An organization uses a business intelligence system to predict products that tend to be purchased together. This is an example of A) Regression Analysis O B) Cluster Analysis C) RFM Analysis D) Market Basket Analysis
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- Under what conditions might a firm use multiple forecasting methods?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?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_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.The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). 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?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 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?year quarterly sales (000 units) Q1 Q2 Q3 Q4 2016 1300 1500 1200 2000 2017 1600 1800 1100 2200 2018 1700 1900 1300 2300 2019 1800 2100 1400 2500 Using a simple regression analysis, determine the trend equation of the sales and use it to estimate the number of units of clothing sold throughout the fiscal year 2020. Assume that Q1 of 2016 is 1, Q2 of 2016 is 2, etc. Show all relevant cakculation detail. What are the advantages and disadvantages of Regression Model, Econometric Model, Driving Indicator Models?
- NING SYSTEM (ACADEMIC) Series forecasting for Business || The F-test used in testing the significance of a regression model is O a. Upper tailed test O b. Two tailed test O c. Lower tailed test O d. None OUS PAGEAfter graduation, you take a position at Top-Slice, a well-known manufacturer of golf balls. One of your duties is to forecast monthly demand for golf balls. Using the following data, you developed a regression model that expresses monthly sales as a function of average temperature for the month: Monthly sales=-202.2+86.5x (average temperature) Click the icon to view the additional data. a. Show how the a and 6 values of -202.2 and 86.5 were calculated. Calculate the slope coefficient, b (enter your responses as whole numbers). (745) 12 12 2 =86.5 More Info March 2017 April May June July August September October November December January 2018 February Monthly Sales 5,300 3,990 5,700 6,520 7,600 7,420 Print 6,710 4,870 3,990 3,900 3,320 2,670 Temperature 51 56 Done 64 80 79 87 83 67 58 41 39 40 XThe following data relate the sales figures of the barin Mark Kaltenbach’s small bed-and-breakfast inn in Portand, tothe number of guests registered that week:WEEK GUESTS BAR SALES1 16 $3302 12 2703 18 3804 14 300 a) Perform a linear regression that relates bar sales to guests (notto time).b) If the forecast is for 20 guests next week, what are the salesexpected to be? PX
