Below shown is a logical representation of an index table built on columnASearchKeyRecord LocationG0052341G0989673G0995379G13679013Based on the provided information, which one of the following statements is correct?O a. It is most likely a clustered index, but could possibly be non-clusteredO b. There is not enough information to conclude the nature of this indexO c. It is most likely a non-clustered index, but could possibly be clusteredO d. It is definitely a clustered indexOe. It is definitely a non-clustered index

Explanation: Databases can either have a clustered index or a non-clustered index.Clustered Index:…

Answered: Below shown is a logical representation…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

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The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
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?
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_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
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2. a. Develop a linear trend line for the following data. (Solve manually, using Minitab and using Excel) b. Plot the line and the data on a graph, is linear trend line appropriate. Why or why not? (Use Excel or Minitab) c. Then use the equation to predict the next two values of the series. (Solve manually) d. Compute the coefficient of correlation and coefficient of determination. Interpret. (Solve manually and using Excel) Period 1 2 4 6 7 8 9 Demand 44 52 50 54 55 55 60 56 62 3.
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a. Identify and give a brief explanation of the:i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:i. Derive the values for the intercept and slope. ii. Derive the linear regression equation.iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
b. The following table shows the number of televisions sold over the last ten years at a local electronic store. YEAR 1 2 3 4 5 6 TV SALES 150 300 480 600 630 640 700 825 900 980 7 8 9 10 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.

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