Geries forecasting for Business In a regression model if you drop one insignificant variable then O a. R2will increase and SSE also will increase. O b. None O c. R2 will decrease and SSE also will decrease. O d. R2 will increase but SSE will decrease. O e. R2 will decrease but SSE will increase. CLEAR MY CHOICE US PAGE

Geries forecasting for Business In a regression model if you drop one insignificant variable then O a. R2will increase and SSE also will increase. O b. None O c. R2 will decrease and SSE also will decrease. O d. R2 will increase but SSE will decrease. O e. R2 will decrease but SSE will increase. CLEAR MY CHOICE US PAGE

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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Hi, I need help with solving for the following values (boxed). Thank you.
Which of the following is TRUE regarding the two smoothing constants of the Forecast Including Trend (FIT) model? Select one: a. One constant smoothes the regression intercept, whereas the other smoothes the regression slope. b. One constant is positive, while the other is negative. c. They are called MAD and cumulative error. d. Their values are determined independently. e. Alpha is always smaller than beta.
Qualitative or judgmental forecasting models may use quantitative data. True False
MSE answer for part a = 5.95 is incorrect. Please do recalculations with the correct answer. also the rest of the question was not answered so here it is: Use ? = 0.2 to compute the exponential smoothing values for the time series. Week Time SeriesValue Forecast 1 19 2 14 3 17 4 12 5 18 6 15 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal places.) Use ? = 0.4 to compute the exponential smoothing values for the time series. Week Time SeriesValue Forecast 1 19 2 14 3 17 4 12 5 18 6 15
A company is introducing reusable straws in the market on the 1st of January 2022. They estimate the total market for reusable straws is approximately 3 million per year. The company expects to sell 500000 straws in the first year. There is a competitor already in the market whose sales per year is 1 million straws per year. Your group have been hired as consultants to answer the following questions: What forecasting techniques should the company use for a) sales this year b) sales next year and c) sales in the next five years? Please justify your recommendations. Please provide forecast figures from year 2 to year 5. I want step by step calculation for exponential smoothing for the year 2 to 5 forecast.
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.
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014. Year Period (t) Revenue ($ billions) 2009 1 23.8 2010 29.2 2011 37.9 2012 4 50.3 2013 59.8 2014 6 66.6 (a) Construct a time series plot. 80 80 70 70 70 70 60 60 50 50 50 30 30 30 30- 20 20 20 20 10 10 10 - 10- 4. 6 7 4 6 4 5 6 7 1 2. 4 6 7 Period Period Period Period What type of pattern exists in the data? O The time series plot shows an upward linear trend. O The time series plot shows a downward curvilinear trend. O The time series plot shows a downward linear trend. O The time series plot shows an upward curvilinear trend. (b) Develop a linear trend equation for this time series to forecast revenue (in billions of dollars). (Round your numerical values to three decimal places.) T = (c) What is the average revenue increase per year (in billions of dollars) that this company has been realizing? (Round your answer to three decimal places.) billion Revenue ($ billions) Revenue ($ billions)…
Develop a forecast for the next month using a four-month moving average method. Use the Excel Functions SLOPE and INTERCEPT to write the linear regression prediction equation with Months as the independent variable and sales as the dependent variable. Use the prediction equation to estimate the number of sales in month 9.
After 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 X
What is time series decomposition? Why would a forecaster choose this method versus some of the other methods we've learned in class? In your answer, please make sure to define the components of a time series.
Please do not give solution in image format thanku
Which term most closely relates to associative forecasting techniques? Select one: a. time series data Ob. linear relationships Oc. the Delphi technique O d. consumer survey O e. predictor variables