The Bayside Hotel wants to develop forecasts for occupancy rates based on the occupancy rates for the past 9 years: Year 1 2 3 4 5 6 7 8 9 10 Occupancy Rate 0.83 0.78 0.75 0.81 0.86 0.85 0.89 0.90 0.86 ? If the coefficients for a linear trendline were a = 0.73 and b=0.018. what would the forecast for Year 10 be?
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- The US. import of wine (in hectoliters) for several years is given in Table 5. Determine whether the trend appearslinear. Ifso, and assuming the trend continues, in what year will imports exceed 12,000 hectoliters?A coffee shop owner wants to estimate demand for the next four quarters for hot chocolate. Sales data consist of trend and seasonality. Quarter relatives are 1.06 for the first quarter, 1.03 for the second quarter, 0.61 for the third quarter, and 1.30 for the fourth quarter. Using the appropriate values of quarter relatives and the equation Ft = 187 +9.2t for the trend component, estimate demand for periods 9-12. (Round all calculations to two decimal points. Demand Period 9 Demand Period 10 Demand Period 11. Demand Period 12If a trend line had the equation y = 2.7x+0.82, what y-value would you expect to obtain when x has the following values? а. 14 b. 0 c. 4.2 d. 7.9 a. When x = 14, y =. (Type an integer or decimal rounded to the nearest hundredth as needed.) b. When x = 0, y =- (Type an integer or decimal rounded to the nearest hundredth as needed.) c. When x = 4.2, y =. (Type an integer or decimal rounded to the nearest hundredth as needed.) d. When x= 7.9, y =. (Type an integer or decimal rounded to the nearest hundredth as needed.) Enter your answer in each of the answer boxes. W P Type here to search 17
- The following table gives the average monthly exchange rate between the U.S. dollar and the euro for 2009. It shows that 1 euro was equivalent to 1.289 U.S. dollars in January 2009. Develop a trend line that could be used to predict the exchange rate for 2010. Use this model to predict the exchange rate for January 2010 and February 2010. MONTH ______________________ EXCHANGE RATE January ....................................... 1.289 February ...................................... 1.324 March ......................................... 1.321 April .......................................... 1.317 May ........................................... 1.280 June ........................................... 1.254 July ........................................... 1.230 August ....................................... 1.240 September ................................... 1.287 October ..................................... 1.298 November .................................. 1.283 December…A bank wanted to find out whether the number of loan applications received are influenced by the current loan interest rate. The manager selected 11 monthly periods for which different interest rates applied and recorded the number of loan applications received. (b) Show the data graphically in a scatter plot. What relationship is observed? SHOW SOLUTION PLEASE!r 31. You are given the following trend equation : Y 50 +.8X Origin 2012 ; X units one year ; Y units-profits in (000) rupees. Convert the trend equation to a monthly trend equation and shift the origin to Jan. 1, 2013. aigin on Ist Jul2012 1st 1, i,
- If a trend line had the equation y= 3.5x + 0.03, what y-value would you expect to obtain when x has the following values? a. 12 b. 0 c. 5.8 d. 7.3 a. When x = 12, y=. (Type an integer or decimal rounded to the nearest hundredth as needed.) b. When x= 0, y= . (Type an integer or decimal rounded to the nearest hundredth as needed.) c. When x = 5.8, y = (Type an integer or decimal rounded to the nearest hundredth as needed.) d. When x= 7.3, y=. (Type an integer or decimal rounded to the nearest hundredth as needed.) Enter your answer in each of the answer boxes.Monthly sales have been found to follow a linear trend of y = 10 + 8x, where y is the number of items sold and x is the number of the month. Monthly deviations from the trend have been calculated and follow an additive model. In month 12, the seasonal variation is estimated to be -6. What is the forecasted number of items to be sold in month 12?b) The following are the quarterly index numbers of whole sale prices: Year 1928 1929 1930 1931 1932 1933 1934 Values 125 112 136 142 118 120 122 Fit a linear trend to these data and find trend values(Y). Take the deviations of the observed values(Y) and verify that E(Y-Y^)=0.
- Consider the following estimated trend models. Use them to make a forecast for t = 20.a. Linear Trend: yˆy^ = 12.86 + 1.09t (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) Quadratic Trend: yˆy^ = 18.58 + 0.89t − 0.01t2 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) c. Exponential Trend: ln(y)ˆln(y)^ = 1.9 + 0.07t; se = 0.05 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)Consider the following estimated trend models. Use them to make a forecast for t= 22. a. Linear Trend: ý = 12.42 + 1.13t (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) b. Quadratic Trend: û = 18.04 + 1.04t - 0.02t2 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) c. Exponential Trend: In(y) = 1.6 + 0.08t, se = 0.01 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives are SR1 = 0.9, SR2 = 0.95, SR3 = 1.05, and SR4 = 1.1. The trend equation is: Ft = 11 + 3t. Over the past nine quarters, demand has been as follows: %3D Period, t: 2 4 5 7 8 9. Demand: 15 17 20 23 25 29 34 36 39 Click here for the Excel Data File Compute the MAD and tracking signal for each period. (Negative values should be indicated by a minus sign. Round your intermediate calculations and final answers to 3 decimal places.) Period, t Demand MAD Tracking signal 1 15 2 17 3 20 4 23 5 25 29 7 34 36 39