to 2 decimal places.

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.3: Simple Regression Models

Problem 2P: The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a...

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QUARTER LAST YEAR	QUANTITY (UNITS)	QUARTER THIS YEAR	QUANTITY (UNITS)
1	12	1	16
2	18	2	24
3	26	3	28
4	16	4	18

Similar questions

The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
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Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.
The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?
Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.
A small computer chip manufacturer wants to forecast monthly ozperating costs as a function of the number of units produced during a month. The company has collected the 16 months of data in the file P13_34.xlsx. a. Determine an equation that can be used to predict monthly production costs from units produced. Are there any outliers? b. How could the regression line obtained in part a be used to determine whether the company was efficient or inefficient during any particular month?
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Management of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.
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