Question 5We have a dataset of different countries and we want to generate an indicator that indicateswhether the country is in Africa or not. We also have a variable named "continent" that is acategorical string variable indicating the continent of the country. What is the correct syntax togenerate an indicator variable named Africa that is equal to 1 if the country is in Africa and 0otherwise:gen Africa = (continent=="Africa")gen Africa = (continent==Africa)gen Africa= (continent = "Africa")gen Africa = 1 if continent== "Africa"

Explanation : The correct syntax to generate an indicator variable named "Africa" that is equal to 1…

Answered: We have a dataset of different…

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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Seasonal patterns often occur in time series. The ratio-to-moving-average method facilitates the calculation of a seasonal adjustment factor to smooth out seasonal variations by “de-seasonalizing the data”. This process begins by tabulating data by quarter and calculating a centered moving average. In Year 1, quarterly sales were: 4000; 2000; 1000; 3000. Notice: no commas. 1. The four-quarter moving total is 2. This number is placed on the line between which two quarters? ____ and ____ (Use symbols I, II, III, IV) In Quarter I of Year 2, sales were 4000 3. The four-quarter moving total is ____ 4. This number is placed on the line between which two quarters? ____ and ____ (Use symbols I, II, III, IV) 5. The average of moving totals is ____ 6. The four-quarter moving average is ____ 7. The ratio to moving average for Quarter III of the first year is ___%
11
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Please help with correct answers in details: Step by step Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in Bennington, Vermont, over the past 12 weeks. Week Sales (1,000sof gallons) 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 (a) Compute four-week and five-week moving averages for the time series. Week Time SeriesValue 4-WeekMovingAverageForecast 5-WeekMovingAverageForecast 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 b) Compute the MSE for the four-week moving average forecasts. (Round your answer to two decimal places.) c) Compute the MSE for the five-week moving average forecasts. (Round your answer to two decimal places.) d) What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation? MSE for the three-week moving average is 9.65.…
ANSWER 7 AND 8 ONLY
the coefficient
A10
For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are: Monthly Proportion of All Shipments Received On Time 80 81 85 83 84 86 85 85 82 81 85 84 Estimate the average of MSE of a three-month moving average and an exponential smoothingfor α = 0.3. Group of answer choices 1.24 2.4 3.56 4.25 4.58
The manager wants to forecast the month 6's sales using the following historical data: Months Month 1 Month 2 Month 3 Month 4 Month 5 Sales 20 25 32 35 38 Please use the weight 0.45 for Month 5, weight 0.25 for Month 4, weight 0.2 for Month 3, and weight 0.1 for Month 2 to use the weighted moving average to forecast the demand of Month 6. Month 5 = 0.1*(25) +0.2*(32) + .25* (35) divided by 0.1 +0.2 +1.25 -17.65/0.55 = 32.09 Month 6= 0.1* (25) +0.2* (32) +0.25 (35) +0.45* (38) divided by 0.1 +0.2+0.45 = 34.75
Show that if ˆ is an unbiased estimator of θ andvar()ˆ Z 0, then ˆ 2 is not an unbiased estimator of θ 2.
Forecasting method A has errors of 10, -15, 5 and 20. Forecasting method B has errors of -10, 4, 16 and -8. The MAD of method A is equal to The MAD for method B is equal to is more accurate than method Based on MAD, method
4. The number of auto accidents in Athens, Ohio, is related to the regional number of registered automobiles in thou- sands (X1), alcoholic beverage sales in $10,000s (X2), and rainfall in inches (X3). Furthermore, the regression formula has been calculated as: Y=a+b1X1 +b2X2 +b3X3 Where Y = number of automobile accidents a = 7.5 bl = 3.5 b2 = 4.5 b3 = 2.5 Calculate the expected number of automobile accidents under conditions a, b, and c: X, X2 X, (a) 2 3 (b) 5 1 (c) 7 2 N m4

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