# DAT 565 Practice Week 6 Exercise

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Attachments: DAT 565 N2 Practice Week 6 Exercise 2.docx [ Preview Here ] DAT 565 N2 Practice Week 6 Exercise 3.docx [ Preview Here ] DAT 565 N2 Practice Week 6 Exercise.docx [ Preview Here ]

1. Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

(a) Make a line chart and fit an m-period moving average to the exchange rate data shown above with m = 2, 3, 4, and 5 periods. For each method, state the last MA value. (Round your answers to 4 decimal places.)

(b) Which value of m do you prefer?

(c) Is a moving average appropriate for this kind of data?

2)         JetBlue Airlines Revenue,

(a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.)

(b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not round the intermediate calculations. Round your final answers to 2 decimal places.)

3)         U.S. Manufactured General Aviation Shipments, 1984–2016

(a)       Plot the data on U.S. general aviation shipments.

(b) Describe the pattern and discuss possible causes. Hint: What economic factors affect major capital investments? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

(c) Would a fitted trend be helpful? Explain.

(d) Fit a moving average (e.g., period 2) to the data. Is it useful?

(e) Make a forecast for 2016 using a method of your choice (including a judgment forecast). Justify your method. (Round your answer to the nearest whole number.)

4)         Coca-Cola Revenues (\$ millions), 2005–2010

5)         Coca-Cola Revenues (\$ millions), 2005–2010

(a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.)

(a-3) What is the trend model for the deseasonalized time series? (Round your answers to 2 decimal places.)

(b) State the model found when performing a regression using seasonal binaries. (A negative value should be indicated by a minus sign. Round your answers to 4 decimal places.)

(c) Use the regression equation to make a prediction for each quarter in 2011. (Enter your answers in millions rounded to 3 decimal places.)

6)         Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

7)         U.S. Manufactured General Aviation Shipments, 2009–2015

(a) Plot the data on airplane shipments.

(b) Can you see seasonal patterns?

(c) Use MegaStat or Minitab to calculate estimated seasonal indexes and trend. (Round your answers to 3 decimal places.)

(d) In which quarters are shipments highest? Lowest? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

8)         Daily Dollar/Euro Exchange Rate for First 3 Months of 2005 (n = 64 days)

(a) Select an Excel line graph of the exchange rate data which correctly describes the effect of increasing m.

(b) Describe the pattern.

(c) Discuss how this moving average might help a currency speculator.

9)         Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

(a) Make a line chart and fit an m-period moving average to the exchange rate data shown above with m = 2, 3, 4, and 5 periods. For each method, state the last MA value. (Round your answers to 4 decimal places.)

(b) Which value of m do you prefer?

(c) Is a moving average appropriate for this kind of data?

10)       U.S. Civilian Labor Force (thousands)

(a) Make a line graph of the U.S. civilian labor force data.

(b) Describe the trend (if any) and discuss possible causes.

(c) Fit three trend models: linear, exponential, and quadratic. Which model would offer the most believable forecasts? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

11)       Number of Certified Organic Farms

12)       U.S. Treasury 10-Year Bond Yields at Week’s End (n = 52 weeks)

13)       U.S. Manufactured General Aviation Shipments, 1984–2016

14)       U.S. Manufactured General Aviation Shipments, 2009–2015

(a) Plot the data on airplane shipments.

b) Can you see seasonal patterns?

(c) Use MegaStat or Minitab to calculate estimated seasonal indexes and trend. (Round your answers to 3 decimal places.)

(d) In which quarters are shipments highest? Lowest? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

15)       For each of the following fitted trends, make a prediction for period t = 17:

SET 2

1. Coca-Cola Revenues (\$ millions), 2005–2010

(a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.)

(a-3) What is the trend model for the deseasonalized time series? (Round your answers to 2 decimal places.)

(b) State the model found when performing a regression using seasonal binaries. (A negative value should be indicated by a minus sign. Round your answers to 4 decimal places.)

(c) Use the regression equation to make a prediction for each quarter in 2011. (Enter your answers in millions rounded to 3 decimal places.)

2)         Number of Certified Organic Farms

(a) Fit three trends (linear, quadratic, exponential) to the time series. (A negative value should be indicated by a minus sign. Do not round the intermediate calculations. Round your final answers to 2 decimal places.)

(b) Use each of the three fitted trend equations to make numerical forecasts for the next three years. (Round the intermediate calculations to 2 decimal places and round your final answers to 1 decimal place.)

1. Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling
2. U.S. Manufactured General Aviation Shipments, 2009–2015
3. U.S. Manufactured General Aviation Shipments, 1984–2016
4. U.S. Manufactured General Aviation Shipments, 2009–2015

(a) Plot the data on airplane shipments.

(b) Can you see seasonal patterns?

(c) Use MegaStat or Minitab to calculate estimated seasonal indexes and trend. (Round your answers to 3 decimal places.)

(d) In which quarters are shipments highest? Lowest? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

7)         JetBlue Airlines Revenue,

(a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.)

(b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not round the intermediate calculations. Round your final answers to 2 decimal places.)

8)         Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

(a) Make a line chart and fit an m-period moving average to the exchange rate data shown above with m = 2, 3, 4, and 5 periods. For each method, state the last MA value. (Round your answers to 4 decimal places.)

(b) Which value of m do you prefer?

(c) Is a moving average appropriate for this kind of data?

9)         Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

10)       U.S. Civilian Labor Force (thousands)

11)       Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

12)       Daily Dollar/Euro Exchange Rate for First 3 Months of 2005 (n = 64 days)

13)       U.S. Civilian Labor Force (thousands)

(a) Make a line graph of the U.S. civilian labor force data.

(b) Describe the trend (if any) and discuss possible causes.

(c) Fit three trend models: linear, exponential, and quadratic. Which model would offer the most believable forecasts? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

14)       Coca-Cola Revenues (\$ millions), 2005–2010

15)       For each of the following fitted trends, make a prediction for period t = 17:

(a) yt = 2,286e0.076t (Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

(b) yt = 1,149 + 12.78t (Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

(c) yt = 501 + 18.2t – 7.1t2 (A negative value should be indicated by a minus sign. Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

SET 3

1. For each of the following fitted trends, make a prediction for period t = 17:

(a) yt = 2,286e0.076t (Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

(b) yt = 1,149 + 12.78t (Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

(c) yt = 501 + 18.2t – 7.1t2 (A negative value should be indicated by a minus sign. Do not round the intermediate calculations. Round your final answer to 1 decimal place.)

2)         U.S. Civilian Labor Force (thousands)

(a) Make a line graph of the U.S. civilian labor force data.

(b) Describe the trend (if any) and discuss possible causes.

(c) Fit three trend models: linear, exponential, and quadratic. Which model would offer the most believable forecasts? (You may select more than one answer. Click the box with a check mark for the correct answer and double click to empty the box for the wrong answer.)

(d) Make forecasts using the following fitted trend models for years 2017-2019. (Round your answers to the nearest whole number.)

3)         U.S. Manufactured General Aviation Shipments, 2009–2015

(a) Plot the data on airplane shipments.

(b) Can you see seasonal patterns?

(c) Use MegaStat or Minitab to calculate estimated seasonal indexes and trend. (Round your answers to 3 decimal places.)

4)         Coca-Cola Revenues (\$ millions), 2005–2010

(a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.)

(a-3) What is the trend model for the deseasonalized time series? (Round your answers to 2 decimal places.

(b) State the model found when performing a regression using seasonal binaries. (A negative value should be indicated by a minus sign. Round your answers to 4 decimal places.)

(c) Use the regression equation to make a prediction for each quarter in 2011. (Enter your answers in millions rounded to 3 decimal places.)

5)         Coca-Cola Revenues (\$ millions), 2005–2010

(a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.)

(a-3) What is the trend model for the deseasonalized time series? (Round your answers to 2 decimal places.)

(b) State the model found when performing a regression using seasonal binaries. (A negative value should be indicated by a minus sign. Round your answers to 4 decimal places.)

(c) Use the regression equation to make a prediction for each quarter in 2011. (Enter your answers in millions rounded to 3 decimal places.)

6)         U.S. Manufactured General Aviation Shipments, 2009–2015

7)         U.S. Treasury 10-Year Bond Yields at Week’s End (n = 52 weeks)

8)         Number of Certified Organic Farms

9)         Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

10)       U.S. Civilian Labor Force (thousands)

11)       Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

(a) Make a line chart and fit an m-period moving average to the exchange rate data shown above with m = 2, 3, 4, and 5 periods. For each method, state the last MA value. (Round your answers to 4 decimal places.)

(b) Which value of m do you prefer?

(c) Is a moving average appropriate for this kind of data?

12)       Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

13)       U.S. Manufactured General Aviation Shipments, 1984–2016

14)       Daily Dollar/Euro Exchange Rate for First 3 Months of 2005 (n = 64 days)

(a) Select an Excel line graph of the exchange rate data which correctly describes the effect of increasing m.

15)       Daily Spot Exchange Rate, U.S. Dollars per Pound Sterling

(a) Make a line chart and fit an m-period moving average to the exchange rate data shown above with m = 2, 3, 4, and 5 periods. For each method, state the last MA value. (Round your answers to 4 decimal places.)

(b) Which value of m do you prefer?

(c) Is a moving average appropriate for this kind of data?

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