18. The number of defects found in 25 samples of 100 Malossdientes Candy Company lemon drops taken on a daily basis from a production line over a five- week period is given in the worksheet Prob. 9-18.a. Compute dpmo and find the sigma level.b. Plot these data on a run chart. Can you identify any special causes? C. Explain what the Sigma Level means below: Malossdientes Candy CompanyRun ChartNumber of VALUES (<= 30)= SampleAverage12345678910111213141516171819202122232425Sample1Defects2Center 5.8824Defects Center764733439891511277837251458245.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.885.88Calculation of Sigma Value11.5649375.88Enter number of samples16141210642021.5465.8813.06492545.8834675.8851. Click the yellow cell, click on " button above. Select "statistical" fromcategory drop-down. Scroll down statistical selections. Find and select2. NORM.S.INY dialog box will open. Type in the following into the "Probability"text box: (1-.0588). Click OK. (see explanation to the right)3. In the blue cell, type in the standard sigma shift (p469)4. Sigma Level (value) will auto-calculate. Explain what the Sigma Level meansCopy Deleces colomm mito the genot vens detot. Jampre i matGNES TOY735.8867835.888945.889101035.88Chart will auto-populate and format111195.8812 13141285.88151395.881614155.881718AAnalyze chart data. Do not describe the chart!Analyze and explain what the chart data means.Incorporate analysis of the data, and your responses to the problem questions inthe text, in a narrative format using the Report Template.15115.8819The reason for the equation is we have to identify the probability of finding a valuebetween 1.000 and the mean of the distribution (0.0588 or 5.88)201625.8821221775.8823241875.88251985.88--Defects-Center2035.882175.882215.882345.882455.882585.88

Defects Per Million Opportunities is what DPMO stands for. It is a statistical indicator of process…

18. The number of defects found in 25 samples of 100 Malossdientes Candy Company lemon drops taken on a daily basis from a production line over a five- week period is given in the worksheet Prob. 9-18. a. Compute dpmo and find the sigma level. b. Plot these data on a run chart. Can you identify any special causes? C. Explain what the Sigma Level means below:

18. The number of defects found in 25 samples of 100 Malossdientes Candy Company lemon drops taken on a daily basis from a production line over a five- week period is given in the worksheet Prob. 9-18. a. Compute dpmo and find the sigma level. b. Plot these data on a run chart. Can you identify any special causes? C. Explain what the Sigma Level means below:

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 1P: The file P13_01.xlsx contains the monthly number of airline tickets sold by a travel agency. a. Does...

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The file P14_01.xlsx contains data on 100 consumers who drink beer. Some of them prefer light beer, and others prefer regular beer. A major beer producer believes that the following variables might be useful in discriminating between these two groups: gender, marital status, annual income level, and age. a. Use logistic regression to classify the consumers on the basis of these explanatory variables. How successful is it? Which variables appear to be most important in the classification? b. Consider a new customer: Male, Married, Income 42,000, Age 47. Use the logistic regression equation to estimate the probability that this customer prefers Regular. How would you classify this person?
An antique collector believes that the price received for a particular item increases with its age and with the number of bidders. The file P13_14.xlsx contains data on these three variables for 32 recently auctioned comparable items. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Is the antique collector correct in believing that the price received for the item increases with its age and with the number of bidders? Interpret the standard error of estimate and the R-square value for these data.
Management of a home appliance store would like to understand the growth pattern of the monthly sales of Blu-ray disc players over the past two years. Managers have recorded the relevant data in the file P13_33.xlsx. a. Create a scatterplot for these data. Comment on the observed behavior of monthly sales at this store over time. b. Estimate an appropriate regression equation to explain the variation of monthly sales over the given time period. Interpret the estimated regression coefficients. c. Analyze the estimated equations residuals. Do they suggest that the regression equation is adequate? If not, return to part b and revise your equation. Continue to revise the equation until the results are satisfactory.
The file P13_27.xlsx contains yearly data on the proportion of Americans under the age of 18 living below the poverty level. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Create a chart of the series with the forecasts superimposed from this optimal smoothing constant. Does it make much of an improvement over the model in part b? d. Write a short report to summarize your results. Considering the chart in part c, would you say the forecasts are good?
The file P13_19.xlsx contains the weekly sales of a particular brand of paper towels at a supermarket for a one-year period. a. Using a span of 3, forecast the sales of this product for the next 10 weeks with the moving averages method. How well does this method with span 3 forecast the known observations in this series? b. Repeat part a with a span of 10. c. Which of these two spans appears to be more appropriate? Justify your choice.
The file P13_20.xlsx contains the monthly sales of iPod cases at an electronics store for a two-year period. Use the moving averages method, with spans of your choice, to forecast sales for the next six months. Does this method appear to track sales well? If not, what might be the reason?
The file P13_01.xlsx contains the monthly number of airline tickets sold by a travel agency. a. Does a linear trend appear to fit these data well? If so, estimate and interpret the linear trend model for this time series. Also, interpret the R2 and se values. b. Provide an indication of the typical forecast error generated by the estimated model in part a. c. Is there evidence of some seasonal pattern in these sales data? If so, characterize the seasonal pattern.
The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?
The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 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.
The file P13_25.xlsx contains the quarterly numbers of applications for home mortgage loans at a branch office of Northern Central Bank. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b? Is it guaranteed to produce better forecasts for the future?
Stock market analysts are continually looking for reliable predictors of stock prices. Consider the problem of modeling the price per share of electric utility stocks (Y). Two variables thought to influence this stock price are return on average equity (X1) and annual dividend rate (X2). The stock price, returns on equity, and dividend rates on a randomly selected day for 16 electric utility stocks are provided in the file P13_15.xlsx. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Also, interpret the standard error of estimate and the R-square value for these data.